A control method for the mobile platform of a parallel robot for anti-slip sandblasting and rust removal

Abstract

The present invention discloses a control method for a parallel robot mobile platform for anti-slip sandblasting and rust removal, and belongs to the field of sandblasting and rust removal of steel box girders. First, a pressure-bearing model of a driving wheel is established according to the physical characteristics of the road surface, and then the dynamic characteristics of the slip rate are obtained according to the friction coefficient equation; the influence of the slip rate on the friction coefficient of the mobile platform is analyzed, and a kinematic model of the mobile platform is established. The slip rate observer is constructed using the model to estimate the slip rate of the wheel in real time, thereby establishing a dynamic model of the mobile platform considering the slip characteristics; then, an anti-slip fast integer power second-order sliding mode controller is designed based on the model to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the sliding mode control jitter. Finally, the mobile platform control system is constructed to make it move according to the desired trajectory. The present invention can ensure that the mobile platform can achieve high-performance tracking of the desired motion trajectory in the presence of slip disturbances.

Description

Technical Field

[0001] The invention relates to a sandblasting and rust removal technology for steel box beams, and in particular to a control method for a mobile platform of an anti-slip sandblasting and rust removal parallel robot. Background Art

[0002] In order to realize the sandblasting and rust removal of steel box girders, a parallel robot for sandblasting and rust removal of steel box girders was independently developed and designed based on the Stewart parallel mechanism. It consists of a parallel mechanism, a lifting mechanism and a mobile platform, etc. It has the advantages of high rigidity, strong bearing capacity and good mobility, and can realize arbitrary movement, free lifting and lowering, and six-degree-of-freedom posture precise motion operation. When the sandblasting and rust removal parallel robot is sandblasting, the quartz sand and steel sand mixture used will hit the surface of the steel box girder at high speed to form a gravel accumulation road surface with a thickness of about 4 cm. This road surface has a low adhesion coefficient. For the mobile platform under study, the expected motion trajectory is designed as an "S-type" acceleration and deceleration curve. When the mobile platform accelerates, the driving force may be too large, and it is easy to slip when driving on an uneven gravel road surface. The occurrence of slip will seriously affect the control performance of the mobile platform. Therefore, it is necessary to study the high-performance trajectory tracking control of the mobile platform under slip conditions.

[0003] The document "Unmanned Ground Vehicle Control Method Based on Wheel-Ground Friction Compensation Mechanism" (Wang Linjiu et al. Dalian University of Technology 2016) aims at the problem of tracking the trajectory of a wheeled mobile robot under slippage. The slip rate is used as a variable to quantitatively analyze the interference force generated by the slippage, and is introduced into the dynamic model of the unmanned vehicle together with the friction interference. Its main controller adopts the terminal sliding mode control method. There are two problems with this method. First, the slip rate is affected by the friction factor of the gravel accumulation ground, and is a dynamic change with the ground adhesion coefficient. However, the slip rate parameter in the model of this method is quantitatively calculated, which makes it difficult to accurately and real-time reflect the change of the slip rate. Second, its terminal sliding mode control method has singularity and jitter problems. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art. For the sandblasting and rust removal parallel robot mobile platform, a control method for the anti-slip sandblasting and rust removal parallel robot mobile platform is proposed, and a control system is constructed to solve the problem of high-performance trajectory tracking control of the sandblasting and rust removal parallel robot mobile platform under low-adhesion road surfaces with sand and gravel accumulation.

[0005] The anti-slip sandblasting and rust removal parallel robot mobile platform control system includes the following steps:

[0006] 1) Determine the expected motion trajectory of the mobile platform according to the blasting path and blasting process requirements of the sandblasting and rust removal parallel robot;

[0007] 2) According to the physical characteristics of the gravel accumulation road surface, the pressure model of the driving wheel of the mobile platform is established, and the dynamic characteristic curve of the slip rate is further obtained according to the friction coefficient equation; the influence of the slip rate on the friction coefficient of the mobile platform is analyzed, and the kinematic model of the mobile platform of the sandblasting and rust removal parallel robot is established. According to the kinematic model of the mobile platform, a new slip rate observer is constructed based on the nonlinear disturbance observer to estimate the slip rate of the wheel in real time;

[0008] 3) Using the Lagrangian method, a dynamic model of a mobile platform considering the sliding characteristics in a sand and gravel accumulation environment is established;

[0009] 4) Based on the mobile platform dynamics model considering the slip characteristics established in step 3), a fast integer power second-order sliding mode controller for the anti-slip sandblasting and rust removal parallel robot mobile platform is designed to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the sliding mode control jitter.

[0010] 5) The distributed structure of "upper computer (IPC-610L) + lower computer (CK3M)" is adopted to build an anti-slip sandblasting and rust removal parallel robot mobile platform control system to achieve anti-slip high-performance trajectory tracking of the sandblasting and rust removal parallel robot mobile platform.

[0011] 6) The calculated driving wheel torque control command is sent to each motor driver to make the sandblasting and rust removal parallel robot mobile platform move along the desired trajectory.

[0012] The present invention proposes for the first time a control method for a mobile platform of a parallel robot for anti-slip sandblasting and rust removal, which realizes high-performance trajectory tracking control of a mobile platform of a parallel robot for sandblasting and rust removal on a low-adhesion road surface with sand and gravel accumulation. The characteristics and beneficial effects are as follows:

[0013] 1) Aiming at the anti-slip problem of the mobile platform of the sandblasting and rust removal parallel robot on the low-adhesion road with sand and gravel accumulation, a new slip rate observer is constructed according to the kinematic model of the mobile platform and based on the nonlinear disturbance observer to estimate the slip rate of the wheel in real time. It can not only eliminate the complex calculation amount brought by the quantitative calculation method in the controller design, but also establish the dynamic model of the mobile platform of the sandblasting and rust removal parallel robot that reflects the real-time change of the slip rate.

[0014] 2) In order to improve the robustness of the control system of the sandblasting and rust removal parallel robot mobile platform to overcome time-varying disturbances in the external environment (wind force, tire inflation volume, road friction, etc.) and solve the chattering problem of the first-order sliding mode control, the present invention adopts a superhelical algorithm to design an anti-slip fast integer power second-order sliding mode controller for the sandblasting and rust removal parallel robot mobile platform to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the sliding mode control chattering. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1This is a real picture of the parallel robot for sandblasting and rust removal.

[0016] Figure 2 Kinematic geometry model of the mobile platform.

[0017] Figure 3 Coordinate diagram of the mobile platform pose tracking error.

[0018] Figure 4 This is a top view of the mobile platform structure of the sandblasting and rust removal parallel robot.

[0019] Figure 5 Schematic diagram of the control system for the parallel robot mobile platform for anti-slip sandblasting and rust removal.

[0020] Figure 6 It is a control system for the parallel robot mechanism for sandblasting and rust removal.

[0021] In the figure: 1-spray gun, 2-parallel mechanism, 3-sandblasting hose, 4-mobile platform, 5-lifting mechanism, 6-electrical control cabinet, 7-host computer. DETAILED DESCRIPTION

[0022] The specific implementation manner of the present invention is further described below with reference to the accompanying drawings.

[0023] Firstly, the expected motion trajectory of the mobile platform is determined according to the sandblasting path and sandblasting process requirements of the sandblasting and rust removal parallel robot. Then, the pressure model of the driving wheel of the mobile platform is established according to the physical characteristics of the gravel accumulation road surface. The dynamic characteristic curve of the slip rate is further obtained according to the friction coefficient equation. The influence of the slip rate on the friction coefficient of the mobile platform is analyzed, and the kinematic model of the mobile platform of the sandblasting and rust removal parallel robot is established by the particle motion analysis method. According to the kinematic model of the mobile platform, a new slip rate observer is constructed based on the nonlinear disturbance observer to estimate the slip rate of the wheel in real time. The Lagrangian method is then used to establish the dynamic model of the mobile platform considering the slip characteristics in the sand and gravel accumulation environment. Finally, based on the established dynamic model of the mobile platform considering the slip characteristics, a fast integer power second-order sliding mode controller of the anti-slip sandblasting and rust removal parallel robot mobile platform is designed to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the chattering of the sliding mode control. Furthermore, the distributed structure of "upper computer (IPC-610L) + lower computer (CK3M)" is used to build a control system for the anti-slip sandblasting and rust removal parallel robot mobile platform; then, the calculated driving wheel torque control command is sent to each motor driver to make the sandblasting and rust removal parallel robot mobile platform move according to the desired trajectory. The specific method is as follows:

[0024] 1. According to the sandblasting process and sandblasting path of the sandblasting and rust removal parallel robot, determine the expected motion trajectory of the mobile platform and design the "grating type" sandblasting trajectory of the sandblasting and rust removal robot mobile platform as the expected running trajectory of the mobile platform according to the sliding characteristics on the gravel accumulation road surface, and determine the expected motion trajectory of the mobile platform in the generalized coordinate system q = (x, y, θ) T , where the desired posture component x is the X-axis coordinate value, y is the Y-axis coordinate value, both in units of m, and the angle θ between the horizontal direction of the mobile platform and the X-axis is in rad; at the same time, the dynamic characteristic curve of the slip rate is obtained according to the friction coefficient equation to determine the optimal slip rate value.

[0025] 2. According to the physical characteristics of the gravel accumulation road surface of the mobile platform, the pressure model of the driving wheel is established and the influence of the slip rate parameters on the friction coefficient of the mobile platform is analyzed. The kinematic model of the mobile platform is established using the particle motion analysis method.

[0026] According to the motion analysis of the mobile platform, the pressure model of the driving wheels of the mobile platform is established:

[0027]

[0028] Where m is the wheel mass, μ is the adhesion coefficient, and F Z is the vertical pressure of the wheel, F P is the shear force between the driving wheel and the gravel accumulation road surface, v is the forward linear speed of the wheel, c i (i=1, 2, 3, 4) is the friction curve coefficient, and it changes with the changes in road conditions and wheel tires.

[0029] Based on the slip rate variable analysis, we know that: λ∈[0,1), the kinematic model of the mobile platform can be established:

[0030]

[0031] In the formula is the derivative of curvature, λ * is the optimal slip ratio,

[0032] 3. According to the kinematic model of the mobile platform and based on the nonlinear disturbance observer, a new slip rate observer is constructed to estimate the wheel slip rate in real time.

[0033] In order to estimate the slip rate of the wheel in real time, based on the kinematic model of the mobile platform (2), the disturbance observer is designed as follows:

[0034]

[0035] Since the error of the system converges to the origin in a finite time, based on this, the estimated expression of the interference d can be obtained as follows:

[0036]

[0037] The real-time estimated value of the slip ratio parameter is obtained through formula (4):

[0038]

[0039] 4. Use the Lagrangian method to establish a dynamic model of a mobile platform taking into account the sliding characteristics in a sand and gravel accumulation environment.

[0040] The Lagrangian function method is used to establish the dynamic model of the mobile platform considering the slip rate:

[0041]

[0042] Where M(q) is the mass matrix; is the Coriolis force and centrifugal force matrix, describing the dynamic characteristics of the mobile platform when turning; H(q) is the non-holonomic constraint matrix; N(q) is the input transformation matrix. τ is the torque input matrix, τ v Output driving force for the mobile platform driving motor, τ σ Output torque for the mobile platform steering motor.

[0043] By eliminating the non-holonomic constraint terms, the dynamic model of the mobile platform considering the sliding characteristics in the sand and gravel accumulation environment is established as follows:

[0044]

[0045] In the formula

[0046] 5. Based on the established dynamic model of the mobile platform considering the slip characteristics, a fast integer power second-order sliding mode controller for the anti-slip sandblasting and rust removal parallel robot mobile platform is designed to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the sliding mode control jitter.

[0047] First, design the kinematic auxiliary speed controller, that is, the desired input V of the dynamic controller c for:

[0048]

[0049] Where k x , k y , k θ is a constant, and v c ≠0.

[0050] Secondly, the dynamic sliding mode controller is designed: the dynamic controller takes the output of the auxiliary speed controller as the reference control input.

[0051] Design the following integral sliding surface:

[0052]

[0053] In the formula, s v (t) and s σ (t) are sliding mode variables of velocity and curvature, β v and β σ is the control parameter. When the sliding mode variable s v (t) and s σ (t) approaches zero, the tracking error e v and e σ will also approach zero. v c and v represent the virtual expected linear velocity and the actual linear velocity of the mobile platform, respectively. and σ represent the derivative of the virtual desired curvature and the derivative of the actual curvature of the mobile platform, respectively, β v >0,β σ >0.

[0054] Taking the derivative of both sides of equation (9) and combining it with the mobile platform dynamics model equation (7), we can get

[0055]

[0056] In order to improve the convergence speed of the mobile platform to overcome the sliding disturbance and weaken the chattering caused by the sliding mode control, the second-order sliding mode reaching law is designed by introducing a fast integer power linear correction term:

[0057]

[0058] Where:

[0059] Based on equations (10) and (11), the anti-slip fast integer power second-order sliding mode control law of the sandblasting and rust removal parallel robot mobile platform is obtained:

[0060]

[0061] 6. A distributed structure, i.e., "upper computer + lower computer" structure, is used to construct an anti-slip sandblasting and rust removal parallel robot control system.

[0062] Taking Omron CK3M multi-axis motion controller as the core control unit, an anti-slip sandblasting and rust removal parallel robot control system is constructed. The control system adopts a distributed structure of "upper computer Advantech industrial computer + lower computer Omron CK3M multi-axis motion controller".

[0063] 7. Send the calculated driving wheel torque control command to each motor driver to make the sandblasting and rust removal parallel robot mobile platform move along the desired trajectory.

[0064] The mobile platform driving wheel torque control quantity calculated according to formula (12) in step 5) is sent to the sandblasting and rust removal parallel robot mobile platform motor driver through the control system through host computer programming to drive the mechanism to move according to the desired trajectory.

[0065] An embodiment of the present invention is provided below:

[0066] Example 1

[0067] The control method of the present invention mainly focuses on realizing high-performance trajectory tracking control of the mobile platform of the sandblasting and rust removal parallel robot under the gravel accumulation road surface by using a new slip rate observation technology and fast integer power second-order sliding mode control technology. The specific implementation method of the control method is as follows:

[0068] 1. According to the sandblasting process and sandblasting path of the sandblasting and rust removal parallel robot, determine the expected motion trajectory of the mobile platform, design the "grating type" sandblasting trajectory of the sandblasting and rust removal robot mobile platform as the expected running trajectory of the mobile platform, and determine the expected motion trajectory of the mobile platform in the generalized coordinate system q = (x, y, θ) T During the actual sandblasting operation, the mobile platform mainly moves parallel to the steel box beam along the x direction. The specific expression is as follows:

[0069]

[0070] y=0 (14)

[0071] θ=0 (15)

[0072] 2. Use the particle motion analysis method to establish the kinematic model of the mobile platform.

[0073] The nonholonomic constraints of the mobile platform kinematics are:

[0074]

[0075] Where H(q) is the non-holonomic constraint matrix:

[0076] The kinematic model of the mobile platform under the nonholonomic constraint (16) is:

[0077]

[0078] In the formula, is the angular velocity of the driving wheel of the mobile platform, l is the axle spacing between the front and rear wheels of the mobile platform, and r is the wheel radius of the mobile platform;

[0079] Define the trajectory curvature σ:

[0080]

[0081] Establish the kinematic model of the mobile platform:

[0082]

[0083] 3. According to the kinematic model of the mobile platform and based on the nonlinear disturbance observer, a new slip rate observer is constructed to estimate the wheel slip rate in real time.

[0084] First, transform equation (19) into the following form.

[0085]

[0086] The matrix expression is as follows:

[0087]

[0088] And J 1 (q) is a matrix that does not contain slip rate parameters, only J 2 (q) contains unknown slip rate parameters, which are assumed as follows:

[0089]

[0090] Since the slip ratio λ is bounded, d in equation (22) is a bounded uncertain disturbance. In order to estimate the slip ratio, the present invention estimates the size of the disturbance d by designing a disturbance observer, and finally obtains the estimated value of the slip ratio parameter by equation (27).

[0091] First, write equation (20) and equation (22) as follows:

[0092]

[0093] Design the observer as follows:

[0094]

[0095] Subtract (24) from (23) to get the system error formula, where ξ is a constant. If And κ,ρ satisfy the following conditions:

[0096]

[0097] Then the error of the system can converge to the origin in a finite time, so the estimated expression of the slip disturbance d can be obtained as follows:

[0098]

[0099] From the above, the estimated value of the slip rate parameter can be obtained as follows

[0100]

[0101] In the formula, is the component vector of the slip disturbance estimate.

[0102] 4. Establish a dynamic model of a mobile platform taking into account the sliding characteristics in a sand and gravel accumulation environment.

[0103] The Lagrangian function method is used to establish the dynamic model of the mobile platform considering slippage:

[0104]

[0105] Where L is the Lagrangian function.

[0106] The total kinetic energy T of the mobile platform can be expressed as:

[0107] T=T p +T fw +T rw (29)

[0108] Where, T p 、T fw 、T rw are the vehicle body kinetic energy, the front wheel kinetic energy and the rear wheel kinetic energy respectively, and are specifically expressed as shown in equations (30), (31) and (32):

[0109]

[0110] In the formula, m p is the mass of the mobile platform, is the moving speed of the center of mass of the mobile platform along the axis X, is the moving speed of the center of mass of the mobile platform along the Y axis, I p is the moment of inertia of the vehicle body.

[0111]

[0112] In the formula, m w is the wheel mass, is the moving speed of the right front wheel along the X axis, is the moving speed of the right front wheel along the Y axis, is the moving speed of the left front wheel along the X axis, is the moving speed of the right front wheel along the Y axis, I w is the moment of inertia of the wheel.

[0113]

[0114] In the formula, is the moving speed of the right rear wheel along the X axis, is the moving speed of the right rear wheel along the Y axis, is the moving speed of the left rear wheel along the X axis, is the moving speed of the left rear wheel along the Y axis.

[0115] To simplify the derivation of the Lagrangian function, we can use:

[0116]

[0117] m a =m p l+2m w l (34)

[0118]

[0119] Substituting equations (30), (31), and (32) into equation (28), the general form of the mobile platform dynamics model is simplified as follows:

[0120]

[0121] In the formula, M(q) is the mass matrix, which is also a positive definite and symmetric matrix; is the Coriolis force and centrifugal force matrix, which describes the dynamic characteristics of the mobile platform when turning; τ is the torque input matrix, τ v Output driving force for the mobile platform driving motor, τ σ is the output torque of the mobile platform steering motor. The specific values ​​of each matrix or vector are as follows:

[0122]

[0123]

[0124] The mobile platform dynamics model includes a nonholonomic constraint coefficient γ, which is an unknown constant. Multiply each term in equation (36) by J T , and the nonholonomic constraint term is substituted into equation (36), thereby obtaining the dynamic equation of the mobile platform considering the slip rate parameter under the elimination of the nonholonomic constraint term:

[0125]

[0126] In the formula N=J T N. The specific forms of each matrix are as follows:

[0127]

[0128]

[0129] matrix and The variables are defined as follows:

[0130]

[0131]

[0132] Finally, a dynamic model of the mobile platform of the sandblasting and rust removal parallel robot considering the sliding characteristics under the gravel accumulation road surface was established:

[0133]

[0134] 5. Based on the established dynamic model of the mobile platform considering the slip characteristics, a fast integer power second-order sliding mode controller for the anti-slip sandblasting and rust removal parallel robot mobile platform is designed to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the sliding mode control jitter.

[0135] First, design the kinematic auxiliary speed controller, that is, the desired input V of the dynamic controller c for:

[0136]

[0137] In the formula, v c is the virtual expected speed, v d is the expected speed, σ c is the virtual expected curvature, σ d is the desired curvature, x e is the displacement error of the mobile platform in the x direction, y e is the displacement error of the mobile platform in the y direction, θ e is the heading angle error, k x , k y , k θ is a constant, and v c ≠0.

[0138] Secondly, a dynamic sliding mode controller is designed: the dynamic controller takes the output of the auxiliary speed controller as the reference control input.

[0139] Equation (39) has calculated the virtual expected input V of dynamic control c =[v c σ c ], and the velocity tracking error is defined as:

[0140]

[0141] First, design the integral sliding surface as shown below:

[0142]

[0143] In the formula, s v (t) and s σ(t) are sliding mode variables of the mobile platform speed and curvature, β is the sliding surface control parameter, β v and β σ is the control parameter and β v >0,β σ >0,e v is the linear velocity tracking error of the mobile platform, e σ is the curvature tracking error of the mobile platform.

[0144] The derivative of the sliding surface of equation (41) is:

[0145] Combined with the mobile platform dynamics model (38), we can get

[0146]

[0147] In order to improve the convergence speed of the mobile platform to overcome the sliding disturbance and weaken the chattering caused by the sliding mode control, the second-order sliding mode reaching law is designed by introducing a fast integer power linear correction term:

[0148]

[0149] Where: Based on equations (43) and (44), the anti-slip fast integer power second-order sliding mode control law of the sandblasting and rust removal parallel robot mobile platform is obtained:

[0150]

[0151] 6. Use a distributed structure, i.e., "upper computer + lower computer" structure, to build an anti-slip sandblasting and rust removal parallel robot control system;

[0152] Taking Omron CK3M multi-axis motion controller as the core control unit, an anti-slip sandblasting and rust removal parallel robot control system is constructed. The control system adopts a distributed structure of "upper computer Advantech industrial computer + lower computer Omron CK3M multi-axis motion controller".

[0153] 7. Send the calculated driving wheel torque control command to each motor driver to make the sandblasting and rust removal parallel robot mobile platform move along the desired trajectory.

[0154] The mobile platform driving wheel torque control quantity calculated according to formula (45) in step 5) is sent to the sandblasting and rust removal parallel robot mobile platform motor driver through the control system through host computer programming to drive the mechanism to move according to the desired trajectory.

Claims

1. A method for controlling a mobile platform of a parallel robot for anti-slip sandblasting and rust removal, characterized in that: The steps include: 1) Determine the expected motion trajectory of the mobile platform according to the blasting path and blasting process requirements of the sandblasting and rust removal parallel robot; 2) According to the physical characteristics of the gravel accumulation road surface, the pressure model of the driving wheel of the mobile platform is established, and the dynamic characteristic curve of the slip rate is further obtained according to the friction coefficient equation; the influence of the slip rate on the friction coefficient of the mobile platform is analyzed, and the kinematic model of the mobile platform of the sandblasting and rust removal parallel robot is established. According to the kinematic model of the mobile platform, a new slip rate observer is constructed based on the nonlinear disturbance observer to estimate the slip rate of the wheel in real time; 3) Using the Lagrangian method, a dynamic model of a mobile platform considering the sliding characteristics in a sand and gravel accumulation environment is established; 4) Based on the mobile platform dynamics model considering the slip characteristics established in step 3), a fast integer power second-order sliding mode controller for the anti-slip sandblasting and rust removal parallel robot mobile platform is designed to improve the convergence speed of the mobile platform to overcome the slip disturbance and weaken the sliding mode control chattering; 5) Adopt the distributed structure of "upper computer + lower computer" to build an anti-slip sandblasting and rust removal parallel robot mobile platform control system to achieve anti-slip high-performance trajectory tracking of the sandblasting and rust removal parallel robot mobile platform; 6) Sending the calculated driving wheel control instructions to each motor driver to make the sandblasting and rust removal parallel robot mobile platform move along the desired trajectory; In step 2), a kinematic model of the mobile platform is established, and a disturbance observer is constructed according to the kinematic model of the mobile platform to estimate the slip rate of the wheel in real time, specifically including: According to the motion analysis of the mobile platform, the horizontal and vertical force balance pressure model of the mobile platform subjected to the resistance of sand and gravel is established: Where m is the wheel mass, is the acceleration of the mobile platform, μ is the adhesion coefficient, F Z is the vertical pressure of the wheel, λ is the slip rate of the wheel, F P is the shear force between the driving wheel and the gravel accumulation road surface, μ(λ) is the dynamic characteristic curve equation of the slip rate, c i is the friction curve coefficient, and changes with the road conditions and wheel tires, where i = 1, 2, 3, 4; Establish the kinematic model of the mobile platform: In the formula, is the velocity component of the mobile platform in the X-axis direction, is the velocity component of the mobile platform in the Y-axis direction, is the derivative of the angle between the horizontal direction of the mobile platform and the X-axis, is the steering angular velocity of the front wheel of the mobile platform, θ is the angle between the horizontal direction of the mobile platform and the X-axis, λ∈[0,1), λ * is the optimal slip rate, σ is the trajectory tracking curvature, is the derivative of the trajectory tracking curvature, l is the axle spacing between the front and rear wheels of the mobile platform, v is the linear velocity of the mobile platform, J(q) is the Jacobian matrix of the mobile platform, and V is the velocity matrix of the mobile platform; In order to estimate the wheel slip rate in real time, the kinematic model of the mobile platform (2) is used to construct the disturbance observer as follows: In the formula, is the observer design function, J1(q) is the conversion matrix, κ and ρ are the observer switching gains, q is the pose vector of the mobile platform, sgn() is the sign function, and η is the observer parameter vector; Since the error of the system converges to the origin in a finite time, based on this, the estimated expression of the interference d can be obtained as follows: In the formula, is the estimated value of slip disturbance; The real-time estimated value of the slip ratio parameter is obtained through formula (4): In the formula, is the estimated value of the slip ratio, is the component vector of the estimated value of the slip disturbance; In step 3), a dynamic model of a mobile platform considering the sliding characteristics in a sand and gravel accumulation environment is established, specifically including: The Lagrangian function method is used to establish the dynamic model of the mobile platform considering the slip rate: Where q is the pose vector of the mobile platform, and M(q) is the mass matrix; is the Coriolis force and centrifugal force matrix, describing the dynamic characteristics of the mobile platform when turning; H(q) is the nonholonomic constraint matrix, H T (q) is the transpose of the nonholonomic constraint matrix; N(q) is the input transformation matrix, τ is the moment input matrix, τ v Output driving force for the mobile platform driving motor, τ σ Output torque for the mobile platform steering motor; By eliminating the non-holonomic constraint terms, the dynamic model of the mobile platform considering the sliding characteristics in the sand and gravel accumulation environment is established as follows: In the formula, is the derivative of the velocity matrix, J is the Jacobian matrix, J T is the transpose of the Jacobian matrix, 2. The method according to claim 1, characterized in that: Step 4) The specific process is: Design the following integral sliding surface: Where S is the sliding surface function, e is the tracking error, β is the sliding surface parameter, e(τ) is the torque error, τ is the joint driving force, and s v (t) and s σ (t) are sliding mode variables of velocity and curvature, β v and β σ is the control parameter, when the sliding mode variable s v (t) and s σ (t) approaches zero, the tracking error e v and e σ will also approach zero, is the tracking error of the curvature derivative, and v c and v represent the virtual expected linear velocity and the actual linear velocity of the mobile platform, respectively. and σ represent the derivative of the virtual desired curvature and the derivative of the actual curvature of the mobile platform, respectively, β v >0,β σ >0; Taking the derivative of both sides of equation (8) and combining it with the mobile platform dynamics model equation (7), we can get is the derivative function of the sliding surface function, is the derivative of the desired velocity of the mobile platform. In order to improve the convergence speed of the mobile platform to overcome the sliding disturbance and weaken the chattering caused by the sliding mode control, the second-order sliding mode reaching law is designed by introducing a fast integer power linear correction term: Where: is the superhelical reaching law function, s1 is the velocity sliding mode variable, s2 is the curvature sliding mode variable, α i is the switching gain of the superhelical reaching law and α i >0Among them, i＝1…4； Based on equations (9) and (10), the anti-slip fast integer power second-order sliding mode control law of the sandblasting and rust removal parallel robot mobile platform is obtained as follows: In the formula, is the derivative of the desired velocity of the mobile platform.

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