Control method and system for pneumatic artificial muscle parallel robot based on hysteresis compensation

Abstract

The invention belongs to the field of robot control, and provides a pneumatic artificial muscle parallel robot control method and system based on hysteresis compensation. The control method comprises the following steps: constructing a dynamic model of the pneumatic artificial muscle parallel robot based on state information of the pneumatic artificial muscle parallel robot; based on the dynamic model of the pneumatic artificial muscle parallel robot, constructing a fractional order Bouc-Wen hysteresis model and a corresponding inverse model thereof; and hysteresis feedforward compensation is performed based on the fractional order Bouc-Wen hysteresis model and the corresponding inverse model thereof, and an output feedback synchronous controller is constructed by combining a pre-designed tracking error, a pre-designed synchronization error, a pre-designed coupling error and a pre-designed speed estimation system so as to act on the pneumatic artificial muscle parallel robot, so that the pneumatic artificial muscle parallel robot can be controlled. Therefore, the master arm can quickly and accurately track the smooth reference trajectory.

Description

Technical Field

[0001] The invention belongs to the field of robot control, and in particular relates to a pneumatic artificial muscle parallel robot control method and system based on hysteresis compensation. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] As a bionic actuator, pneumatic artificial muscle can simulate the contraction and relaxation behavior of biological muscle, and has unique advantages such as controllable stiffness, light weight and simple structure. Combined with the high load-bearing capacity, high rigidity and high stability of parallel robots, pneumatic artificial muscle parallel robots can complete rigid-flexible coupling operation tasks, overcome the limitations of poor adaptability and low compliance of traditional parallel robots, and have great application potential in medical rehabilitation, surgical assistance and other fields with high requirements for compliance and safety.

[0004] In practical applications, overcoming serious nonlinear problems is a prerequisite for fully realizing the application potential of pneumatic artificial muscle parallel robots. Specifically, during the contraction / relaxation process of pneumatic artificial muscles, friction and irreversible deformation are prone to occur between the outer woven mesh and the inner rubber tube, causing the pneumatic artificial muscles to exhibit hysteresis nonlinear characteristics that do not exist in traditional drivers, which has an adverse effect on control performance. At the same time, the hysteresis curve of the pneumatic artificial muscle is asymmetric and related to the input frequency, which further increases the difficulty of accurately describing the input-output relationship of the pneumatic artificial muscle. Among the existing pneumatic artificial muscle hysteresis models, the operator-based hysteresis model usually has a relatively complex structure, the model accuracy is positively correlated with the model parameters, and the generated fitting curve is often not smooth enough; the hysteresis model based on differential equations has a relatively simple structure, but the ability to characterize rate-dependent hysteresis is weak. On the other hand, unlike serial robots, pneumatic artificial muscle parallel robots are closed-loop structures composed of multiple robotic arms. Enhancing the synchronization between robotic arms helps to improve the overall motion performance. However, existing synchronization control methods require the actual system to be equipped with sensors that feedback speed information, and rarely consider the convergence speed, which is not conducive to reducing the sensor installation cost and improving operation efficiency. Summary of the invention

[0005] In order to solve at least one technical problem existing in the above-mentioned background technology, the present invention provides a pneumatic artificial muscle parallel robot control method and system based on hysteresis compensation, which designs an accurate pneumatic artificial muscle hysteresis model, performs corresponding hysteresis compensation, and constructs an output feedback synchronous controller to improve the control performance of the pneumatic artificial muscle parallel robot, so as to realize the fast and accurate tracking of the active arm to the smooth reference trajectory.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A first aspect of the present invention provides a pneumatic artificial muscle parallel robot control method based on hysteresis compensation.

[0008] A pneumatic artificial muscle parallel robot control method based on hysteresis compensation, comprising:

[0009] Based on the state information of the pneumatic artificial muscle parallel robot, a dynamic model of the pneumatic artificial muscle parallel robot is constructed;

[0010] Based on the dynamic model of the pneumatic artificial muscle parallel robot, a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model are constructed;

[0011] Based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model, hysteresis feedforward compensation is performed, and an output feedback synchronization controller is constructed in combination with a pre-designed tracking error, synchronization error, coupling error and speed estimation system to act on the pneumatic artificial muscle parallel robot.

[0012] As an implementation method, the dynamic model expression of the pneumatic artificial muscle parallel robot is:

[0013]

[0014] in, is the angle vector of the active arm, which is determined by the initial angle and rotation angle constitute; is the system input torque vector, which is related to the input air pressure of the pneumatic artificial muscle related; M(θ) is the inertia matrix, is the Coriolis force matrix, and G(θ) is the vector related to gravity.

[0015] As an implementation method, the fractional-order Bouc-Wen hysteresis model is used to characterize the input air pressure p i With the rotation angle θ Δi The relationship between:

[0016]

[0017] In the formula, μ i is the intermediate state variable of the hysteresis model, and the polynomial term It is used to characterize the asymmetric characteristics of the hysteresis of pneumatic artificial muscles. The positive integer N is the number of terms in the polynomial; the auxiliary term ξ i =-κ i4 p i |μ i |-κ i5|p i |μ i Used to store historical information; 0<λ i1 ,λ i2 <1 are fractional derivatives and The order of γ i1 ,γ i2 ,…,γ iN and κ i1 ,κ i2 ,…,κ i5 are the model parameters to be identified.

[0018] As an implementation method, the expression of the inverse model corresponding to the fractional-order Bouc-Wen hysteresis model is:

[0019]

[0020] In the formula, θ Δri =θ ri -θ 0i is the reference rotation angle.

[0021] As an implementation method, the expression of the output feedback synchronization controller is:

[0022]

[0023] Where p is the input air pressure of the pneumatic artificial muscle, θ r is the smooth reference trajectory of the active arm, z is the tracking error of the active arm, I is the unit matrix of appropriate dimension, K0 is the nominal value matrix, B and β are the positive definite matrix and positive constant in the coupling error, K1, K2, K3, K5, K6 are the positive definite diagonal matrices to be designed, η and χ are the variables in the speed estimation system, is the estimate of the weight matrix W in the fuzzy logic system, Estimates is the input vector of the fuzzy logic system, is the basis function vector in the fuzzy logic system; max (·) indicates the maximum eigenvalue.

[0024] As an implementation, the weight estimation matrix It is updated online by the following adaptive law:

[0025]

[0026] In the formula, Γ i is an element in the positive definite diagonal matrix Γ=diag(Γ1,Γ2), ρ i and is a positive constant.

[0027] A second aspect of the present invention provides a pneumatic artificial muscle parallel robot control system based on hysteresis compensation.

[0028] A pneumatic artificial muscle parallel robot control system based on hysteresis compensation, comprising:

[0029] A dynamic model building module, which is used to build a dynamic model of the pneumatic artificial muscle parallel robot based on the state information of the pneumatic artificial muscle parallel robot;

[0030] A hysteresis inverse model construction module, which is used to construct a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model based on the dynamics model of the pneumatic artificial muscle parallel robot;

[0031] The synchronous controller construction module performs hysteresis feedforward compensation based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model, and constructs an output feedback synchronous controller in combination with the pre-designed tracking error, synchronization error, coupling error and speed estimation system to act on the pneumatic artificial muscle parallel robot.

[0032] A third aspect of the present invention provides a computer-readable storage medium.

[0033] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described above.

[0034] A fourth aspect of the present invention provides a computer device.

[0035] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described above.

[0036] A fifth aspect of the present invention provides a computer device.

[0037] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described above are implemented.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] (1) The present invention provides a pneumatic artificial muscle parallel robot control method based on hysteresis compensation, which can ensure that the active arm quickly and accurately tracks the smooth reference trajectory. Specifically, by using fractional-order calculus to introduce the rate information of the input air pressure, an improved fractional-order Bouc-Wen hysteresis model is established for the pneumatic artificial muscle, and auxiliary terms are added to further improve the model accuracy; on this basis, the inverse model is designed with the help of the inverse multiplication structure, and the feedforward compensation of the pneumatic artificial muscle hysteresis is performed. In addition, the synchronization error of the robot arm is defined based on the cross-information of the tracking error, and the auxiliary variables in the speed estimation system are fused into the filter to realize output feedback synchronization control without the need for speed information, so that the proposed method reduces the hardware configuration requirements and is applicable to a wider range of scenarios; at the same time, the introduction of the sign function into the speed estimation system speeds up the system response and effectively improves the operating efficiency.

[0040] (2) The present invention takes into account the hysteresis characteristics of pneumatic artificial muscles and the asymmetric and rate-dependent features of the hysteresis, and proposes an improved fractional-order Bouc-Wen model and an inverse model for feedforward compensation, which improves the accuracy of the model without increasing the complexity of the model structure.

[0041] (3) The present invention fully considers the problem of missing speed sensors that may be easily caused by factors such as physical space or cost, and proposes a speed estimation system based on available angle information, which is used to generate unmeasurable speed estimation signals online, reduce the configuration requirements for sensor hardware, and broaden the scope of application of the proposed method.

[0042] (4) The present invention takes into account the closed-loop structure composed of multiple robotic arms and proposes a finite-time synchronization control method based on output feedback, which can improve motion synchronization by enhancing information exchange between robotic arms, thereby improving overall control accuracy and operating efficiency.

[0043] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0045] Figure 1 A block diagram of a pneumatic artificial muscle parallel robot control method based on hysteresis compensation according to an embodiment of the present invention;

[0046] Figure 2 Schematic diagram of a pneumatic artificial muscle parallel robot considered in an embodiment of the present invention;

[0047] Figure 3 is the hysteresis fitting result of the pneumatic artificial muscle in the embodiment of the present invention;

[0048] Figure 4 is the hysteresis compensation result of the pneumatic artificial muscle in the embodiment of the present invention;

[0049] Figure 5 is a simulation result of a speed estimation system in an embodiment of the present invention;

[0050] Figure 6 The simulation results of the active arm tracking the reference trajectory, tracking error and pneumatic artificial muscle input air pressure in the embodiment of the present invention. DETAILED DESCRIPTION

[0051] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0052] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0053] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0054] Embodiment 1

[0055] Figure 2 A 2-DOF pneumatic artificial muscle parallel robot with bilaterally symmetrical structure is presented, in which the pneumatic artificial muscle replaces the motor in the traditional parallel robot. Figure 1 As shown, this embodiment provides a pneumatic artificial muscle parallel robot control method based on hysteresis compensation, which includes:

[0056] Step 1: Based on the state information of the pneumatic artificial muscle parallel robot, a dynamic model of the pneumatic artificial muscle parallel robot is constructed;

[0057] Step 2: Based on the dynamic model of the pneumatic artificial muscle parallel robot, construct a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model;

[0058] Step 3: Based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model, hysteresis feedforward compensation is performed, and combined with the pre-designed tracking error, synchronization error, coupling error and speed estimation system, an output feedback synchronization controller is constructed to act on the pneumatic artificial muscle parallel robot.

[0059] In step 1, according to the Lagrangian modeling method, the following dynamic equations of the pneumatic artificial muscle parallel robot can be established:

[0060]

[0061] In the formula, is the angle vector of the active arm, which is determined by the initial angle and rotation angle constitute; is the system input torque vector; M(θ) is the inertia matrix, is the Coriolis force matrix, G(θ) is the vector related to gravity. Then, according to the experimental model of pneumatic artificial muscle, the pneumatic artificial muscle input air pressure The relationship between and the system input torque τ can be expressed as:

[0062]

[0063] In the formula, the force arm ι i It can be expressed as i =ι 0i +ι Δi , ι 0i is the initial value of the lever arm, ι Δi is the change in the moment arm during the motion; and Respectively represent the contraction force and hysteresis force of the pneumatic artificial muscle; the specific forms of other variables are

[0064]

[0065] ψ ai =[ι i ψ ai0 ,ι i ψ ai1 ,ι i ψ ai2 ],ψ ci =ι 0i ψ bi1 ,

[0066] ψ bi =[ι i ψ bi0 ,ι Δi ψ bi1 ,ι i ψ bi2 ,ιi ψ bi3 ],

[0067] In the formula, ψ aij (j=0,1,2) and ψ aik (k=0,1,…,4) are unknown parameters in the pneumatic artificial muscle contraction force model.

[0068] In step 2, for the pneumatic artificial muscle parallel robot under consideration, the inherent hysteresis of the pneumatic artificial muscle and the asynchrony between the active arms will have an adverse effect on the overall performance, and the lack of speed sensors in practical applications makes the existing full-state feedback synchronization control method unusable. Therefore, the control goal is to establish a more accurate pneumatic artificial muscle hysteresis model, perform corresponding hysteresis compensation, and then construct a synchronization controller p without speed feedback to achieve the active arm to smooth reference trajectory. Tracking movement.

[0069] Compared with the hysteresis of actuators such as piezoelectric ceramics, although the hysteresis in pneumatic artificial muscles is also asymmetric and rate-dependent, its hysteresis curve is more asymmetric and complex, and it is difficult to obtain a good fitting result by directly applying the Bouc-Wen hysteresis model of actuators such as piezoelectric ceramics to pneumatic artificial muscles. To this end, the following improved fractional-order Bouc-Wen model is designed to characterize the input air pressure p i With the rotation angle θ Δi The relationship between:

[0070]

[0071] In the formula, μ i is the intermediate state variable of the hysteresis model, and the polynomial term It is used to characterize the asymmetric characteristics of the hysteresis of pneumatic artificial muscles. The positive integer N is the number of terms in the polynomial; the carefully designed auxiliary term ξ i =-κ i4 p i |μ i |-κ i5 |p i |μ i It can store historical information, enhance the memory of the pneumatic artificial muscle hysteresis model, and further improve the accuracy of the model; different from the integer-order calculus in the traditional Bouc-Wen hysteresis model, 0<λ i1 ,λ i2 <1 are fractional derivatives and ...order, this fractional calculus can take the input pressure pi The rate information of γ is indirectly introduced into the model, which effectively characterizes the rate-related characteristics of the pneumatic artificial muscle and avoids complicating the model structure.i1 ,γ i2 ,…,γ iN and κ i1 ,κ i2 ,…,κ i5 is the model parameter to be identified. Then, by using the inverse multiplication structure, the corresponding hysteresis inverse model can be obtained:

[0072]

[0073] In the formula, θ Δri =θ ri -θ 0i is the reference rotation angle. Therefore, after feedforward compensation using the hysteresis inverse model (4), the input torque τ can be expressed as

[0074]

[0075] In the formula, Ψ a =diag(ψ a1 ,ψ a2 ), b =diag(ψ b1 ,ψ b2 ), c =diag(ψ c1 ,ψ c2 ), Θ a =diag(θ a1 ,θ a2 ), L = diag(ι1, ι2), is the hysteresis compensation error. On this basis, the dynamic model of the pneumatic artificial muscle parallel robot can be re-expressed as follows:

[0076]

[0077] In the formula, K0 and K Δ M -1 (θ)Ψ a Θ a The nominal value and unknown part, namely M -1 (θ)Ψ a Θ a =K0+K Δ ; Nonlinear dynamics to be handled It can be expressed as

[0078] In step 3, the following tracking error and synchronization error are defined to measure the tracking performance and synchronization performance of the active arm respectively:

[0079]

[0080] Then, introduce the following code containing z and z s The coupling error z c :

[0081] z c =z+αz s =Bz, (9)

[0082] In the formula, the coupling gain α satisfies 0<α<1, and the matrix B=I+αA is positive definite. From (9), we can see that when z c When converged, z and z s The convergence of can also be guaranteed; therefore, using the coupling error z c Subsequent controller design helps to reduce the computational burden. To achieve output feedback synchronous control without speed information, the following filter including auxiliary variables is designed:

[0083]

[0084] Where β is a positive constant and the auxiliary variable χ is generated online by the following speed estimation system:

[0085]

[0086] Where η(0) = θ(0), χ(0) = 0, the diagonal matrices K1, K2, K3, K4, K5, K6, K8 are positive definite; sgn(·) represents the sign function, λ max (·) represents the maximum eigenvalue. It can be seen that the auxiliary variable χ can be obtained by the integral operation of formula (12), avoiding the use of unmeasurable speed Therefore, η and are θ and The available estimation signal. Compared with the existing speed estimation method, the speed estimation systems (11) and (12) used contain the sign function terms sgn(θ-η) and sgn(χ), which can speed up the response time of the speed estimation system and improve the operation efficiency; at the same time, these sign function terms exist in the subsequent controller in the form of integrals and will not induce system jitter. Next, the open-loop dynamics of the filter r can be calculated as:

[0087]

[0088] The fuzzy logic system Used to estimate uncertain system dynamics Right now

[0089]

[0090] Where W is the weight matrix and φ(x) satisfies The basis function vector of is a bounded approximation error vector; hence, the basis function vector φ(x) cannot be used in the controller unless the velocity estimate signal Replacement of unmeasurable speed Furthermore, (14) can be rewritten as follows:

[0091]

[0092] In the formula, is the input vector, There is an upper bound Right now Based on the results in (13) and (15), the following synchronization controller p is constructed:

[0093]

[0094] In the formula, the weight estimation matrix It is updated online by the following adaptive law:

[0095]

[0096] In the formula, Γ i is an element in the positive definite diagonal matrix Γ=diag(Γ1,Γ2), ρ i and is a positive constant. From (17), we can see that as long as the initial conditions satisfy inequality Always holds true, and we can get the estimated error is bounded, that is w 0i is a positive constant. In addition, the relevant control parameters need to meet the following conditions:

[0097]

[0098] In the formula, λ min (·) represents the minimum eigenvalue

[0099] In order to analyze the performance of the closed-loop system, the estimation results in (15) and the synchronous controller in (16) are substituted into the open-loop dynamic equation in (13), and the following results can be obtained:

[0100]

[0101] On this basis, the following Lyapunov candidate function is selected

[0102]

[0103] In the formula, tr{·} represents the trace of the matrix. Then, it is not difficult to calculate its time derivative as:

[0104]

[0105] The following inequality is used in the above derivation:

[0106]

[0107] Where K7 is a positive definite diagonal matrix. For the term in equation (21) Substituting the adaptive law and using Young's inequality, we can get

[0108]

[0109] Finally, substituting (22) into (21) yields

[0110]

[0111] In the formula, the parameters a, b and c can be expressed as

[0112]

[0113] Therefore, from formula (23), we can know that r,z,χ,θ-η, And the variables r,z,χ,θ-η, can converge to the vicinity of the origin in a finite time; furthermore, combining the error definition in equations (7)-(10) and the synchronization controller in equation (16), we can know that z s , z s and The actual finite-time convergence of can be achieved by adjusting the control parameters.

[0114] In order to verify the accuracy of the proposed improved fractional-order Bouc-Wen model in characterizing the asymmetric and rate-dependent hysteresis in pneumatic artificial muscles, an open-loop control was performed on a 2-DOF pneumatic artificial muscle parallel robot experimental platform to collect the rotation angle data of the active arm. The variable frequency input air pressure signal used was:

[0115] p i =[2.8sin(0.2e 0.015t πt-π / 2)+2.8]×e -0.015t [bar],i=1,2.

[0116] By collecting the input air pressure p i -Rotation angle θ ΔiThe parameter values ​​of the proposed improved fractional-order Bouc-Wen model can be obtained by performing parameter identification based on the data. Since the pneumatic artificial muscle parallel robot under consideration has a left-right symmetrical structure, only the identification results of the left arm are given here:

[0117] λ 11 =0.4,γ 11 =0.1154,γ 13 =0.0020,κ 12 =0.0752,κ 14 =2.4330,

[0118] λ 12 =0.3,γ 12 =0.0048,κ 11 =-0.0838,κ 13 =-0.0546,κ 15 =2.4632.

[0119] Figure 3 The hysteresis fitting result under this set of model parameters. The dotted line in the figure is the measurement curve, and the solid line is the fitting curve of the proposed improved fractional-order Bouc-Wen model. From this figure, we can see that the proposed model can fit the input air pressure p1-rotation angle θ more accurately. Δ1 The hysteresis relationship between them is more accurate. Figure 4 This is the result after feedforward compensation using the corresponding inverse model, from which we can see the rotation angle θ Δ1 With reference rotation angle θ Δr1 It is almost in direct proportion, which indicates that the inverse model can effectively compensate for the hysteresis in pneumatic artificial muscles.

[0120] In addition, in order to verify the effectiveness of the proposed output feedback synchronization control method, a numerical simulation was carried out using a 2-DOF pneumatic artificial muscle parallel robot system. The control goal is to quickly and accurately generate a reliable speed estimation signal online when the speed sensor is missing or unavailable, and to ensure that the active arm can quickly and accurately move along the following reference trajectory:

[0121]

[0122] The design parameters of the output feedback synchronous control method proposed in the present invention are α=0.1, β=0.1, Γ1=Γ2=100, ρ1=ρ2=0.01, K0=diag(1,1), K1=diag(150,150), K2=diag(10,10), K3=diag(30 ,30), K4=diag(10,10), K5=diag(0.01,0.01), K6=diag(0.01,0.01), K8=diag(0.01,0.01).

[0123] Figure 5 and Figure 6 This is the simulation result of the output feedback synchronization control method proposed in the present invention. Figure 5 In the figure, the dotted line is the real angle / velocity trajectory, and the solid line is the estimated signal generated online by the velocity estimation system; it can be seen that η1 and η2 can accurately estimate the real angles θ1 and θ2, respectively. and It can also accurately estimate the true speed and This shows that the designed speed estimation system is effective. Figure 6 In the figure, the dotted line is the reference trajectory, and the solid line is the trajectory under the proposed method; from the sub-graphs in the first four rows, it can be seen that even if the motion frequencies of the two active arms are different, the proposed method can still enable the two active arms to quickly track their respective reference trajectories, and the tracking errors z1 and z2 are both small; the sub-graphs in the 5th and 6th rows are the input air pressures of the two pneumatic artificial muscles, respectively. Therefore, the output feedback synchronous control method proposed in the present invention can achieve good speed estimation and tracking motion effects.

[0124] Embodiment 2

[0125] The embodiment of the present invention provides a pneumatic artificial muscle parallel robot control system based on hysteresis compensation, which includes:

[0126] A dynamic model building module, which is used to build a dynamic model of the pneumatic artificial muscle parallel robot based on the state information of the pneumatic artificial muscle parallel robot;

[0127] A hysteresis inverse model construction module, which is used to construct a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model based on the dynamics model of the pneumatic artificial muscle parallel robot;

[0128] A synchronous controller construction module is used to perform hysteresis feedforward compensation based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model, and to construct an output feedback synchronous controller in combination with a pre-designed tracking error, synchronization error, coupling error and speed estimation system to act on the pneumatic artificial muscle parallel robot.

[0129] It should be noted here that each module in the embodiment of the present invention corresponds to each step in the first embodiment, and the specific process will not be described in detail.

[0130] Embodiment 3

[0131] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described above are implemented.

[0132] Embodiment 4

[0133] This embodiment provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described above.

[0134] Embodiment 5

[0135] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described above are implemented.

[0136] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0137] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0138] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A pneumatic artificial muscle parallel robot control method based on hysteresis compensation, characterized in that: include: Based on the state information of the pneumatic artificial muscle parallel robot, a dynamic model of the pneumatic artificial muscle parallel robot is constructed; Based on the dynamic model of the pneumatic artificial muscle parallel robot, a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model are constructed; Based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model, hysteresis feedforward compensation is performed, and an output feedback synchronization controller is constructed in combination with a pre-designed tracking error, synchronization error, coupling error and speed estimation system to act on the pneumatic artificial muscle parallel robot.

2. The pneumatic artificial muscle parallel robot control method based on hysteresis compensation according to claim 1, characterized in that: The dynamic model expression of the pneumatic artificial muscle parallel robot is: Where θ=[θ1,θ2] T is the angle vector of the active arm, which is given by the initial angle θ0 = [θ 01 ,θ 02 ] T and the rotation angle θ Δ =[θ Δ1 ,θ Δ2 ] T Composition; τ = [τ1, τ2] T is the system input torque vector, and the input air pressure of the pneumatic artificial muscle p=[p1,p2] T related; M(θ) is the inertia matrix, is the Coriolis force matrix, and G(θ) is the vector related to gravity.

3. The pneumatic artificial muscle parallel robot control method based on hysteresis compensation according to claim 1, characterized in that: The fractional-order Bouc-Wen hysteresis model is used to characterize the input pressure p i With the rotation angle θ Δi The relationship between: In the formula, μ i is the intermediate state variable of the hysteresis model, and the polynomial term It is used to characterize the asymmetric characteristics of the hysteresis of pneumatic artificial muscles. The positive integer N is the number of terms in the polynomial; the auxiliary term ξ i =-κ i4 p i |μ i |-κ i5 |p i |μ i Used to store historical information; 0<λ i1 ,λ i2 <1 are fractional derivatives and The order of γ i1 ,γ i2 ,…,γ iN and κ i1 ,κ i2 ,…,κ i5 are the model parameters to be identified.

4. The pneumatic artificial muscle parallel robot control method based on hysteresis compensation as claimed in claim 3, characterized in that: The expression of the inverse model corresponding to the fractional-order Bouc-Wen hysteresis model is: In the formula, θ Δri =θ ri -θ 0i is the reference rotation angle.

5. The pneumatic artificial muscle parallel robot control method based on hysteresis compensation according to claim 1, characterized in that: The expression of the output feedback synchronous controller is: Where p is the input air pressure of the pneumatic artificial muscle, θ r is the smooth reference trajectory of the active arm, z is the tracking error of the active arm, I is the unit matrix of appropriate dimension, K0 is the nominal value matrix, B and β are the positive definite matrix and positive constant in the coupling error, K1, K2, K3, K5, K6 are the positive definite diagonal matrices to be designed, η and χ are the variables in the velocity estimation system, is the estimate of the weight matrix W in the fuzzy logic system, Estimates is the input vector of the fuzzy logic system, is the basis function vector in the fuzzy logic system; max (·) indicates the maximum eigenvalue.

6. The pneumatic artificial muscle parallel robot control method based on hysteresis compensation as claimed in claim 5, characterized in that: Weight estimation matrix It is updated online by the following adaptive law: In the formula, Γ i is an element in the positive definite diagonal matrix Γ=diag(Γ1,Γ2), ρ i and is a positive constant.

7. A pneumatic artificial muscle parallel robot control system based on hysteresis compensation, characterized in that: include: A dynamic model building module, which is used to build a dynamic model of the pneumatic artificial muscle parallel robot based on the state information of the pneumatic artificial muscle parallel robot; A hysteresis inverse model construction module, which is used to construct a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model based on the dynamics model of the pneumatic artificial muscle parallel robot; A synchronous controller construction module is used to perform hysteresis feedforward compensation based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model, and to construct an output feedback synchronous controller in combination with a pre-designed tracking error, synchronization error, coupling error and speed estimation system to act on the pneumatic artificial muscle parallel robot.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described in any one of claims 1 to 6 are implemented.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described in any one of claims 1 to 6 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the pneumatic artificial muscle parallel robot control method based on hysteresis compensation as described in any one of claims 1 to 6 are implemented.

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