A hierarchical fault-tolerant control method for a four-wheel independent electric drive port AGV

Abstract

The present invention discloses a hierarchical fault-tolerant control method for a four-wheel independent electric-driven port AGV. The control system comprises an upper control module, a middle control module, a lower control module and an execution module. The upper control module comprises an MPC controller and a PI speed controller. The upper control module is used to maintain the running track. The middle controller module designs a yaw angular velocity sliding mode controller and a center of mass sideslip angle sliding mode controller based on the sliding mode control theory, and then calculates the optimal additional yaw torque through a failure allocation strategy. The lower control module comprises a fault-tolerant control distributor. When a wheel motor fails, the fault-tolerant control distributor redistributes the driving torques of the remaining wheels according to the total longitudinal torque and the optimal additional yaw torque required for the port AGV to travel, so that the remaining wheel motors rotate to form a closed-loop control, thereby ensuring that the port AGV can still travel normally when the motor fails, thereby improving the working efficiency and safety of the port AGV.

Description

Technical Field

[0001] The present invention belongs to the technical field of fault-tolerant control of special operation vehicles, and in particular relates to a hierarchical fault-tolerant control method of a four-wheel independent electric-driven port AGV. Background Art

[0002] Four-wheel independent electric drive vehicles refer to vehicles with independent power sources on all four wheels, such as hub motors, wheel-side motors, etc. The driving force obtained by the vehicle is twice that of a two-wheel drive, which greatly improves the vehicle's driving ability. However, the safety issues caused by motor failure are also worthy of attention. As a special operation vehicle, the port heavy-duty AGV (hereinafter referred to as the port AGV) has the characteristics of a high center of gravity and a wide wheelbase. In addition, due to the harsh operating environment of the port, affected by rainfall, wind erosion, salt erosion, etc., the probability of motor failure is relatively high. The existing control strategy is to directly shut down and repair after a failure occurs.

[0003] Since the four-wheel independent drive port AGV is a redundant system, by utilizing its redundant characteristics, when any wheel motor of the port AGV fails during operation, the healthy motor torque can be controlled through the control strategy, so that the port AGV can still run normally when the motor fails, ensuring the driving safety of the port AGV.

[0004] Hierarchical control is common in the field of vehicle stability control and is derived from the direct yaw moment control method. The direct yaw moment control method is a method that obtains the error between the ideal state and the actual driving state and calculates its additional yaw moment, and converts the obtained additional yaw moment into motor torque through appropriate torque distribution based on the characteristics of distributed drive. The existing hierarchical fault-tolerant control is mainly aimed at passive fault tolerance, that is, the passive fault-tolerant control strategy does not rely on the detection of system faults. Any driving faults in the system can be handled by the original control strategy itself. There is little research on active fault tolerance, especially the control of the failure of a wheel motor under four-wheel independent drive. Summary of the invention

[0005] In view of the deficiencies in the prior art, the technical problem that the present invention intends to solve is to provide a hierarchical fault-tolerant control method for a four-wheel independently electric-driven port AGV.

[0006] The technical method adopted by the present invention to solve the technical problem is as follows:

[0007] A hierarchical fault-tolerant control method for a four-wheel independent electric drive port AGV, the control system used includes an upper control module, a middle control module, a lower control module and an execution module, the upper control module includes an MPC controller and a PI speed controller, the middle controller module includes a yaw angular velocity sliding mode controller and a center of mass sideslip angle sliding mode controller, the lower control module includes a fault-tolerant control distributor, and the execution module includes a left front wheel motor, a right front wheel motor, a left rear wheel motor and a right rear wheel motor; the method includes the following contents:

[0008] 1. Establish the steering model and dynamic model of the port AGV vehicle. The steering model of the port AGV vehicle is:

[0009]

[0010] In the formula, δ 1,1 ,δ 1,2 ,δ 2,1 ,δ 2,2 They represent the left front wheel steering angle, the right front wheel steering angle, the left rear wheel steering angle and the right rear wheel steering angle respectively, G1=a+Rsinβ represents the longitudinal distance between the geometric center of the left front wheel or the right front wheel and the steering center, G2=b-Rsinβ represents the longitudinal distance between the geometric center of the left rear wheel or the right rear wheel and the steering center, It represents the lateral distance between the geometric center of the left front wheel or the left rear wheel and the steering center. The length direction of the port AGV is the longitudinal direction, and the width direction of the port AGV is the lateral direction. a and b are the distances from the front axle and the rear axle to the center of mass of the port AGV, respectively. β is the sideslip angle of the center of mass. R is the distance from the steering center to the center of mass of the port AGV. l is the coaxial wheelbase.

[0011] The dynamic model of the port AGV vehicle is:

[0012]

[0013] in, is the longitudinal torque, represents the lateral torque, represents the yaw torque, M represents the full load mass, u, Respectively represent the longitudinal velocity and acceleration, v, Represent the lateral motion velocity and acceleration, r, denote the yaw rate and angular acceleration respectively, I z is the yaw moment of inertia, F xi,j represents the longitudinal reaction force of wheel i, j on the road surface, F yi,j represents the lateral reaction force of vehicle i,j on the road surface, i,j=1,1,1,2,2,1,2,2 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively;

[0014] The port AGV single-track steering model is established, and its expression is:

[0015]

[0016] In the formula, α f , α r Represent the front wheel slip angle and rear wheel slip angle respectively, F yf 、F yr represent the front wheel lateral force and the rear wheel lateral force respectively, δ f Indicates the front wheel steering angle, L f , L r Indicates the cornering stiffness of the front and rear wheels;

[0017] The port AGV monorail model is:

[0018]

[0019] In the formula, represents the first derivative of the sideslip angle β at the center of mass;

[0020] Combining the port AGV vehicle steering model and the single-track steering model, the relationship between the steering angle of each wheel and the front wheel steering angle is derived as follows:

[0021]

[0022] In the formula, δ f Indicates the front wheel steering angle;

[0023] According to the port AGV monorail model, the position of the port AGV in the geodetic coordinate system is:

[0024]

[0025] Among them, V represents the actual speed of the port AGV, represents the first-order derivative of the heading angle ψ, Respectively represent the first-order derivatives of the abscissa X and ordinate Y of the geodetic coordinate system, δ r Indicates the rear wheel steering angle;

[0026] The position of the port AGV in the geodetic coordinate system is converted into the system state space equation of formula (7):

[0027]

[0028] In the formula, u M =[δ f ] represents the front wheel steering angle matrix, Represents the state quantity H = (ψ, X, Y) T The first-order derivative of , T represents the matrix transpose;

[0029] The MPC controller converts the steering angle control problem of each wheel of the port AGV into an optimization problem, and the objective function is:

[0030]

[0031] Among them, H(t) is the state of the port AGV at time t, u M (t-1) is the front wheel steering angle matrix at time t-1, ΔU(t) is the increment of the front wheel steering angle matrix at time t, τ(t+n|t) is the output of the MPC controller, τ r (t+n|t) is the reference path, Δu(t+n|t) is the control increment, n is the time step, ε is the relaxation factor, θ is the weight coefficient, A and B are both weight matrices, N p 、N c Represent the prediction time domain and the control time domain respectively;

[0032] In each control cycle, the total error of the port AGV position and each wheel steering angle is minimized, and the optimization problem is described as:

[0033]

[0034] Taking the wheel slip angle constraint as a hard constraint, we have:

[0035] α t,min ≤αf,α r ≤α t,max (14)

[0036] Among them, α t,min , α t,max Respectively represent the minimum and maximum values ​​of the wheel slip angle;

[0037] Taking the lateral acceleration constraint as a soft constraint, we have:

[0038]

[0039] Among them, μ represents the road adhesion coefficient, g represents the acceleration of gravity;

[0040] The PI speed controller takes the expected speed and actual speed of the port AGV as input, solves the expected speed and actual speed, and calculates the total longitudinal torque T required for the port AGV to travel according to formula (16): V ;

[0041] T V =K u (K p e V +K i ∫e V dt) (16)

[0042] In the formula, e V =V d -V represents the speed following error, V d represents the expected speed of the port AGV, K u Indicates the speed coefficient, K p , K i All are PI control parameters;

[0043] 2. If Figure 7 As shown in the figure, the port AGV single track model inputs the desired yaw rate and center of mass sideslip angle, controls the yaw rate and center of mass sideslip angle through the yaw rate sliding mode controller and the center of mass sideslip angle sliding mode controller respectively, and outputs the yaw rate additional yaw moment ΔM z1 and the additional yaw moment ΔM of the sideslip angle at the center of mass z2 , and then according to the joint coefficient allocation strategy, ΔM z1 , ΔM z2 Distribute and obtain the optimal additional yaw moment ΔM z ;

[0044] When the port AGV is in a stable state, the first-order derivative of the center of mass sideslip angle β and yaw angular acceleration are all 0, and substituting them into equation (4), we get the desired yaw angular velocity r d and the desired sideslip angle β d for:

[0045]

[0046] in, represents the stability factor;

[0047] In order to maintain the following ability of yaw angular velocity, the yaw angular velocity additional yaw moment ΔM is added to the port AGV monorail model of equation (4): z1 , then the yaw angular acceleration satisfies equation (18);

[0048]

[0049] Assume that the yaw rate following error is e r , then:

[0050] e r =rr d (19)

[0051] Yaw angular velocity following error e r The first-order derivative of is:

[0052]

[0053] Select the constant velocity reaching law and define the sliding surface s of the yaw rate sliding mode controller r for:

[0054]

[0055] In the formula, c r represents the weight coefficient;

[0056] The sliding surface s of the yaw rate sliding mode controller r The first-order derivative of is:

[0057]

[0058] According to equations (18) to (22), the yaw rate additional yaw moment ΔM is derived z1 for:

[0059]

[0060] Among them, K ω is the approach speed, sgn(·) represents the step function, represents the desired yaw rate r d The second derivative of

[0061] In order to suppress the buffeting phenomenon, the saturation function sat(·) is used to replace the step function sgn(·) in equation (23), then the yaw angular velocity is added with the yaw moment ΔM z1 for:

[0062]

[0063] In order to maintain the following ability of the mass center side slip angle, the additional yaw moment ΔM of the mass center side slip angle is added to the port AGV monorail model of formula (4): z2 , then the first-order derivative of the center of mass sideslip angle β satisfies equation (25);

[0064]

[0065] Assume that the center of mass sideslip angle following error is e β , then:

[0066] e β =β-β d (26)

[0067] Center of mass sideslip angle following error e β The first-order derivative of is:

[0068]

[0069] Select the constant velocity approach law and define the sliding surface s of the sliding mode controller for the sideslip angle of the center of massβ for:

[0070]

[0071] Among them, c β represents the weight coefficient;

[0072] The sliding surface s of the sliding mode controller for the sideslip angle of the center of mass β The first-order derivative of is:

[0073]

[0074] According to equations (25)-(29), the additional yaw moment ΔM due to the sideslip angle of the center of mass is derived: z2 for:

[0075]

[0076] In order to suppress the buffeting phenomenon, the saturation sat(·) is used to replace the step function sgn(·) in equation (30), and the additional yaw moment ΔM of the sideslip angle of the center of mass is obtained. z2 for:

[0077]

[0078] The yaw moment ΔM is added to the yaw rate by the joint coefficient allocation strategy z1 and the additional yaw moment ΔM of the sideslip angle at the center of mass z2 The optimal additional yaw moment ΔM is calculated by equation (32): z ;

[0079] ΔM z =(1-p)ΔM z1 +pΔM z2 (32)

[0080] Where p represents the joint distribution coefficient;

[0081] The joint coefficient allocation strategy is:

[0082]

[0083] In the formula, B1 and B2 represent the lower and upper limits of the stability boundary of the port AGV respectively;

[0084] 3. The total longitudinal torque T required for port AGV to travel V and the optimal additional yaw moment ΔM z As the input of the fault-tolerant allocation controller, the fault-tolerant allocation controller drives the allocated wheel drive torque motor driver, and the motor driver controls the corresponding port AGV wheel motor to rotate, so that the port AGV can run normally;

[0085] The road adhesion utilization rate J is selected to characterize the driving stability of port AGV. η is the objective function, and its expression is:

[0086]

[0087] Among them, D i,j represents the adhesion margin coefficient of wheel i, j, F zi,j represents the vertical load on wheels i, j;

[0088] In order to avoid danger to the port AGV, it is necessary to keep the road adhesion utilization rate of the port AGV as low as possible. At the same time, since the motor cannot provide lateral force, F yi,j =0, so the objective function of formula (34) is transformed into the optimization function of formula (35);

[0089]

[0090] The optimal additional yaw moment satisfies the constraint condition of formula (36);

[0091]

[0092] Among them, T x1,1 、T x1,2 、T x2,1 、T x2,2 Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel driving torque, r ω Indicates the wheel rolling radius;

[0093] When a single wheel motor fails, the wheel motor will no longer generate the required longitudinal driving force, so the torque of the remaining wheel motors needs to be redistributed to ensure the normal operation of the port AGV. When the left front wheel fails, the driving torque of the left front wheel is zero, and the total longitudinal torque T required for the port AGV to operate is V and the optimal additional yaw moment ΔM z Satisfy the following formula:

[0094]

[0095] Substituting formula (37) into formula (35), we get:

[0096]

[0097] Solve the objective function and then calculate the right rear wheel drive torque T according to equation (39): x2,2 Taking partial derivative, we get the right rear wheel driving torque T of equation (40): x2,2 ;

[0098]

[0099]

[0100] Similarly, the driving torques of the right front wheel and the left rear wheel are obtained as follows:

[0101]

[0102]

[0103] Compared with the prior art, the present invention has the following beneficial effects:

[0104] In view of the port environment characteristics and the working nature of the port AGV, the present invention proposes a hierarchical fault-tolerant control method for the port AGV, establishes the steering and dynamics model of the port AGV vehicle, and provides a reliable model basis for the control research of the port AGV. The control system is divided into upper, middle and lower control modules. The upper control module obtains the steering angle of each wheel based on the reference trajectory and the port AGV state quantity, and outputs the total longitudinal torque required for the port AGV to travel based on the expected speed and the actual speed. The upper control module is used to maintain the running trajectory; the middle control module designs two sliding mode controllers based on the sliding mode control method to maintain the following ability of the yaw angular velocity and the sideslip angle of the center of mass, and obtains the optimal additional yaw torque through the joint coefficient allocation strategy; the lower control module coordinates and distributes the driving torque of the remaining motors after the motor fails, ensuring that the port AGV can still travel normally in the case of motor failure, improving the path tracking ability and vehicle body stability of the port AGV, and ensuring the working efficiency and safety of the port AGV. BRIEF DESCRIPTION OF THE DRAWINGS

[0105] Figure 1 This is the structural diagram of the port AGV fault-tolerant control system;

[0106] Figure 2 This is a schematic diagram of the steering model of the port AGV;

[0107] Figure 3 This is a schematic diagram of the dynamics model of the port AGV vehicle;

[0108] Figure 4 This is a schematic diagram of the port AGV single-track steering model;

[0109] Figure 5 It is the flow chart of MPC control module;

[0110] Figure 6 It is the flow chart of PI speed controller;

[0111] Figure 7 It is the flow chart of the middle-level control module;

[0112] Figure 8 It is the flow chart of the lower control module. DETAILED DESCRIPTION

[0113] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and specific implementation methods, but the protection scope of the present application is not limited thereto.

[0114] Figure 1 The structure diagram of the port AGV fault-tolerant control system is shown in FIG. The system includes an upper control module, a middle control module, a lower control module and an execution module. The upper control module includes an MPC controller and a PI speed controller. The MPC controller obtains the front wheel steering angle based on the reference trajectory and the port AGV state quantity according to the port AGV monorail model, and then calculates the steering angle of each wheel according to the port AGV monorail steering model, and transmits it to the port AGV monorail model to calculate the position of the port AGV in the geodetic coordinate system, thereby performing real-time regulation and closed-loop feedback control on the steering angle of each wheel. The PI speed controller outputs the total longitudinal torque required for the port AGV to travel according to the expected speed and the actual speed. The middle controller module designs the yaw angular velocity based on the sliding mode control theory. The sliding mode controller and the center of mass sideslip angle sliding mode controller, the yaw angular velocity sliding mode controller outputs the yaw angular velocity additional yaw moment according to the actual value and expected value of the yaw angular velocity, the center of mass sideslip angle sliding mode controller outputs the center of mass sideslip angle additional yaw moment according to the actual value and expected value of the center of mass sideslip angle, and then calculates the optimal additional yaw moment through the failure allocation strategy; the lower control module includes a fault-tolerant control distributor. When a wheel motor fails, the fault-tolerant control distributor redistributes the driving torques of the remaining wheels according to the total longitudinal torque and the optimal additional yaw moment required for the port AGV to travel, so that the remaining wheel motors rotate, forming a closed-loop control to ensure the normal travel of the port AGV; the execution module includes a left front wheel motor, a right front wheel motor, a left rear wheel motor and a right rear wheel motor.

[0115] The present invention is a hierarchical fault-tolerant control method for a four-wheel independent electric drive port AGV, including the following contents:

[0116] 1. Establish the steering model and dynamic model of the port AGV vehicle, such as Figure 2 , 3 As shown; Based on the Ackerman steering theorem, the geometric relationship of the steering angles of each wheel is obtained as follows:

[0117]

[0118] In the formula, δ 1,1 ,δ 1,2 ,δ 2,1 ,δ 2,2They represent the left front wheel steering angle, the right front wheel steering angle, the left rear wheel steering angle and the right rear wheel steering angle respectively, G1=a+Rsinβ represents the longitudinal distance between the geometric center of the left front wheel or the right front wheel and the steering center o1, G2=b-Rsinβ represents the longitudinal distance between the geometric center of the left rear wheel or the right rear wheel and the steering center o1, It represents the lateral distance between the geometric center of the left front wheel or the left rear wheel and the steering center. The length direction of the port AGV is the longitudinal direction, and the width direction of the port AGV is the lateral direction. a and b are the distances from the front axle and the rear axle to the center of mass o of the port AGV, respectively. β is the sideslip angle of the center of mass. R is the distance from the steering center o1 to the center of mass o of the port AGV. l is the coaxial wheelbase.

[0119] The movement of the port AGV mainly includes the roll movement around the x-axis, the lateral movement along the y-axis and the yaw movement around the z-axis. The dynamic model of the port AGV is:

[0120]

[0121] in, is the longitudinal torque, represents the lateral torque, represents the yaw torque, M represents the full load mass, u, Respectively represent the longitudinal velocity and acceleration, v, Represent the lateral motion velocity and acceleration, r, denote the yaw rate and angular acceleration respectively, I z is the yaw moment of inertia, F xi,j represents the longitudinal reaction force of wheel i, j on the road surface, F yi,j represents the lateral reaction force of vehicle i,j on the road surface, i,j=1,1,1,2,2,1,2,2 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively;

[0122] The tracking path of the port AGV is regarded as a point on the vehicle body tracking a point on the reference trajectory, so the following can be established: Figure 4 The port AGV single-track steering model shown is expressed as:

[0123]

[0124] In the formula, α f , α r Represent the front wheel slip angle and rear wheel slip angle respectively, F yf 、F yr represent the front wheel lateral force and the rear wheel lateral force respectively, δ f Indicates the front wheel steering angle, L f , L r Indicates the cornering stiffness of the front and rear wheels;

[0125] Substituting formula (3) into formula (2) and sorting it out, the expression of the port AGV monorail model is obtained as follows:

[0126]

[0127] In the formula, represents the first derivative of the sideslip angle β at the center of mass;

[0128] Combined with the port AGV vehicle steering model and the single track steering model, the steering angle of each wheel and the front wheel steering angle δ are derived. f The relationship between them is:

[0129]

[0130] According to the port AGV monorail model, the position of the port AGV in the geodetic coordinate system is:

[0131]

[0132] Among them, V represents the actual speed of the port AGV, represents the first-order derivative of the heading angle ψ, Respectively represent the first-order derivatives of the abscissa X and ordinate Y of the geodetic coordinate system, δ r Indicates the rear wheel steering angle;

[0133] The position of the port AGV in the geodetic coordinate system is converted into the system state space equation of formula (7):

[0134]

[0135] In the formula, u M =[δ f ] represents the front wheel steering angle matrix, Represents the state quantity H = (ψ, X, Y) T The first-order derivative of , T represents the matrix transpose;

[0136] Since the established dynamic model is nonlinear, the amount of calculation required to predict the future state of the port AGV using the nonlinear model is large, which will lead to poor real-time performance of the controller involved. Therefore, the system state space equation is linearized to obtain the time-varying equation:

[0137]

[0138] in, C=

[010] T , t represents the time variable, y represents the output of the MPC controller after linearization;

[0139] In order to simplify the model and speed up the solution, the time-varying equation is discretized. The discretization process uses the first-order pre-difference quotient method and writes the incremental form, then the time-varying equation is discretized into:

[0140]

[0141] Where k represents the control increment, and y(k) represents the output of the MPC controller after discretization;

[0142] In order to accurately constrain the control increment, a new state variable ζ(k|t) = [H(k|t) u M (k-1|t)] T , transforming the system state space equation into:

[0143]

[0144] in, E represents the identity matrix, τ(k|t) represents the output of the MPC controller after the introduction of the new state quantity;

[0145] At this time, the output of the MPC controller can be expressed as:

[0146] Y M (k)=Fζ(k)+IΔU(k) ​​(11)

[0147] Where Y M (k)=[τ(k+1|k) τ(k+2|k)…τ(k+N p |k)] T

[0148] ΔU(k)=[Δu M (k) Δu M (k+1)…Δu M (k+N c -1)] T

[0149]

[0150]

[0151] Among them, N p 、N c Represent the prediction time domain and the control time domain respectively;

[0152] The output of the MPC controller is solved, that is, the steering angle control problem of each wheel of the port AGV is converted into the objective function form of the optimization problem. Based on the complexity of the kinematics of the port AGV, a relaxation factor needs to be added to the objective function to reduce the difference between the calculation results of each layer and avoid the divergence of the calculation results. The objective function is:

[0153]

[0154] Among them, H(t) is the state of the port AGV at time t, u M (t-1) is the front wheel steering angle matrix at time t-1, ΔU(t) is the increment of the front wheel steering angle matrix at time t, τ(t+n|t) is the output of the MPC controller, τ r (t+n|t) is the reference path, Δu(t+n|t) is the control increment, n is the time step, ε is the relaxation factor, θ is the weight coefficient, and A and B are both weight matrices;

[0155] In each control cycle, the total error of the port AGV position and each wheel steering angle is minimized, and the optimization problem is described as:

[0156]

[0157] Taking the wheel slip angle constraint as a hard constraint, we have:

[0158] α t,min ≤α f , α r ≤α t,max (14)

[0159] Among them, α t,min , α t,max Respectively represent the minimum and maximum values ​​of the wheel slip angle;

[0160] Taking the lateral acceleration constraint as a soft constraint, we have:

[0161]

[0162] Among them, μ represents the road adhesion coefficient, g represents the acceleration of gravity;

[0163] like Figure 6 As shown in the figure, the PI speed controller takes the expected speed and actual speed of the port AGV as input, solves the expected speed and actual speed, and calculates the total longitudinal torque T required for the port AGV to travel according to formula (16): V ;

[0164] T V =K u (K p eV+K i ∫eVdt) (16)

[0165] In the formula, e V =V d -V represents the speed following error, V d represents the expected speed of the port AGV, K uIndicates the speed coefficient, K p , K i All are PI control parameters;

[0166] 2. If Figure 7 As shown in the figure, the port AGV single track model inputs the desired yaw rate and center of mass sideslip angle, controls the yaw rate and center of mass sideslip angle through the yaw rate sliding mode controller and the center of mass sideslip angle sliding mode controller respectively, and outputs the yaw rate additional yaw moment ΔM z1 and the additional yaw moment ΔM of the sideslip angle at the center of mass z2 , and then according to the joint coefficient allocation strategy, ΔM z1 , ΔM z2 Distribute and obtain the optimal additional yaw moment ΔM z ; Finally, the port AGV vehicle dynamics model outputs the actual yaw rate and center of mass sideslip angle to the two sliding mode controllers in real time, so that the entire system can achieve closed-loop control;

[0167] When the port AGV is in a stable state, the first-order derivative of the center of mass sideslip angle β and yaw angular acceleration are all 0, and substituting them into equation (4), we get the desired yaw angular velocity r d and the desired sideslip angle β d for:

[0168]

[0169] in, represents the stability factor;

[0170] In order to maintain the following ability of yaw angular velocity, the yaw angular velocity additional yaw moment ΔM is added to the port AGV monorail model of equation (4): z1 , then the yaw angular acceleration satisfies equation (18);

[0171]

[0172] Assume that the yaw rate following error is e r , then:

[0173] e r =rr d (19)

[0174] Yaw angular velocity following error e r The first-order derivative of is:

[0175]

[0176] Select the constant velocity reaching law and define the sliding surface s of the yaw rate sliding mode controller r for:

[0177]

[0178] In the formula, c r represents the weight coefficient;

[0179] The sliding surface s of the yaw rate sliding mode controller r The first-order derivative of is:

[0180]

[0181] According to equations (18) to (22), the yaw rate additional yaw moment ΔM is derived z1 for:

[0182]

[0183] Among them, K ω is the approach speed, sgn(·) represents the step function, represents the desired yaw rate r d The second derivative of

[0184] In order to suppress the buffeting phenomenon, the saturation function sat(·) is used to replace the step function sgn(·) in equation (23), then the yaw angular velocity is added with the yaw moment ΔM z1 for:

[0185]

[0186] In order to maintain the following ability of the mass center side slip angle, the additional yaw moment ΔM of the mass center side slip angle is added to the port AGV monorail model of formula (4): z2 , then the first-order derivative of the center of mass sideslip angle β satisfies equation (25);

[0187]

[0188] Assume that the center of mass sideslip angle following error is e β , then:

[0189] e β =β-β d (26)

[0190] Center of mass sideslip angle following error e β The first-order derivative of is:

[0191]

[0192] Select the constant velocity approach law and define the sliding surface s of the sliding mode controller for the sideslip angle of the center of mass β for:

[0193]

[0194] Among them, c β represents the weight coefficient;

[0195] The sliding surface s of the sliding mode controller for the sideslip angle of the center of mass β The first-order derivative of is:

[0196]

[0197] According to equations (25)-(29), the additional yaw moment ΔM due to the sideslip angle of the center of mass is derived: z2 for:

[0198]

[0199] The yaw moment ΔM is added to the yaw rate by the joint coefficient allocation strategy z1 and the additional yaw moment ΔM of the sideslip angle at the center of mass z2 The optimal additional yaw moment ΔM is calculated by equation (32): z ;

[0200] ΔM z =(1-p)ΔM z1 +pΔM z2 (32)

[0201] Where p represents the joint distribution coefficient;

[0202] The joint coefficient allocation strategy is:

[0203]

[0204] In the formula, B1 and B2 represent the lower and upper limits of the stability boundary of the port AGV respectively;

[0205] 3. Figure 8 As shown in the figure, the lower control module includes a fault-tolerant distribution controller, which converts the total longitudinal torque T required for the port AGV to travel V and the optimal additional yaw moment ΔM z As the input of the fault-tolerant allocation controller, the fault-tolerant allocation controller drives the allocated wheel drive torque motor driver, and the motor driver controls the corresponding port AGV wheel motor to rotate, so that the port AGV can run normally;

[0206] The road adhesion utilization rate J is selected to characterize the driving stability of port AGV. η is the objective function, and its expression is:

[0207]

[0208] Among them, D i,j represents the adhesion margin coefficient of wheel i, j, Fzi,j represents the vertical load on wheels i, j;

[0209] In order to avoid danger to the port AGV, it is necessary to keep the road adhesion utilization rate of the port AGV as low as possible. At the same time, since the motor cannot provide lateral force, F yi,j =0, so the objective function of formula (34) is transformed into the optimization function of formula (35);

[0210]

[0211] It can be seen from formula (33) that the designed objective function controls the tire force of the wheel and increases the tire force of other wheels for compensation, thereby ensuring the road adhesion utilization rate of the whole vehicle;

[0212] Under the conditions of satisfying the total longitudinal torque and the optimal additional yaw torque, each wheel needs to consider the motor output limitation and the port road surface limitation, so the optimal additional yaw torque satisfies the constraint condition of formula (36);

[0213]

[0214] Among them, T x1,1 、T x1,2 、T x2,1 、T x2,2 Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel driving torque, r ω Indicates the wheel rolling radius;

[0215] When a single wheel motor fails, the wheel motor will no longer generate the required longitudinal driving force, so the torque of the remaining wheel motors needs to be redistributed to ensure the normal operation of the port AGV. For example, when the left front wheel fails, the driving torque of the left front wheel is zero, and the total longitudinal torque T required for the port AGV to operate is V and the optimal additional yaw moment ΔM z Satisfy the following formula:

[0216]

[0217] Substituting formula (37) into formula (35), we get:

[0218]

[0219] The extreme value method is used to solve the objective function, and then the right rear wheel driving torque T is calculated according to formula (39): x2,2 Taking partial derivative, we get the right rear wheel driving torque T of equation (40): x2,2 ;

[0220]

[0221]

[0222] Similarly, the driving torques of the right front wheel and the left rear wheel are obtained as follows:

[0223]

[0224]

[0225] Any matters not described in the present invention are applicable to the prior art.

Claims

1. A hierarchical fault-tolerant control method for a four-wheel independent electric drive port AGV, the control system used includes an upper control module, a middle control module, a lower control module and an execution module, the upper control module includes an MPC controller and a PI speed controller, the middle controller module includes a yaw angular velocity sliding mode controller and a center of mass sideslip angle sliding mode controller, the lower control module includes a fault-tolerant control distributor, and the execution module includes a left front wheel motor, a right front wheel motor, a left rear wheel motor and a right rear wheel motor; characterized in that, The method includes the following:

1. Establish the steering model and dynamic model of the port AGV vehicle. The steering model of the port AGV vehicle is: In the formula, δ 1,1 , δ 1,2 , δ 2,1 , δ 2,2 They represent the left front wheel steering angle, the right front wheel steering angle, the left rear wheel steering angle and the right rear wheel steering angle respectively, G1=a+Rsinβ represents the longitudinal distance between the geometric center of the left front wheel or the right front wheel and the steering center, G2=b-Rsinβ represents the longitudinal distance between the geometric center of the left rear wheel or the right rear wheel and the steering center, It represents the lateral distance between the geometric center of the left front wheel or the left rear wheel and the steering center. The length direction of the port AGV is the longitudinal direction, and the width direction of the port AGV is the lateral direction. a and b are the distances from the front axle and the rear axle to the center of mass of the port AGV, respectively. β is the sideslip angle of the center of mass. R is the distance from the steering center to the center of mass of the port AGV. l is the coaxial wheelbase. The dynamic model of the port AGV vehicle is: in, represents the longitudinal torque, represents the lateral torque, represents the yaw torque, M represents the full load mass, u, Respectively represent the longitudinal velocity and acceleration, v, Represent the lateral motion velocity and acceleration, r, denote the yaw rate and angular acceleration respectively, I z is the yaw moment of inertia, F xi,j represents the longitudinal reaction force of wheel i, j on the road surface, F yi,j represents the lateral reaction force of vehicle i,j on the road surface, i,j=1,1,1,2,2,1,2,2 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; The port AGV single-track steering model is established, and its expression is: In the formula, α f , α r Represent the front wheel slip angle and rear wheel slip angle respectively, F yf 、F yr represent the front wheel lateral force and the rear wheel lateral force respectively, δ f Indicates the front wheel steering angle, L f , L r Indicates the cornering stiffness of the front and rear wheels; The port AGV monorail model is: In the formula, represents the first derivative of the sideslip angle β at the center of mass; Combining the port AGV vehicle steering model and the single-track steering model, the relationship between the steering angle of each wheel and the front wheel steering angle is derived as follows: In the formula, δ f Indicates the front wheel steering angle; According to the port AGV monorail model, the position of the port AGV in the geodetic coordinate system is: Among them, V represents the actual speed of the port AGV, represents the first-order derivative of the heading angle ψ, Respectively represent the first-order derivatives of the abscissa X and ordinate Y of the geodetic coordinate system, δ r Indicates the rear wheel steering angle; The position of the port AGV in the geodetic coordinate system is converted into the system state space equation of formula (7): In the formula, u M =[δ f ] represents the front wheel steering angle matrix, Represents the state quantity H = (ψ, X, Y) T The first-order derivative of , T represents the matrix transpose; The MPC controller converts the steering angle control problem of each wheel of the port AGV into an optimization problem, and the objective function is: Among them, H(t) is the state of the port AGV at time t, u M (t-1) is the front wheel steering angle matrix at time t-1, ΔU(t) is the increment of the front wheel steering angle matrix at time t, τ(t+n|t) is the output of the MPC controller, τ r (t+n|t) is the reference path, Δu(t+n|t) is the control increment, n is the time step, ε is the relaxation factor, θ is the weight coefficient, A and B are both weight matrices, N p 、N c Represent the prediction time domain and the control time domain respectively; In each control cycle, the total error of the port AGV position and each wheel steering angle is minimized, and the optimization problem is described as: Taking the wheel slip angle constraint as a hard constraint, we have: α t,min ≤α f ，α r ≤α t,max (14) Among them, α t,min , α t,max Respectively represent the minimum and maximum values ​​of the wheel slip angle; Taking the lateral acceleration constraint as a soft constraint, we have: Among them, μ represents the road adhesion coefficient, g represents the acceleration of gravity; The PI speed controller takes the expected speed and actual speed of the port AGV as input, solves the expected speed and actual speed, and calculates the total longitudinal torque T required for the port AGV to travel according to formula (16): V ; T V =K u (K p e V +K i ∫e V dt) (16) In the formula, e V =V d -V represents the speed following error, V d represents the expected speed of the port AGV, K u Indicates the speed coefficient, K p , K i All are PI control parameters; 2. The port AGV monorail model inputs the desired yaw rate and center of mass sideslip angle, controls the yaw rate and center of mass sideslip angle through the yaw rate sliding mode controller and the center of mass sideslip angle sliding mode controller respectively, and outputs the yaw rate additional yaw moment ΔM z1 and the additional yaw moment ΔM of the sideslip angle at the center of mass z2 , and then according to the joint coefficient allocation strategy, ΔM z1 , ΔM z2 Distribute and obtain the optimal additional yaw moment ΔM z ; When the port AGV is in a stable state, the first-order derivative of the center of mass sideslip angle β and yaw angular acceleration are all 0, and substituting them into equation (4), we get the desired yaw angular velocity r d and the desired sideslip angle β d for: in, represents the stability factor; In order to maintain the following ability of yaw angular velocity, the yaw angular velocity additional yaw moment ΔM is added to the port AGV monorail model of equation (4): z1 , then the yaw angular acceleration satisfies equation (18); Assume that the yaw rate following error is e r , then: e r ＝r-r d (19) Yaw angular velocity following error e r The first-order derivative of is: Select the constant velocity reaching law and define the sliding surface s of the yaw rate sliding mode controller r for: In the formula, c r represents the weight coefficient; The sliding surface s of the yaw rate sliding mode controller r The first-order derivative of is: According to equations (18) to (22), the yaw rate additional yaw moment ΔM is derived z1 for: Among them, K ω is the approach speed, sgn(·) represents the step function, represents the desired yaw rate r d The second derivative of In order to suppress the buffeting phenomenon, the saturation function sat(·) is used to replace the step function sgn(·) in equation (23), then the yaw angular velocity is added with the yaw moment ΔM z1 for: In order to maintain the following ability of the sideslip angle of the center of mass, the additional yaw moment ΔM of the sideslip angle of the center of mass is added to the port AGV monorail model of formula (4): z2 , then the first-order derivative of the center of mass sideslip angle β satisfies equation (25); Assume that the center of mass sideslip angle following error is e β , then: e β ＝β-β d (26) Center of mass sideslip angle following error e β The first-order derivative of is: Select the constant velocity approach law and define the sliding surface s of the sliding mode controller for the sideslip angle of the center of mass β for: Among them, c β represents the weight coefficient; The sliding surface s of the sliding mode controller for the sideslip angle of the center of mass β The first-order derivative of is: According to equations (25)-(29), the additional yaw moment ΔM due to the sideslip angle at the center of mass is derived: z2 for: In order to suppress the buffeting phenomenon, the saturation sat(·) is used to replace the step function sgn(·) in equation (30), and the additional yaw moment ΔM of the sideslip angle of the center of mass is obtained. z2 for: The yaw moment ΔM is added to the yaw rate by the joint coefficient allocation strategy z1 and the additional yaw moment ΔM of the sideslip angle at the center of mass z2 The optimal additional yaw moment ΔM is calculated by equation (32): z ; ΔM z =(1-p)ΔM z1 +pΔM z2 (32) Where p represents the joint distribution coefficient; The joint coefficient allocation strategy is: In the formula, B1 and B2 represent the lower and upper limits of the stability boundary of the port AGV respectively; 3. The total longitudinal torque T required for port AGV to travel V and the optimal additional yaw moment ΔM z As the input of the fault-tolerant allocation controller, the fault-tolerant allocation controller drives the allocated wheel drive torque motor driver, and the motor driver controls the corresponding port AGV wheel motor to rotate, so that the port AGV can run normally; The road adhesion utilization rate J is selected to characterize the driving stability of port AGV. η is the objective function, and its expression is: Among them, D i,j represents the adhesion margin coefficient of wheel i, j, F zi,j represents the vertical load on wheels i, j; In order to avoid danger to the port AGV, it is necessary to keep the road adhesion utilization rate of the port AGV as low as possible. At the same time, since the motor cannot provide lateral force, F yi,j =0, so the objective function of formula (34) is transformed into the optimization function of formula (35); The optimal additional yaw moment satisfies the constraint condition of formula (36); Among them, T x1,1 , T x1,2 , T x2,1 , T x2,2 Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel driving torque, r ω Indicates the wheel rolling radius; When a single wheel motor fails, the wheel motor will no longer generate the required longitudinal driving force, so the torque of the remaining wheel motors needs to be redistributed to ensure the normal operation of the port AGV. When the left front wheel fails, the driving torque of the left front wheel is zero, and the total longitudinal torque T required for the port AGV to operate is V and the optimal additional yaw moment ΔM z Satisfy the following formula: Substituting formula (37) into formula (35), we get: Solve the objective function and then calculate the right rear wheel drive torque T according to equation (39): x2,2 Taking partial derivative, we get the right rear wheel driving torque T of equation (40): x2,2 ; Similarly, the driving torques of the right front wheel and the left rear wheel are obtained as follows:

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