CN106950842B - Decoupling control method and device, robot and storage medium - Google Patents
Decoupling control method and device, robot and storage medium Download PDFInfo
- Publication number
- CN106950842B CN106950842B CN201710353270.4A CN201710353270A CN106950842B CN 106950842 B CN106950842 B CN 106950842B CN 201710353270 A CN201710353270 A CN 201710353270A CN 106950842 B CN106950842 B CN 106950842B
- Authority
- CN
- China
- Prior art keywords
- moment
- motion control
- vector
- determining
- parameters
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 105
- 238000003860 storage Methods 0.000 title claims abstract description 19
- 230000033001 locomotion Effects 0.000 claims abstract description 243
- 239000013598 vector Substances 0.000 claims abstract description 160
- 239000011159 matrix material Substances 0.000 claims abstract description 102
- 230000008569 process Effects 0.000 claims abstract description 33
- 230000001133 acceleration Effects 0.000 claims description 36
- 238000001914 filtration Methods 0.000 claims description 9
- 238000000354 decomposition reaction Methods 0.000 claims description 8
- 230000008878 coupling Effects 0.000 claims description 3
- 238000010168 coupling process Methods 0.000 claims description 3
- 238000005859 coupling reaction Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 description 32
- 238000005070 sampling Methods 0.000 description 20
- 230000006870 function Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 238000005259 measurement Methods 0.000 description 5
- 238000009826 distribution Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 230000003044 adaptive effect Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 244000145845 chattering Species 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- 206010044565 Tremor Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000001808 coupling effect Effects 0.000 description 1
- 239000012467 final product Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- -1 period Chemical class 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
- 210000000707 wrist Anatomy 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Mechanical Engineering (AREA)
- Robotics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Feedback Control In General (AREA)
Abstract
The invention discloses a decoupling control method, a decoupling control device, a robot and a storage medium. The decoupling control method comprises the following steps: acquiring an inertia matrix of a motion control object, system parameters and operation parameters at the current moment in the operation process; determining a corresponding diagonal matrix according to the inertia matrix; determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters; determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix; determining a moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector; and taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object. By adopting the method, the existing decoupling method can be optimized, and the decoupling of the motion control object can be simply and effectively realized.
Description
Technical Field
The invention relates to the technical field of robot control, in particular to a decoupling control method, a decoupling control device, a robot and a storage medium.
Background
The mechanical arm is a mechanical electronic device simulating the functions of a human arm, a wrist and a hand. It can move any object or tool according to the time-varying requirement of space pose (position and posture), so as to meet the operation requirement of some industrial production. A typical robot arm is composed of several joints and links connected in series, each joint having one degree of freedom and being able to translate or rotate. It can be seen that the robotic arm is a multiple-input multiple-output kinematic system. Therefore, in practical applications, the mechanical arms will have mutual influence among joints, and a coupling effect is generated, that is, the input signal of each control loop in the dynamic system will have influence on the output of all the loops, and the output of each loop will be affected by all the inputs. In view of the above, decoupling has become an urgent technical problem to be solved in the application of mechanical arms.
Existing mechanical arm decoupling methods typically include: a moment calculation method, an adaptive control method and a sliding mode control method. The moment calculation method requires an accurate dynamic model and requires a large amount of real-time calculation, and since the mechanical structure of the mechanical arm is very complex, it is difficult to derive an accurate mathematical model expression. The adaptive control method takes into account the variability of the model parameters and then adapts the dynamic model adaptively according to the variability, however, the adaptive control method still requires a large amount of calculation. The sliding mode control method does not need an accurate dynamic model and has strong robustness on parameter change of load disturbance, but the sliding mode control method can cause vibration of the mechanical arm. In conclusion, the existing mechanical arm decoupling method cannot simply and effectively achieve decoupling of the mechanical arm.
Disclosure of Invention
In view of this, embodiments of the present invention provide a decoupling control method and apparatus, a robot, and a storage medium, so as to optimize an existing mechanical arm decoupling method and simply and effectively implement decoupling on a mechanical arm.
In a first aspect, an embodiment of the present invention provides a decoupling control method, including:
acquiring an inertia matrix of a motion control object, system parameters and operation parameters at the current moment in the operation process;
determining a corresponding diagonal matrix according to the inertia matrix;
determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters;
determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix;
determining the moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector;
and taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
In a second aspect, an embodiment of the present invention further provides a decoupling control apparatus, including:
the parameter acquisition module is used for acquiring an inertia matrix of the motion control object, system parameters and operation parameters at the current moment in the operation process;
the diagonal matrix determining module is used for determining a corresponding diagonal matrix according to the inertia matrix;
the control moment determining module is used for determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters;
the moment compensation determining module is used for determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix;
the moment vector determining module is used for determining the moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector;
and the output value determining module is used for taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
In a third aspect, an embodiment of the present invention further provides a robot, including:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the decoupling control method of the first aspect.
In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the decoupling control method according to the first aspect.
According to the decoupling control method, the decoupling control device, the robot and the storage medium, the control moment vector and the corresponding moment compensation vector are determined by obtaining the inertia matrix of the motion control object, the system parameters and the operation parameters at the current moment in the operation process, so that the final moment output value of each motion control sub-object in the motion control object is obtained, the motion control object is simply and effectively decoupled, meanwhile, on the premise that the decoupling accuracy is guaranteed, a complex decoupling model is not required to be constructed, and a good decoupling effect can be achieved only through simple calculation.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
fig. 1a is a flowchart of a decoupling control method according to an embodiment of the present invention;
FIG. 1b is a schematic view of a robot with a motion control object installed thereon;
fig. 2a is a flowchart of a decoupling control method according to a second embodiment of the present invention;
FIG. 2b is a flow chart of a method of determining a control input vector;
FIG. 2c is a flow chart of a method of exercise planning;
FIG. 2d is a flow chart of a method of determining a control torque vector;
FIG. 2e is an algorithm diagram of the decoupling control method;
FIG. 2f is a flow chart of a decoupling control method;
fig. 3 is a schematic structural diagram of a decoupling control device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a robot according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings.
Example one
Fig. 1a is a flowchart of a decoupling control method according to an embodiment of the present invention. The decoupling control method provided by the embodiment is suitable for the situation of decoupling the motion control object in the operation process of the motion control object. The decoupling control method provided by the embodiment can be executed by a decoupling control device, and the decoupling control device can be realized in a software and/or hardware manner and is integrated in a robot provided with a motion control object. The robot is a machine device that can automatically perform work. It can accept human command, run the program programmed in advance, and also can operate according to the principle outline action made by artificial intelligence technology. For example, mobile forklift trucks and equipment with robotic arms are all robots.
Typically, when inertia, friction, clearance, and saturation of the motion control object are not considered, the kinetic equation of the motion control object can be expressed as:
wherein, tau1Representing the torque output by the motion control object in an ideal state. Theta represents the generalized coordinates of the kinetic and potential energy of the motion control object, which may also be referred to as the position vector of the motion control object,is a velocity vector corresponding to theta and,is the acceleration vector corresponding to theta. D (θ) is an inertia matrix whose dimensions are related to the number of motion control sub-objects.Are the centrifugal and coriolis force vectors, whose dimensions are also related to the number of motion control sub-objects. G (θ) is a gravity vector whose dimensions are also related to the number of motion control sub-objects.
In practical applications, when the moment control motion control object determined according to equation (1) moves, a coupling phenomenon is usually generated between each motion control sub-object in the motion control object. Therefore, in this embodiment, it is proposed to obtain the torque vector actually output by each motor of the motion control object by determining the motor control parameter and the torque compensation parameter of each motion control sub-object, so as to decouple the motion process of the motion control object.
Referring to fig. 1a, a decoupling control method provided in this embodiment specifically includes:
and S110, acquiring an inertia matrix of the motion control object, system parameters and operation parameters at the current moment in the operation process.
In this embodiment, the motion control object comprises at least two movable motion control sub-objects, each motion control sub-object being provided with a corresponding drive motor. Taking a motion control object as an example of a mechanical arm, the corresponding motion control sub-object consists of a joint and a corresponding connecting rod, and each joint is provided with a driving motor for controlling the translation or rotation of the joint.
Fig. 1b is a schematic structural diagram of a robot with a motion control object installed thereon, which specifically includes an upper computer 11, a driver 12, and a motion control object 13. The upper computer 11 may specifically include at least one processor and a storage device, and is configured to execute the decoupling control method provided in this embodiment, and the driver 12 and the motion control object 13 may be collectively referred to as a motion control device. Typically, the upper computer 11 is installed with a real-time Linux operating system and can communicate with the driver 12 through a portal using a real-time industrial fieldbus protocol. The real-time industrial fieldbus protocol may include: a high-level communication protocol (also called CANOpen) or an ethernet control automation technology (also called EtherCAT) protocol configured on a Controller Area Network (CAN). The driver 12 is connected to the upper computer 11 through a bus, and is configured to control the motion control object 13 to move according to the torque output value determined by the upper computer 11, where the driver 12 and the motion control object 13 may be connected through a bus or electrically, and fig. 1b illustrates electrical connection. Generally, the driver 12 controls the motion control object 13 to move, which means that a motor of a corresponding motion control sub-object is controlled to operate. Optionally, the motion control object 13 further includes an encoder (not shown), which can read parameters such as the operation angle and speed of the motor and send the generated encoded data to the driver 12. The driver 12 measures and converts the readings of the encoder, and feeds back the converted results to the upper computer 11 through the bus. In general, the measured parameters (operating parameters) obtained by measurement, which are referred to in the following embodiment processes, can be understood as data obtained by measurement of an encoder. The robot described above is for explanation only, and is not intended to limit the robot to which the motion control object is attached in the present embodiment.
Further, a dinavit-Hartenberg (DH) coordinate system is established for the motion control object, so as to determine the position data of each motion control sub-object according to the coordinate system, and further determine a pose matrix of the motion control object, wherein the pose matrix generally refers to the position of each operation control sub-object joint in the DH coordinate system.
In particular, the inertia matrix, which may also be referred to as an inertia matrix, is determined from the mass, the centroid position, and the inertia tensor of each motion control sub-object. When the position data of the motion control sub-object changes, the corresponding centroid position and inertia tensor also change, and further the specific value of the inertia matrix also changes correspondingly. In determining the inertia tensor, it is necessary to consider the influence of the motion control sub-object adjacent to the current motion control sub-object on the current motion control sub-object.
In a complete decoupling control process, system parameters are generally unchanged, can be set according to actual conditions, and have no fixed value range. Generally, before decoupling the motion control object, a corresponding calculation model may be preset to achieve parameter calculation. The fixed parameters used in the calculation of the calculation model may be referred to as system parameters. In the present embodiment, the calculation model is preferably a control input model, which is used in particular for determining the control input vector.
The operation parameter refers to a physical quantity obtained by measurement during the operation or movement of the motion control object. Which include, but are not limited to: the operating time, the position of the motion control object, the angular velocity of the motion control object, and the moment parameter of the motion control object. The position of the motion control object refers to an angle at which the motor of each motion control sub-object operates, and the angular velocity of the motion control object refers to an angular velocity at which the motor of each motion control sub-object operates. The operating parameters are typically represented in the form of vectors, each of which corresponds to a parameter associated with one of the motion control sub-objects. In general, the operating parameters may be obtained by an encoder.
Optionally, a sampling period is preset, and the data is acquired according to the sampling period interval.
And S120, determining a corresponding diagonal matrix according to the inertia matrix.
Generally, the inertia matrix is a diagonally symmetric matrix. When determining the diagonal matrix of the inertia matrix, the eigenvalue of the inertia matrix may be calculated, and the eigenvalue of the inertia matrix may be used as a value on the diagonal of the diagonal matrix. Assuming a total of N motion control sub-objects, there are a total of N eigenvalues as values on the diagonal in the diagonal matrix.
And S130, determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters.
The control moment vector can be understood as the moment that the motor of each motion control sub-object should output, namely the motor control parameter, calculated according to the inertia matrix, the system parameter and the operation parameter.
Furthermore, when determining the control moment vector, first, the control parameters to be input to each motion control sub-object at the current time are determined according to the operation parameters of each motion control sub-object, and are recorded as the control input vectors. When determining the control input vector, a control input model may be set in advance, where the control input model calculates the control input vector, the input quantity is an operating parameter, and the model parameter is a system parameter. Generally, the control input model is determined and then unchangeable in a complete decoupling control process. Optionally, the control input model may adopt a control regulation mode such as proportional-integral control, proportional control or proportional-derivative control. Preferably, proportional-integral control is employed.
After the control input vector is determined, the control input vector and the diagonal matrix are subjected to multiplication to obtain a control moment vector. The dimensions of the control moment vector and the control input vector are the same as the quantity value of the motion control sub-object.
And S140, determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix.
For example, the torque compensation vector may be understood as a compensation parameter determined according to an actual torque currently output by the motion control object, and the control torque vector is compensated according to the compensation parameter, so as to ensure accuracy of a finally output torque vector.
Furthermore, the moment compensation vector can be determined by combining the current moment parameters actually output in the operation parameters with the current angular acceleration and the diagonal matrix of each motion control sub-object at the current moment. Specifically, the diagonal matrix and the current angular acceleration are subjected to multiplication, and the difference is made between the current moment parameter and the multiplication result to obtain a moment compensation vector. The moment compensation vector dimension is the same as the magnitude of the motion control sub-object.
And S150, determining the moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector.
Specifically, the control moment vector and the moment compensation vector are added to obtain the moment vector of the motion control object at the current moment. The torque vector can also be understood as the result of a torque compensation of the control torque vector. The moment vector dimension is the same as the magnitude of the motion control sub-object.
And S160, taking each numerical value in the moment vector as a moment output value of the corresponding motion control sub-object in the motion control object.
After the moment vector is determined, the moment vector is sent to the driver through the bus, so that the driver controls the motor of each motion control sub-object to operate according to the moment vector. Each specific numerical value in the moment vector corresponds to a moment output value of the motion control sub-object.
Optionally, after controlling each motion control sub-object to move according to the moment vector, if the motion control object does not stop moving, continuing to use the next sampling time as the current sampling time, and returning to S110 to re-determine the moment vector at the next sampling time until the motion control object stops moving.
According to the technical scheme provided by the embodiment, the control moment vector and the corresponding moment compensation vector are determined by obtaining the inertia matrix of the motion control object, the system parameters and the operation parameters at the current moment in the operation process, so that the final moment output value of each motion control sub-object in the motion control object is obtained, the motion control object is decoupled simply and effectively, and meanwhile, on the premise of ensuring the decoupling accuracy, a complex decoupling model is not required to be constructed, and a good decoupling effect can be achieved only through simple calculation.
Example two
Fig. 2a is a flowchart of a decoupling control method according to a second embodiment of the present invention. The present embodiment is embodied on the basis of the above-described embodiments. Specifically, referring to fig. 2a, the decoupling control method provided in this embodiment specifically includes:
s210, obtaining an inertia matrix of the motion control object, system parameters and operation parameters of the current moment in the operation process.
And S220, performing singular value decomposition on the inertia matrix to obtain a diagonal matrix.
Setting the inertia matrix as D and the diagonal matrix asBecause D is an oblique symmetric matrix, D can be obtained when singular value decomposition is carried out on D:
wherein D' is a unitary matrix corresponding to D. Can be calculated according to the formula (2)At this time, the values on the diagonal in the diagonal matrix are eigenvalues obtained by singular value decomposition.
And S230, determining a control input vector of the motion control object according to the system parameters and the operation parameters.
In the present embodiment, the control input model adopts proportional-integral control, i.e., a proportional-integral (PI) regulator is used to determine the control input vector. The PI regulator can realize that integral control is added in time on the basis of proportional control to eliminate control deviation, and is particularly suitable for scenes with high control precision requirements, such as decoupling scenes in the embodiment. Further, the system parameters include: the specific values of the proportional parameter and the integral parameter in the PI regulator can be set according to the actual situation.
Specifically, referring to fig. 2b, the method for determining the control input vector is as follows:
and S231, determining the target operation parameters of the motion control object at the current moment according to the operation moments in the operation parameters.
The target operating parameter may also be referred to as an ideal operating parameter, which indicates an operating state that the motion control object should reach at the current time in the ideal state. When determining the target operation parameters, the motion planning needs to be performed on the operation state of the motion control object during the initial operation of the motion control object, and the target operation parameters at each operation time are determined according to the motion planning result. A motion planning may also be understood as a planning of the operation of the individual motors of the motion control object. The target operation parameter is expressed in a vector form, and the dimension of the target operation parameter is the same as the quantity value of the motion control sub-object.
In the motion planning of the motion control object, various existing motion planning methods can be adopted, and in the embodiment, a quintic polynomial method is exemplarily selected for the motion planning. In the following, an exemplary description is given of the motion planning based on the quintic polynomial method, specifically, referring to fig. 2c, the motion planning method provided in this embodiment specifically includes S290-S2100:
and S290, acquiring initial parameters of the initial running time of the motion control object.
Specifically, the operation planning process of the quintic polynomial method can be expressed as:
S(t)＝a0+a1t+a2t2+a3t3+a4t4+a5t5 (3)
wherein, a0、a1、a2、a3、a4And a5And (t) is a planning coefficient, t is the current operation time of the motion control object, and S (t) is an operation planning result at the time t. From the above equations, it can be seen that motion control is determined if desiredThe operation planning result of the object needs to specify the specific value of the planning coefficient, and the specific value of the planning coefficient can be determined according to the initial parameter. Accordingly, it is necessary to obtain initial parameters of the initial operation time of the motion control object to determine the planning coefficients according to the initial parameters.
Optionally, the initial parameters include: the sampling period, the initial position, the initial angular velocity and the initial angular acceleration of the actual operation of the motion control object at the initial operation time, and the initial parameters further include: ideally, the initial operation time moves a target initial position, a target initial angular velocity, and a target initial angular acceleration that the control object is expected to reach. Wherein, the sampling period is the sampling interval of each parameter in the moving process of the motion control object.
It should be noted that the various types of position parameters (initial position, target position, and position of the motion control object) referred to in this embodiment can be understood as the operation angle of the motor of each motion control sub-object; various angular velocity parameters (initial angular velocity, target angular velocity, and angular velocity of the motion control object) can be understood as the operation angular velocity of the motor of each motion control sub-object; the angular acceleration parameter is similar to the angular velocity parameter, and is not described herein.
And S2100, performing motion planning on the motion control object according to the initial parameters to determine target operation parameters corresponding to the operation time according to the motion planning result.
Illustratively, the planning coefficients in equation (3) are determined based on the initial parameters.
Taking a motion control sub-object as an example, a sampling period T, an initial position θ (0), and an initial angular velocity are setInitial angular accelerationTarget initial position θ0Target initial angular velocityAnd target initial angular accelerationThen it can be found that:
a0＝θ(0) (4-1)
further, after determining the planning coefficients, equation (3) can be expressed as:
θ1(t)＝a0+a1t+a2t2+a3t3+a4t4+a5t5 (5)
wherein, theta1(t) represents a target position at which the motion control sub-object is expected to operate at the operation time t. By performing a differential calculation on equation (5), it is possible to obtain:
wherein,which represents the target angular velocity at which the motion control sub-object is expected to operate at the operating time t. Performing differential calculation on equation (6)Obtaining:
wherein,which represents the target angular acceleration at which the motion control sub-object is expected to operate at the operating time t.
Further, equations (5), (6) and (7) are motion planning equations for one motion control sub-object. According to the method, a motion planning formula of all the motion control sub-objects can be constructed. In practical application, each initial parameter can be expressed and calculated in a vector form, and each value in the vector corresponds to one motion control sub-object. Taking the initial position as an example, each value in the corresponding vector corresponds to the initial position of one motion control sub-object. This has the advantage that only one motion planning is needed to obtain the motion planning result for all motion control sub-objects.
It should be noted that, in the actual process, at least one motion planning formula may be selectively constructed in the formula (5), the formula (6), and the formula (7) according to the actual situation, and the target operation parameters corresponding to the operation time are determined according to the constructed motion planning formula, where the target operation parameters include: at least one of a target position, a target angular velocity, and a target angular acceleration.
And S232, determining a control input vector of the motion control object according to the target operation parameter, the operation parameter and the system parameter.
Wherein the system parameters include: proportional and integral parameters, the operating parameters including: the operating time, the position of the moving control object and the angular velocity of the moving control object, the target operating parameters including: a target position, a target angular velocity, and a target angular acceleration.
The formula for determining the control input vector u is as follows:
wherein, theta1(t)，And respectively representing the target position, the target angular velocity and the target angular acceleration of the motion control object corresponding to the running time t, wherein the target position, the target angular velocity and the target angular acceleration can be determined through a motion planning result and are all in a vector form. θ' (t) andthe position of the motion control object and the angular velocity of the motion control object corresponding to the operating time t are respectively represented, which can be determined by a driver reading the data of the encoder, and are both in vector form. At theta1(t) for example, wherein each value represents the target position of one motion control sub-object at time t. Kp1And Kp2As a proportional parameter, Ki1And Ki2Is an integral parameter, and Kp1、Kp2、Ki1And Ki2Are diagonal matrices whose dimensions are related to the number of motion control sub-objects. For example, if the number of motion control sub-objects is set to 5, then the dimensions of the system parameters are all 5 × 5.
As can be seen from the above formula, the control input model in this embodiment specifically includes two proportional-integral links, one of which is specific to the target position and the position of the motion control object, and the other is specific to the target angular velocity and the angular velocity of the motion control object, so that the accuracy of the finally obtained control input vector can be ensured.
And S240, performing multiplication operation on the diagonal matrix and the control input vector to obtain a control moment vector.
Specifically, in order to suppress the influence of high-frequency chattering in the control torque vector on the calculation accuracy, the calculation result is filtered by a low-pass filter after multiplication calculation, so as to suppress the high-frequency chattering. Referring to fig. 2d, this step specifically includes:
and S241, performing multiplication operation on the diagonal matrix and the control input vector.
Illustratively, setting C denotes the result of the multiplication, i.e.
And S242, taking the result obtained by the multiplication operation as the input of a low-pass filter, and taking the result obtained after filtering as a control moment vector.
Specifically, a first-order low-pass filter is taken as an example for description:
the filtering formula of the first-order low-pass filter is as follows:
in the formula (9), λ is a cutoff frequency, s is an independent variable, and f(s) is a laplace transform amount. In practical applications, in order to simplify the computer implementation process, when filtering with a first-order low-pass filter, a differential difference equation is preferably used, which specifically includes:
Y(t)＝aX(t)+(1-a)Y(t-T') (10)
where T 'is the sampling frequency of the first-order low-pass filter, which may be the same as or different from the sampling period of the operating parameter, x (T) is the input signal of the first-order low-pass filter at the current time, i.e., C, T is the current time, Y (T-T') is the output signal of the first-order low-pass filter based on the previous sampling time of the current time, a ═ λ · 2 π T ', λ is the cutoff frequency of the first-order low-pass filter, Y (T) is the output signal of the current time, i.e., the control torque vector, which is denoted as C'.
And S250, determining the current angular acceleration of the motion control object according to the operation parameters.
Generally, the position and angular velocity of the motion control object at the current time can be directly measured, and the corresponding current angular acceleration needs to be calculated. The current angular acceleration obtained by calculation is also in a vector form, and the dimension is the same as the quantity value of the motion control sub-object.
Specifically, in order to ensure the accuracy of the current angular acceleration, in this embodiment, a motion planning method is used to determine the target angular acceleration at the current time, and the actual angular acceleration calculated by the operation parameters is corrected according to the target angular acceleration, so as to obtain the final current angular acceleration.
The following describes an exemplary method of determining the current angular acceleration:
specifically, in order to reduce the amount of calculation, motion planning is generally performed only once in a complete decoupling process, and equation (5), equation (6), and/or equation (7) may be directly used in this step, and equation (7) is preferably used.
Further, the position θ' (t) of the motion control object or the angular velocity of the motion control object corresponding to the operation time t is usedCalculating angular acceleration as actual angular acceleration by differential calculation
Specifically, the determination is made based on θ' (t)The formula of time is as follows:
where T is a sampling period, θ ' (T) is a position of the motion control object, T is an operating time, θ ' (T-T) is a position of the motion control object at a history time corresponding to a previous sampling period based on the current time, and θ ' (T-2T) is a position of the motion control object at a history time corresponding to a previous sampling period based on the current time. From the above equation, the second differential calculation of θ' (t) can be obtained
According toDeterminingThe formula of time is as follows:
wherein, T is the sampling period,for the purpose of moving the angular velocity of the control object, t is the moment of operation,the angular velocity of the object is controlled for movement at a historical time corresponding to a sampling period prior to the current time. The above formula shows thatPerforming a differential calculation to obtain
Is calculated to obtainThen, using a low-pass filter pairFiltering is performed to suppress high-frequency noise to some extent and amplify errors in differential calculation, and the filtered data is recorded asThe low-pass filter may be a first-order low-pass filter, and the specific filtering manner of the low-pass filter is the same as the filtering manner mentioned in S242, which is not described herein again.
Further, the signal is processed by a Bayesian filterAnd target angular accelerationFusing to obtain the current angular acceleration of the current time
Wherein,andall approximately satisfy the Gaussian distribution, andthe corresponding first variance value is greater thanThe corresponding second variance value. Specifically, when the setting satisfies the gaussian distribution,can be recorded asRtIs a first variance value, which can be determined from the analysis of historical actual angular acceleration.Can be recorded asQtThe second variance value may be set according to a control effect expected to be achieved when the motion control object operates. Generally, QtThe smaller the control of the motion control object is, the more precise the control of the motion control object is when it is running. In general, RtGreater than QtCan explainIs higher than the confidence level ofThe confidence of (c). In other words, set RtGreater than QtCan ensure the final productAnd is more accurate.
Obtained by fusion of Bayesian filtersIt is also believed that a gaussian distribution is satisfied, which can be expressed as:
where η is a proportionality coefficient, which may also be referred to as a distribution average, and can be obtained by calculation.
In order to simplify the calculation process, a Bayesian filter pair is utilized in the actual calculationAndwhen fusion is performed, the following calculation formula can be adopted:
wherein,Rtis a first variance value, QtAnd t is the current time, and is the second variance value.
Optionally, when passing through the Bayesian filter, becauseWill usually precedeReaches a Bayesian filter, so thatDelaying by one sampling period to ensureAndwhile achieving a bayesian filter.
The accurate current angular acceleration can be calculated according to the formula (14), and the influence of the measurement error generated during the measurement of the operation parameters on the calculation of the angular acceleration is reduced.
And S260, determining a moment compensation vector of the motion control object according to the current angular acceleration, the current moment parameter in the operation parameters and the diagonal matrix.
In particular, the moment compensation vectorThe calculation formula of (a) is as follows:
wherein, tau1The current torque parameter can be directly measured from the operation parameters.As the current angular acceleration, the angular acceleration is,is a diagonal matrix.
As can be seen from the formula (15),in practice, it can also be considered as a torque compensation quantity which is determined on the basis of the current torque parameter measured at the current time and the torque parameter which should theoretically be generated.
And S270, determining the moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector.
The calculation formula of the moment vector tau is as follows:
according to the above formula, the control torque vector C' is added to the torque compensation vectorThe torque output τ can be obtained. That is, C' is compensated for moment, so that the moment vector τ that should be actually output can be determined.
And S280, taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
In the above process, the process of calculating the control torque vector may be referred to as a first process, since it determines the torque to be output by the motor, and the motor is preferably a servo motor, and may be referred to as a servo control process, and the process of calculating the torque compensation vector may be referred to as a second process, since it calculates the torque compensation value for correcting the control torque vector, and may be referred to as an auxiliary motion process. That is, the decoupling control method in this embodiment can be implemented by only the above two processes.
Fig. 2e is an algorithm schematic diagram of the decoupling control method, and fig. 2f is a flowchart of the decoupling control method, and for convenience of understanding, the decoupling control method provided in this embodiment is exemplarily described with reference to fig. 2e and fig. 2 f:
wherein the motion control object is a mechanical arm. Specifically, initial parameters of the mechanical arm are obtained, and a motion planning formula is constructed by using a motion planning method, wherein the motion planning formula is specificallyAre represented by formula (5), formula (6) and formula (7). Then, the target position θ at time t is determined by equations (5), (6) and (7)1(t) target angular velocityAnd target angular accelerationIn the operation process of the mechanical arm, according to the sampling interval T, the inertia matrix, the system parameters and the operation parameters of the mechanical arm at the current moment T are acquired at intervals.
Further, a diagonal matrix is determined according to equation (2)And then, solving a control input vector u by using an equation (8) through two proportional-integral links. ComputingAnd the calculation result is used as the input of the low-pass filter, and the control moment vector is obtained by using the formula (10).
The actual angular acceleration is obtained by subjecting the position θ' (t) of the arm in the measured operational parameter to a differential calculation method (see equation (11)) and a low-pass filter (see equation (10))And will beDelayed by one sampling periodObtaining the current angular acceleration through a Bayesian filter (see equation (14))Then, the moment compensation vector is obtained by solving the equation (15)Then, the moment vector τ is obtained by solving equation (16). And taking the specific value in the tau as a torque output value of a motor of a corresponding joint in the mechanical arm so as to realize decoupling when each motor operates.
According to the technical scheme provided by the embodiment, the diagonal matrix is obtained by performing singular value decomposition on the obtained inertia matrix, the control input vector is determined according to the obtained system parameters and the operation parameters, and further the control moment vector and the moment compensation vector are determined, so that the actually output moment vector is obtained. Meanwhile, when the control input vector is determined, the accuracy of the control input vector is ensured by utilizing two proportional-integral links, and high-frequency tremor is effectively inhibited by utilizing a low-pass filter.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a decoupling control device according to a third embodiment of the present invention. The decoupling control device provided in this embodiment specifically includes: a parameter acquisition module 301, a diagonal matrix determination module 302, a control torque determination module 303, a torque compensation determination module 304, a torque vector determination module 305, and an output value determination module 306.
The parameter obtaining module 301 is configured to obtain an inertia matrix of a motion control object, system parameters, and operation parameters at a current time in an operation process; a diagonal matrix determining module 302, configured to determine a corresponding diagonal matrix according to the inertia matrix; a control moment determining module 303, configured to determine a control moment vector of the motion control object according to the diagonal matrix, the system parameter, and the operation parameter; a moment compensation determining module 304, configured to determine a moment compensation vector of the motion control object according to the operation parameter and the diagonal matrix; a moment vector determining module 305, configured to determine a moment vector of the motion-controlled object at the current moment according to the control moment vector and the moment compensation vector; and the output value determining module 306 is configured to use each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
According to the technical scheme provided by the embodiment, the control moment vector and the corresponding moment compensation vector are determined by obtaining the inertia matrix of the motion control object, the system parameters and the operation parameters at the current moment in the operation process, so that the final moment output value of each motion control sub-object in the motion control object is obtained, the motion control object is decoupled simply and effectively, and meanwhile, on the premise of ensuring the decoupling accuracy, a complex decoupling model is not required to be constructed, and a good decoupling effect can be achieved only through simple calculation.
On the basis of the foregoing embodiment, the diagonal matrix determination module 302 is specifically configured to: and performing singular value decomposition on the inertia matrix to obtain a diagonal matrix, wherein values on a diagonal in the diagonal matrix are characteristic values obtained by singular value decomposition.
On the basis of the above embodiment, the control torque determination module 303 includes: the control input determining unit is used for determining a control input vector of the motion control object according to the system parameter and the operation parameter; and the multiplication unit is used for performing multiplication operation on the diagonal matrix and the control input vector to obtain a control moment vector.
On the basis of the above embodiment, the control input determining unit specifically includes: the target parameter determining subunit is used for determining a target operation parameter of the motion control object at the current moment according to the operation moment in the operation parameters; a control input vector determining subunit, configured to determine a control input vector for moving the control object according to the target operating parameter, the operating parameter, and the system parameter, where the system parameter includes: proportional and integral parameters, the operating parameters including: the time of operation, the position of the moving control object and the angular velocity of the moving control object.
On the basis of the above embodiment, the method further includes: the initial parameter acquisition module is used for acquiring initial parameters of the initial operation time of the motion control object before acquiring an inertia matrix, system parameters and operation parameters of the motion control object at the current time in the operation process; and the motion planning module is used for performing motion planning on the motion control object according to the initial parameters so as to determine target operation parameters corresponding to the operation time according to the motion planning result.
On the basis of the above embodiment, the multiplication unit specifically includes: the multiplier subunit is used for performing multiplication operation on the diagonal matrix and the control input vector; and the filtering subunit is used for taking the result obtained by the multiplication operation as the input of the low-pass filter and taking the result obtained after filtering as the control moment vector.
On the basis of the foregoing embodiment, the torque compensation determining module 304 specifically includes: an angular acceleration determination unit for determining a current angular acceleration of the motion control object according to the operation parameter; and the compensation determining unit is used for determining a moment compensation vector of the motion control object according to the current angular acceleration, the current moment parameter in the operation parameters and the diagonal matrix.
The decoupling control device provided by the embodiment can be used for executing the decoupling control method provided by any embodiment, and has corresponding functions and beneficial effects.
Example four
Fig. 4 is a schematic structural diagram of a robot according to a fourth embodiment of the present invention, as shown in fig. 4, the robot includes a processor 40, a memory 41, an input device 42, an output device 43, and a motion control device 44; the number of the processors 40 in the robot can be one or more, and one processor 40 is taken as an example in fig. 4; the processor 40, the memory 41, the input device 42, the output device 43 and the motion control device 44 in the robot may be connected by a bus or other means, and fig. 4 illustrates the connection by a bus as an example. Wherein the processor 40 implements the decoupling control method as in the embodiment of the present invention when executing the program. The processor 40 and memory 41 may be collectively referred to as a host computer. The motion control device 44 is used for moving according to the moment vector determined by the decoupling control method, and comprises a motion control object and a driver for driving the motion control object to move, wherein the driver is electrically connected with the motion control object, the motion control object comprises at least two motion control sub-objects, and each motion control sub-object is provided with a movable motor.
The memory 41 serves as a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the decoupling control method in the embodiment of the present invention (for example, a parameter acquisition module 301, a diagonal matrix determination module 302, a control input determination module 303, a torque compensation determination module 304, a torque vector determination module 305, and an output value determination module 306 in the decoupling control device). The processor 40 executes various functional applications and data processing of the robot by running software programs, instructions and modules stored in the memory 41, that is, implements the decoupling control method described above.
The memory 41 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the robot, and the like. Further, the memory 41 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 41 may further include memory remotely located from the processor 40, which may be connected to the robot through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 42 may be used to receive input numeric or character information and to generate key signal inputs relating to user settings and function control of the robot. The output device 43 may include a display device such as a display screen.
The robot provided by the embodiment can be used for executing the decoupling control method provided by any embodiment, and has corresponding functions and beneficial effects.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are executed by a computer processor to perform a decoupling control method, where the decoupling control method includes:
acquiring an inertia matrix of a motion control object, system parameters and operation parameters at the current moment in the operation process;
determining a corresponding diagonal matrix according to the inertia matrix;
determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters;
determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix;
determining a moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector;
and taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
Of course, the storage medium provided by the embodiment of the present invention includes computer-executable instructions, and the computer-executable instructions are not limited to the operations of the decoupling control method described above, and may also perform related operations in the decoupling control method provided by any embodiment of the present invention, and have corresponding functions and advantages.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, and the computer software product may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions to enable a computer device (which may be a robot, a personal computer, a server, or a network device) to execute the decoupling control method according to the embodiments of the present invention.
It should be noted that, in the above embodiment of the decoupling control device, the included units and modules are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A decoupling control method, comprising:
acquiring an inertia matrix, system parameters and operation parameters of a motion control object at the current moment in the operation process, wherein the motion control object comprises at least two movable motion control sub-objects capable of generating a coupling phenomenon, and each motion control sub-object is configured with a corresponding driving motor;
determining a corresponding diagonal matrix according to the inertia matrix;
determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters;
determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix;
determining the moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector;
and taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
2. The decoupling control method of claim 1 wherein said determining a corresponding diagonal matrix from said inertia matrix comprises:
and performing singular value decomposition on the inertia matrix to obtain a diagonal matrix, wherein values on diagonal lines in the diagonal matrix are eigenvalues obtained by singular value decomposition.
3. The decoupling control method of claim 1 wherein said determining a control moment vector for the moving control object from the diagonal matrix, the system parameters, and the operating parameters comprises:
determining a control input vector of the motion control object according to the system parameter and the operation parameter;
and performing multiplication operation on the diagonal matrix and the control input vector to obtain a control moment vector.
4. The decoupling control method of claim 3 wherein said determining a control input vector for the moving control object as a function of the system parameters and the operating parameters comprises:
determining a target operation parameter of the motion control object at the current moment according to the operation moment in the operation parameters;
determining a control input vector for the motion controlled object based on the target operating parameter, the operating parameter, and the system parameter, wherein the system parameter comprises: proportional parameters and integral parameters, the operating parameters including: a time of operation, a position of the motion control object, and an angular velocity of the motion control object.
5. The decoupling control method of claim 4, wherein obtaining the inertia matrix of the moving control object, the system parameters, and the operating parameters at the current time during operation further comprises:
acquiring initial parameters of an initial running time of a motion control object;
and performing motion planning on the motion control object according to the initial parameters so as to determine target operation parameters corresponding to the operation time according to a motion planning result.
6. The decoupling control method of claim 3 wherein said multiplying said diagonal matrix by said control input vector to obtain a control torque vector comprises:
performing multiplication operation on the diagonal matrix and the control input vector;
and taking the result obtained by the multiplication operation as the input of a low-pass filter, and taking the result obtained after filtering as a control moment vector.
7. The decoupling control method of claim 1 wherein said determining a moment compensation vector for the moving control object based on the operating parameters and the diagonal matrix comprises:
determining the current angular acceleration of the motion control object according to the operation parameters;
and determining a moment compensation vector of the motion control object according to the current angular acceleration, the current moment parameter in the operation parameters and the diagonal matrix.
8. A decoupling control device, comprising:
the device comprises a parameter acquisition module, a parameter acquisition module and a parameter acquisition module, wherein the parameter acquisition module is used for acquiring an inertia matrix, system parameters and operation parameters of a motion control object at the current moment in the operation process, the motion control object comprises at least two movable motion control sub-objects capable of generating a coupling phenomenon, and each motion control sub-object is configured with a corresponding driving motor;
the diagonal matrix determining module is used for determining a corresponding diagonal matrix according to the inertia matrix;
the control moment determining module is used for determining a control moment vector of the motion control object according to the diagonal matrix, the system parameters and the operation parameters;
the moment compensation determining module is used for determining a moment compensation vector of the motion control object according to the operation parameters and the diagonal matrix;
the moment vector determining module is used for determining the moment vector of the motion control object at the current moment according to the control moment vector and the moment compensation vector;
and the output value determining module is used for taking each numerical value in the moment vector as a moment output value of a corresponding motion control sub-object in the motion control object.
9. A robot, comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a decoupling control method as in any one of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the decoupling control method of any one of claims 1-7 when executed by a computer processor.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710353270.4A CN106950842B (en) | 2017-05-18 | 2017-05-18 | Decoupling control method and device, robot and storage medium |
| PCT/CN2017/103261 WO2018209860A1 (en) | 2017-05-18 | 2017-09-25 | Decoupling control method and device, robot and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710353270.4A CN106950842B (en) | 2017-05-18 | 2017-05-18 | Decoupling control method and device, robot and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106950842A CN106950842A (en) | 2017-07-14 |
| CN106950842B true CN106950842B (en) | 2019-10-25 |
Family
ID=59479772
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710353270.4A Active CN106950842B (en) | 2017-05-18 | 2017-05-18 | Decoupling control method and device, robot and storage medium |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN106950842B (en) |
| WO (1) | WO2018209860A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106950842B (en) * | 2017-05-18 | 2019-10-25 | 广州视源电子科技股份有限公司 | Decoupling control method and device, robot and storage medium |
| CN108189036B (en) * | 2018-01-17 | 2021-08-13 | 广州视源电子科技股份有限公司 | Torque control method and device, robot and storage medium |
| CN110347040B (en) * | 2019-07-12 | 2023-02-10 | 广东工业大学 | Control method, device, equipment and storage medium of cooperative motion mechanism |
| CN115922698B (en) * | 2022-11-11 | 2024-10-08 | 江苏开放大学（江苏城市职业学院） | Six-joint robot active decoupling method based on DH parameter method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101369132A (en) * | 2008-07-11 | 2009-02-18 | 天津大学 | Mechanical decoupling control method of permanent magnet spherical motor based on neural network identifier |
| EP2345511A2 (en) * | 2010-01-13 | 2011-07-20 | KUKA Laboratories GmbH | Control for a manipulator |
| CN104070522A (en) * | 2013-03-27 | 2014-10-01 | 深圳市生命之泉科技发展有限公司 | Method and device capable of automatically identifying and preventing collision for industrial robot |
| CN105843078A (en) * | 2016-05-24 | 2016-08-10 | 哈尔滨工程大学 | Sliding mode control method and apparatus |
| CN106313031A (en) * | 2016-10-11 | 2017-01-11 | 北京航空航天大学 | Space mechanical arm driven by control torque spinning tops |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102006053158A1 (en) * | 2006-11-10 | 2008-05-15 | Kuka Roboter Gmbh | Robot controller, robot and method for controlling a robot |
| CN106950842B (en) * | 2017-05-18 | 2019-10-25 | 广州视源电子科技股份有限公司 | Decoupling control method and device, robot and storage medium |
-
2017
- 2017-05-18 CN CN201710353270.4A patent/CN106950842B/en active Active
- 2017-09-25 WO PCT/CN2017/103261 patent/WO2018209860A1/en not_active Ceased
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101369132A (en) * | 2008-07-11 | 2009-02-18 | 天津大学 | Mechanical decoupling control method of permanent magnet spherical motor based on neural network identifier |
| EP2345511A2 (en) * | 2010-01-13 | 2011-07-20 | KUKA Laboratories GmbH | Control for a manipulator |
| CN104070522A (en) * | 2013-03-27 | 2014-10-01 | 深圳市生命之泉科技发展有限公司 | Method and device capable of automatically identifying and preventing collision for industrial robot |
| CN105843078A (en) * | 2016-05-24 | 2016-08-10 | 哈尔滨工程大学 | Sliding mode control method and apparatus |
| CN106313031A (en) * | 2016-10-11 | 2017-01-11 | 北京航空航天大学 | Space mechanical arm driven by control torque spinning tops |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106950842A (en) | 2017-07-14 |
| WO2018209860A1 (en) | 2018-11-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108189036B (en) | Torque control method and device, robot and storage medium | |
| CN103412491B (en) | A kind of Spacecraft feature axis attitude maneuver index time-varying sliding-mode control | |
| CN106020124B (en) | Servo motor control device and collision detection method | |
| Cheah et al. | Adaptive vision and force tracking control for robots with constraint uncertainty | |
| CN106950842B (en) | Decoupling control method and device, robot and storage medium | |
| CN114450131B (en) | Derivative-free model learning system and design of robot system | |
| US12240119B2 (en) | Motion control method, robot, and computer-readable storage medium | |
| CN102189550A (en) | Robot having learning control function | |
| Zheng et al. | Tracking control of manipulator based on high-order disturbance observer | |
| CN111258216A (en) | Sliding mode repetitive controller suitable for four-rotor aircraft | |
| Solanes et al. | Robust hybrid position-force control for robotic surface polishing | |
| CN115890735A (en) | Robotic arm system, robotic arm and control method thereof, controller and storage medium | |
| Chen et al. | Adaptive robust control based on Moore-Penrose generalized inverse for underactuated mechanical systems | |
| Imran et al. | Adaptive control of quadrotor unmanned aerial vehicle with time-varying uncertainties | |
| CN108931922A (en) | A kind of adaptive Non-smooth surface Trajectory Tracking Control method of industrial robot | |
| CN111152213B (en) | Mechanical arm vibration compensation method and device based on hybrid control | |
| CN120029339A (en) | A spacecraft preset time preset accuracy attitude tracking control method and system based on performance function | |
| CN111015661A (en) | Active vibration control method and system for flexible load of robot | |
| Khalifa et al. | MPC and DOb-based robust optimal control of a new quadrotor manipulation system | |
| Vandernotte et al. | Dynamic sensor-based control | |
| Zhang et al. | An adaptive type-2 fuzzy sliding mode tracking controller for a robotic manipulator. | |
| Liaquat et al. | Sampled data output regulation of n-link robotic manipulator using a realizable reconstruction filter | |
| Dumlu et al. | Real-time implementation of continuous model based sliding mode control technique for trajectory tracking control of mobile robot | |
| CN109176529A (en) | A kind of NEW ADAPTIVE fuzzy control method of the robot for space coordinated movement of various economic factors | |
| Ahmed et al. | Adaptive backstepping trajectory tracking control without velocity measurements for quadrotor UAVs under multiple unknown disturbances |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |