A Control Method and System for Parallel Pneumatic Artificial Muscle Robots Based on Hysteresis Compensation

Abstract

This invention belongs to the field of robot control and provides a control method and system for a pneumatic artificial muscle parallel robot based on hysteresis compensation. The control method includes: constructing a dynamic model of the pneumatic artificial muscle parallel robot based on its state information; constructing a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model based on the dynamic model; performing hysteresis feedforward compensation based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model; and constructing an output feedback synchronization controller by combining a pre-designed tracking error, synchronization error, coupling error, and velocity estimation system to act on the pneumatic artificial muscle parallel robot, thereby achieving rapid and accurate tracking of a smooth reference trajectory by the active arm.

Description

Technical Field

[0001] This invention belongs to the field of robot control, and particularly relates to a control method and system for a pneumatic artificial muscle parallel robot based on hysteresis compensation. Background Technology

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

[0003] Pneumatic artificial muscles, as a type of biomimetic actuator, can simulate the contraction and relaxation behavior of biological muscles, possessing 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 perform rigid-flexible coupling operations, overcoming the limitations of traditional parallel robots' poor adaptability and low compliance. They have enormous application potential in fields with high requirements for compliance and safety, such as medical rehabilitation and surgical assistance.

[0004] In practical applications, overcoming severe nonlinear problems is a prerequisite for fully realizing the application potential of pneumatic artificial muscle parallel robots. Specifically, during the contraction / relaxation of pneumatic artificial muscles, friction and irreversible deformation easily occur between the outer woven mesh and the inner rubber tube, causing the pneumatic artificial muscle to exhibit hysteresis nonlinear characteristics not found in traditional actuators, which adversely affects control performance. Simultaneously, the hysteresis curve of the pneumatic artificial muscle is asymmetrical and related to the input frequency, further increasing the difficulty of accurately describing the input-output relationship. Among existing pneumatic artificial muscle hysteresis models, operator-based hysteresis models typically have complex structures, their accuracy is positively correlated with the model parameters, and the generated fitting curves are often not smooth enough; differential equation-based hysteresis models have simpler structures, but their 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 overall motion performance. However, existing synchronization control methods require the actual system to be equipped with sensors that provide feedback speed information, and rarely consider convergence speed. This is not conducive to reducing sensor installation costs and improving operating efficiency. Summary of the Invention

[0005] To address at least one of the technical problems mentioned above, this invention provides a control method and system for a pneumatic artificial muscle parallel robot based on hysteresis compensation. It designs an accurate pneumatic artificial muscle hysteresis model, performs corresponding hysteresis compensation, and constructs an output feedback synchronization controller to improve the control performance of the pneumatic artificial muscle parallel robot, enabling the active arm to quickly and accurately track a smooth reference trajectory.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of the present invention provides a control method for a parallel robot with pneumatic artificial muscles based on hysteresis compensation.

[0008] A control method for a parallel pneumatic artificial muscle robot 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] Hysteresis feedforward compensation is performed based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model. Combined with the pre-designed tracking error, synchronization error, coupling error and velocity estimation system, an output feedback synchronization controller is constructed to act on the pneumatic artificial muscle parallel robot.

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

[0013]

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

[0015] As one implementation, the fractional-order Bouc-Wen hysteresis model is used to characterize the input air pressure p. i With rotation angle θ Δi Relationship between them:

[0016]

[0017] In the formula, μ i These are the intermediate state variables of the hysteresis model, and the polynomial terms. Used to characterize the asymmetric properties of hysteresis in pneumatic artificial muscles, where the positive integer N is the number of terms in the polynomial; 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 represents the fractional derivative. and The order of γ; i1 ,γ i2 ,…,γ iN and κ i1 ,κ i2 ,…,κ i5 These are the model parameters to be identified.

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

[0019]

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

[0021] As one implementation method, the expression for the output feedback synchronization controller is:

[0022]

[0023] Where p is the input air pressure of the pneumatic artificial muscle, θ r Let z be the smooth reference trajectory of the active arm, I be the tracking error of the active arm, K0 be the nominal matrix, B and β be the positive definite matrix and positive constant in the coupling error, respectively, K1, K2, K3, K5, K6 be the positive definite diagonal matrices to be designed, and η and χ For variables in the velocity estimation system, For estimating the weight matrix W in a fuzzy logic system, Estimate For the input vector of the fuzzy logic system, λ is the basis function vector in the fuzzy logic system. max (·) represents the largest eigenvalue.

[0024] As one implementation method, the weight estimation matrix The following adaptive law is used for online updates:

[0025]

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

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

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

[0029] The dynamic model construction module is used to construct the dynamic model of the pneumatic artificial muscle parallel robot based on the state information of the pneumatic artificial muscle parallel robot.

[0030] The hysteresis inverse model construction module is used to construct a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model based on the dynamic model of the pneumatic artificial muscle parallel robot.

[0031] The synchronization controller construction module performs hysteresis feedforward compensation based on the fractional-order Bouc-Wen hysteresis model and its corresponding inverse model. Combined with the pre-designed tracking error, synchronization error, coupling error and velocity estimation system, it constructs an output feedback synchronization controller 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 having a computer program stored thereon, which, when executed by a processor, implements the steps in the hysteresis-compensated pneumatic artificial muscle parallel robot control method described above.

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

[0035] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps in the hysteresis-compensated pneumatic artificial muscle parallel robot control method described above.

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

[0037] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the hysteresis-compensated pneumatic artificial muscle parallel robot control method described above.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] (1) This invention provides a control method for a parallel robot with pneumatic artificial muscles based on hysteresis compensation, which can ensure that the active arm can quickly and accurately track a smooth reference trajectory. Specifically, by using fractional calculus to introduce the rate information of the input air pressure, an improved fractional 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, an inverse model is designed using an inverse multiplication structure to perform feedforward compensation for the hysteresis of the pneumatic artificial muscle. 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 velocity estimation system are fused into the filter to achieve output feedback synchronization control without velocity information, which reduces the hardware configuration requirements of the proposed method and makes it applicable to a wider range of scenarios. At the same time, the introduction of the sign function into the velocity estimation system speeds up the system response and effectively improves the operating efficiency.

[0040] (2) This 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. While improving the accuracy of the model, it does not increase the complexity of the model structure.

[0041] (3) In this invention, the problem of speed sensor shortage caused by factors such as physical space or cost is fully considered. A speed estimation system based on available angle information is proposed to generate unmeasurable speed estimation signals online, reduce the configuration requirements of sensor hardware, and broaden the applicability of the proposed method.

[0042] (4) This invention considers a closed-loop structure composed of multiple robotic arms and proposes a finite-time synchronous 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 invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0044] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

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

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

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

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

[0049] Figure 5 These are simulation results of the velocity estimation system in this embodiment of the invention;

[0050] Figure 6 The simulation results for the active arm tracking reference trajectory, tracking error, and pneumatic artificial muscle input air pressure in the embodiments of the present invention are shown. Detailed Implementation

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

[0052] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

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

[0054] Example 1

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

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

[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, perform hysteresis feedforward compensation, and combine it with the pre-designed tracking error, synchronization error, coupling error and velocity estimation system to construct an output feedback synchronization controller to act on the pneumatic artificial muscle parallel robot.

[0059] In step 1, based on the Lagrange modeling method, the following dynamic equations for the pneumatic artificial muscle parallel robot can be established:

[0060]

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

[0062]

[0063] In the formula, the lever arm ι i It can be represented as ι i =ι 0i +ι Δi , ι 0i This is the initial value of the lever arm, ι Δi It is the change in the lever arm during the motion; and These represent the contractile force and hysteresis force of the pneumatic artificial muscle, respectively; the specific forms of other variables are as follows:

[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 the unknown parameters in the pneumatic artificial muscle contraction force model.

[0068] In step 2, for the considered pneumatic artificial muscle parallel robot, the inherent hysteresis of the pneumatic artificial muscle and the asynchrony between the active arms will adversely affect the overall performance. Furthermore, the lack of speed sensors in practical applications renders existing full-state feedback synchronization control methods unusable. Therefore, the control objective is to establish a more accurate pneumatic artificial muscle hysteresis model, perform corresponding hysteresis compensation, and then construct a synchronization controller p that does not require speed feedback to achieve smooth reference trajectory for the active arms. The tracking motion.

[0069] Compared to the hysteresis of actuators such as piezoelectric ceramics, although the hysteresis in pneumatic artificial muscles also exhibits asymmetry and rate-dependent characteristics, its hysteresis curve is more asymmetric and complex. Therefore, directly applying the Bouc-Wen hysteresis model of actuators such as piezoelectric ceramics to pneumatic artificial muscles yields poor fitting results. To address this, an improved fractional-order Bouc-Wen model is designed to characterize the input air pressure p. i With rotation angle θ Δi Relationship between them:

[0070]

[0071] In the formula, μ i These are the intermediate state variables of the hysteresis model, and the polynomial terms. Used to characterize the asymmetric properties of hysteresis in pneumatic artificial muscles, where the positive integer N is the number of terms in the polynomial; carefully designed auxiliary term ξ. i =-κ i4 p i |μ i |-κ i5 |p i |μ i It can store historical information, enhancing the memory of the pneumatic artificial muscle hysteresis model and further improving model accuracy; unlike the integer-order calculus in the traditional Bouc-Wen hysteresis model, 0 < λ i1 ,λ i2 <1 represents the fractional derivative. and ...order, this fractional calculus can be used to determine the input air pressure pi The rate information is indirectly introduced into the model, thus effectively characterizing the rate-related properties of the pneumatic artificial muscle and avoiding complicating the model structure; γi1 ,γ i2 ,…,γ iN and κ i1 ,κ i2 ,…,κ i5 These are the model parameters 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 The reference rotation angle is used. 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 ), Ψ b =diag(ψ b1 ,ψ b2 ), Ψ c =diag(ψ c1 ,ψ c2 ), Θ a =diag(θ) a1 ,θ a2 ), L = diag(ι1,ι2), This is the hysteresis compensation error. Based on this, 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 They are M -1 (θ)Ψ a Θ a The nominal value and the unknown part, i.e., M -1 (θ)Ψ a Θ a =K0+K Δ ; Nonlinear dynamics to be processed It can be represented 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, we introduce the following, which contains z and z s 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), it can be seen that when z c At convergence, z and z s Convergence can also be guaranteed; therefore, the coupling error z is used. c Subsequent controller design helps reduce the computational burden. To achieve output feedback synchronization control without requiring speed information, the following filter with auxiliary variables is designed.

[0083]

[0084] In the formula, β is a positive constant, and the auxiliary variable χ is generated online by the following velocity estimation system:

[0085]

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

[0087]

[0088] Among them, fuzzy logic system Used to estimate uncertain system dynamics Right now

[0089]

[0090] In the formula, W is the weight matrix, and φ(x) is the expression that satisfies... basis function vectors, It is a bounded approximation error vector; therefore, the basis function vector φ(x) cannot be used in the controller unless the velocity estimation signal is used. Replaces immeasurable velocity Therefore, (14) is rewritten in the following form:

[0091]

[0092] In the formula, It is the input vector. There exists 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 The following adaptive law is used for online updates:

[0095]

[0096] In the formula, Γ i ρ is an element in the positive definite diagonal matrix Γ = diag(Γ1, Γ2). i and It is a positive constant. From (17), we know that as long as the initial conditions are satisfied... inequality This holds true in all cases, and thus the estimation error can be obtained. It is bounded, that is w 0i It is a positive constant. In addition, the relevant control parameters must satisfy the following conditions:

[0097]

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

[0099] 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 are obtained:

[0100]

[0101] Based on this, choose a Lyapunov candidate function of the following form.

[0102]

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

[0104]

[0105] The above derivation uses the following inequality:

[0106]

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

[0108]

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

[0110]

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

[0112]

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

[0114] To verify the accuracy of the proposed improved fractional-order Bouc-Wen model in characterizing asymmetric, rate-dependent hysteresis in pneumatic artificial muscles, 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 analyzing the collected input air pressure p i - Rotation angle θ ΔiBy performing parameter identification on the data, the parameter values ​​in the proposed improved fractional-order Bouc-Wen model can be obtained. Since the considered pneumatic artificial muscle parallel robot has a bilaterally symmetrical structure, only the identification results for 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 figure shows the hysteresis fitting results under these model parameters. The dashed line represents the measurement curve, and the solid line represents the fitting curve of the proposed improved fractional-order Bouc-Wen model. This figure demonstrates that the proposed model can fit the input air pressure p1 - rotation angle θ relatively accurately. Δ1 The hysteresis relationship between them is shown, with high accuracy. Meanwhile, Figure 4 The result is after feedforward compensation using the corresponding inverse model, from which the rotation angle θ can be seen. Δ1 With reference rotation angle θ Δr1 The relationship is almost directly proportional, which indicates that the inverse model can effectively compensate for the hysteresis in pneumatic artificial muscles.

[0120] Furthermore, to verify the effectiveness of the proposed output feedback synchronous control method, numerical simulations were performed using a 2-DOF pneumatic artificial muscle parallel robot system. The control objective was to generate a reliable velocity estimation signal quickly and accurately online when velocity sensors were missing or unavailable, and to ensure that the active arm could move quickly and accurately along the following reference trajectory:

[0121]

[0122] The design parameters for the output feedback synchronization control method proposed in this 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 These are simulation results for the output feedback synchronization control method proposed in this invention. Figure 5 In the diagram, the dashed line represents the actual angle / velocity trajectory, and the solid line represents the estimated signal generated online by the velocity estimation system. It can be seen that η1 and η2 can accurately estimate the actual angles θ1 and θ2, respectively. and It can also accurately estimate the actual speed. and This demonstrates that the designed velocity estimation system is effective. Figure 6 In the diagram, the dashed line represents the reference trajectory, and the solid line represents the trajectory under the proposed method. As can be seen from the first four rows of sub-figures, even with different motion frequencies of the two active arms, the proposed method still enables both active arms to quickly track their respective reference trajectories, with relatively small tracking errors z1 and z2. The sub-figures in rows 5 and 6 represent the input air pressure of the two pneumatic artificial muscles, respectively. Therefore, the output feedback synchronization control method proposed in this invention can achieve excellent velocity estimation and motion tracking effects.

[0124] Example 2

[0125] This invention provides a control system for a pneumatic artificial muscle parallel robot based on hysteresis compensation, comprising:

[0126] The dynamic model construction module is used to construct the dynamic model of the pneumatic artificial muscle parallel robot based on the state information of the pneumatic artificial muscle parallel robot.

[0127] The hysteresis inverse model construction module is used to construct a fractional-order Bouc-Wen hysteresis model and its corresponding inverse model based on the dynamic model of the pneumatic artificial muscle parallel robot.

[0128] The synchronization 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 synchronization controller based on the pre-designed tracking error, synchronization error, coupling error and velocity estimation system, so as to act on the pneumatic artificial muscle parallel robot.

[0129] It should be noted that each module in this embodiment corresponds one-to-one with each step in Embodiment 1, and the specific process will not be described in detail here.

[0130] Example 3

[0131] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the hysteresis-compensated pneumatic artificial muscle parallel robot control method described above.

[0132] Example 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 hysteresis-compensated pneumatic artificial muscle parallel robot control method described above.

[0134] Example 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, it implements the steps in the above-described control method for a pneumatic artificial muscle parallel robot based on hysteresis compensation.

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

[0137] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

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

[0139] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A hysteresis compensation-based pneumatic artificial muscle parallel robot control method, characterized by, The method comprises the following steps: constructing a dynamics model of the pneumatic artificial muscle parallel robot based on state information of the pneumatic artificial muscle parallel robot; constructing a fractional order Bouc-Wen hysteresis model and a corresponding inverse model thereof based on the dynamics model of the pneumatic artificial muscle parallel robot; performing hysteresis feedforward compensation based on the fractional order Bouc-Wen hysteresis model and the corresponding inverse model thereof, and constructing an output feedback synchronization 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; The fractional-order Bouc-Wen hysteresis model is used to characterize the relationship between the input air pressure and the rotation angle ​ In the formula, These are the intermediate state variables of the hysteresis model, and the polynomial terms. Positive integers are used to characterize the asymmetric properties of hysteresis in pneumatic artificial muscles. The term number of the polynomial; auxiliary terms Used to store historical information; These are fractional derivatives and The order of; and These are the model parameters to be identified.

2. The hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to claim 1, characterized by, the dynamics model of the pneumatic artificial muscle parallel robot is expressed as: wherein, is an angle vector of the active arm, composed of an initial angle and a rotation angle ; is a system input torque vector, related to the input air pressure of the pneumatic artificial muscle; is an inertia matrix, is a Coriolis force matrix, is a vector related to gravity.

3. The hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to claim 1, characterized by, the corresponding inverse model of the fractional order Bouc-Wen hysteresis model is expressed as: In the formula, is the reference rotation angle.

4. The hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to claim 1, characterized by, the output feedback synchronization controller is expressed as: where is the input air pressure of the pneumatic artificial muscle, is the smooth reference trajectory of the manipulator, is the tracking error of the manipulator, is the identity matrix of appropriate dimension, is the nominal value matrix, and are the positive definite matrix and the positive constant in the coupling error, respectively, is the positive definite diagonal matrix to be designed, and are the variables in the velocity estimation system, is the estimation of the weight matrix in the fuzzy logic system, is the estimation is the input vector of the fuzzy logic system, is the basis function vector in the fuzzy logic system; denotes the largest eigenvalue.

5. The hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to claim 4, characterized by, weight estimation matrix updated online by the following adaptive law: wherein is a positive definite diagonal matrix whose elements, and are positive constants.

6. A hysteresis compensation-based pneumatic artificial muscle parallel robot control system, characterized by, The method comprises the following steps: a dynamics model construction module configured to construct a dynamics model of the pneumatic artificial muscle parallel robot based on state information of the pneumatic artificial muscle parallel robot; a hysteresis inverse model construction module configured to construct a fractional order Bouc-Wen hysteresis model and a corresponding inverse model thereof based on the dynamics model of the pneumatic artificial muscle parallel robot; a synchronization controller construction module configured to perform hysteresis feedforward compensation based on the fractional order Bouc-Wen hysteresis model and the corresponding inverse model thereof, and construct an output feedback synchronization 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; The fractional-order Bouc-Wen hysteresis model is used to characterize the relationship between the input air pressure and the rotation angle ​ wherein, is the intermediate state variable of the hysteresis model, the polynomial terms are used to represent the asymmetric characteristics of the pneumatic artificial muscle hysteresis, the positive integer is the number of terms of the polynomial; the auxiliary terms are used to store the history information; are the orders of the fractional derivative and respectively; and are the model parameters to be identified.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps in the hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to any one of claims 1-5.

8. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instructions are executed by the processor to implement the steps in the hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to any one of claims 1-5.

9. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the steps in the hysteresis compensation-based pneumatic artificial muscle parallel robot control method according to any one of claims 1-5.

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