Loader safety boundary adaptive sliding mode path tracking control method

Abstract

The invention provides a loader safety boundary adaptive sliding mode path tracking control method. The method comprises the following steps: setting related parameters; reading rotating speed numerical values of a hinge angle sensor and each hub motor, and reading front vehicle body positioning information and longitudinal acceleration of the loading machine, which are acquired by the laser radar in real time; according to loader front vehicle body positioning information collected by a laser radar in real time, a vehicle driving path is planned according to a starting point, and planned path point location information and vehicle longitudinal acceleration are transmitted to an electronic control unit; calculating the vehicle speed according to the rotating speed of each hub motor; estimating the mass m of the whole loader according to the longitudinal acceleration and the speed; sliding mode path tracking control based on safety boundary self-adaption is carried out according to m; and judging whether the sliding mode path arrives at the final position or not, if so, ending the path tracking operation, and otherwise, continuing the sliding mode path tracking control based on safety boundary self-adaption. According to the method, accurate and automatic operation of real-time path tracking of the loader can be realized, and the active safety performance of the vehicle is improved.

Description

Technical Field

[0001] The invention relates to the technical field of loader control, and in particular to a loader safety boundary adaptive sliding mode path tracking control method based on vehicle mass estimation. Background Art

[0002] A loader is a kind of earthwork construction machinery widely used in construction projects such as roads, railways, buildings, hydropower, ports, and mines. It is mainly used to shovel and load bulk materials such as soil, sand, lime, coal, etc. It can also do light shoveling and digging of ore, hard soil, etc. By replacing different auxiliary working devices, it can also carry out bulldozing, lifting, and loading and unloading of other materials such as wood. Loaders have the advantages of high efficiency, reliability, and strong adaptability, and are an important force in engineering construction. Loaders are an important force in engineering construction because they have the advantages of high efficiency, reliability, and strong adaptability. Loaders mostly operate on unstructured terrain, and the operation time is long and repetitive. Drivers are prone to fatigue, which not only reduces work efficiency, but also easily leads to safety accidents. Therefore, accelerating the unmanned process of loaders has become a crucial issue at present.

[0003] Due to the special articulated steering mechanism and complex working environment of the loader, it is not suitable for the path tracking system of a two-axle single vehicle. In addition, it is difficult to install load sensors under the working conditions of the loader with variable loads. Therefore, it is necessary to estimate the vehicle mass of the loader and apply it to the path tracking system of the loader, so that it can perform the working tasks safely, stably and autonomously, and improve the reliability and stability of the vehicle. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a loader safety boundary adaptive sliding mode path tracking control method to achieve safe, stable and precise automated control of the transfer machine.

[0005] The present invention is implemented as follows: a loader safety boundary adaptive sliding mode path tracking control method, which requires the construction of a hardware system, the hardware system comprising: a host computer, an electronic control unit, a laser radar, an articulation angle sensor, a front body left motor controller, a front body right motor controller, a rear body left motor controller, a rear body right motor controller, a front body left wheel hub motor, a front body right wheel hub motor, a rear body left wheel hub motor, and a rear body right wheel hub motor;

[0006] The host computer is connected to the laser radar and the electronic control unit respectively through circuits;

[0007] The electronic control unit is respectively connected to the articulation angle sensor, the front body left motor controller, the front body right motor controller, the rear body left motor controller, and the rear body right motor controller through a circuit;

[0008] The front body left motor controller, the front body right motor controller, the rear body left motor controller, and the rear body right motor controller are connected to the front body left wheel hub motor, the front body right wheel hub motor, the rear body left wheel hub motor, and the rear body right wheel hub motor through circuits in a one-to-one correspondence;

[0009] The wheel hub motors include a front body left wheel hub motor, a front body right wheel hub motor, a rear body left wheel hub motor and a rear body right wheel hub motor, which are respectively connected to their corresponding side wheels through a mechanical structure;

[0010] The articulation angle sensor is located at the articulation point of the front and rear bodies of the loader;

[0011] The laser radar is located above the cab of the rear body of the loader;

[0012] The method comprises the following steps:

[0013] Step S1: Setting the reference vehicle speed v in the electronic control unit ref , hinge angle safety boundary threshold θ safe , endpoint error threshold value e dth Related parameters:

[0014] Step S2: The electronic control unit reads the articulation angle sensor and the rotation speed values ​​of each wheel hub motor, and the host computer reads the front body positioning information x collected by the laser radar in real time. f ,y f , δ f and longitudinal acceleration a x ;

[0015] Step S3: The host computer plans the vehicle driving path according to the starting point based on the real-time positioning information of the front body of the loader collected by the laser radar, and sends the planned path point information x ref ,y ref , δ ref and the vehicle longitudinal acceleration a x Transmitted to the electronic control unit;

[0016] Step S4, the electronic control unit calculates the vehicle speed v according to the rotation speed of each wheel hub motor;

[0017] Step S5: The electronic control unit determines the longitudinal acceleration a x and the calculated vehicle speed v, to estimate the loader's vehicle mass m;

[0018] Step S6, the electronic control unit performs a sliding mode path tracking control based on safety margin adaptation according to the estimated vehicle mass m;

[0019] Step S7, the electronic control unit determines whether the vehicle has reached the destination according to the current location information and the destination location information of the vehicle. If so, the path tracking operation is terminated; otherwise, the process returns to step S6.

[0020] Furthermore, the calculation process of the vehicle speed v in step S4 is specifically as follows:

[0021]

[0022] Among them, w1, w2, w3, and w4 are the rotation speeds of the wheels corresponding to the left wheel hub motor of the front body, the right wheel hub motor of the front body, the left wheel hub motor of the rear body, and the right wheel hub motor of the rear body, respectively, R is the tire radius, g is the acceleration of gravity, and t is the braking time.

[0023] Furthermore, the estimation process of the loader vehicle mass m in step S5 is specifically as follows:

[0024] A longitudinal climbing model of the loader is established, and the recursive least squares method with a forgetting factor is used to estimate the vehicle mass m. The longitudinal climbing model of the loader ignores the rotating mass inertia resistance moment and the rolling resistance moment, that is:

[0025]

[0026] In the formula, F t is the driving force of the loader, F i is the road slope resistance, F w is the air resistance, F f is the rolling resistance, F a is the acceleration resistance of the loader; v x is the longitudinal speed of the vehicle; I δ is the rotation mass conversion factor; I wi is the moment of inertia of each wheel; T wi is the torque of each wheel hub motor; C D is the wind resistance coefficient; A is the frontal area of ​​the vehicle; ρ is the air density; f is the rolling resistance coefficient; σ s Road slope; δ f is the heading angle;

[0027] The rolling resistance coefficient f is converted into:

[0028] f=tanσ f

[0029] The vehicle longitudinal dynamics equation is transformed into:

[0030]

[0031] The recursive least squares method with forgetting factor is used to estimate the mass m of the loader. In the recursive least squares algorithm, the relationship between the measured value and the system parameters is as follows:

[0032]

[0033] Where Z(k) is the measured value; H(k) is the coefficient matrix; is the parameter to be estimated;

[0034] Then the least squares algorithm with forgetting factor is:

[0035]

[0036] Where, L1(k) and L2(k) are gain matrices respectively; P1(k) and P2(k) are covariance matrices respectively;

[0037] The forgetting factor λ f , s It is expressed as:

[0038]

[0039] In the formula, λ base1 , base2 are the basic forgetting factors respectively.

[0040] Furthermore, the step S6 specifically includes:

[0041] Step S61: Establish a kinematic model of the loader, assuming that the tires do not slip, that is:

[0042]

[0043] In the formula, v f is the longitudinal velocity of the front vehicle; v r is the longitudinal velocity of the rear vehicle body; L f L is the distance between the front wheel hub motor and the hinge point; r is the distance between the rear wheel hub motor and the hinge point; θ is the hinge angle; w f is the yaw angle of the front vehicle, i.e. the heading angle δ f ;w r is the rear vehicle body yaw angle, i.e. the heading angle δ r ;

[0044] Simplify the above formula, that is:

[0045]

[0046] Step S62: Establish a loader path tracking error model, namely:

[0047]

[0048] In the formula, x e is the x-direction error of the front vehicle; e is the y-direction error of the front vehicle body; e is the heading angle error of the front vehicle; d1, d2, d3 are disturbance terms;

[0049] Step S63, design of sliding surface, namely:

[0050] s=ξ1x e +ξ2y e +ξ3δ e +ξ4sat(θ-θ safe )

[0051] Where, ξ1 is the weight of the error in the x direction; ξ2 is the weight of the error in the y direction; ξ3 is the weight of the error in the heading angle; ξ4 is the trigger weight of the safety boundary of the articulation angle;

[0052] The saturation function sat(x) is in the form of:

[0053]

[0054] Step S64, deriving the sliding surface, we can obtain:

[0055]

[0056] Where, ξ1 is the weight of the error in the x direction; ξ2 is the weight of the error in the y direction; ξ3 is the weight of the error in the heading angle; ξ4 is the trigger weight of the safety boundary of the articulation angle;

[0057] Step S65: In order to ensure that the system can converge on the sliding surface, the control law needs to satisfy:

[0058]

[0059] Where k is a constant and k>0;

[0060] Step S66: Control the articulation angular velocity It can be solved as:

[0061]

[0062] Furthermore, the calculation process for determining whether the loader has reached the terminal position in step S7 is as follows:

[0063] First, calculate the end point distance error e d :

[0064]

[0065] In the formula, xs is the horizontal coordinate of the end point; s is the ordinate of the end point position;

[0066] Then, it is determined whether the end position has been reached, namely:

[0067]

[0068] Wherein, T means reaching the end position; F means not reaching the end position.

[0069] The present invention has the following advantages:

[0070] 1. In the hardware architecture of the loader, the present invention collects real-time data of the laser radar through the host computer (or industrial computer), collects real-time data of the articulation angle sensor through the electronic control unit (ECU), and controls the four wheel hub motors of the loader by the electronic control unit (ECU) to realize the real-time path tracking operation of the loader;

[0071] 2. By establishing a longitudinal climbing model of the loader based on the designed hardware architecture and using the recursive least squares method with forgetting factor, the loader vehicle mass is estimated, thereby improving the accuracy of path tracking control;

[0072] 3. Through the designed safety boundary-based adaptive sliding mode path tracking control system, the loader's articulation angular velocity is controlled, and it is ensured that the vehicle can operate within the designed safety steering boundary. While improving the vehicle tracking accuracy, it also improves the vehicle's active safety performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The present invention will be further described below in conjunction with embodiments with reference to the accompanying drawings.

[0074] Figure 1 A schematic diagram of the hardware architecture corresponding to a loader safety boundary adaptive sliding mode path tracking control method of the present invention.

[0075] Figure 2 The present invention is a flowchart of a loader safety boundary adaptive sliding mode path tracking control method.

[0076] Description of Figure Numbers:

[0077] 1. Host computer, 2. Electronic control unit, 3. LiDAR, 4. Articulation angle sensor, 5. Front body left motor controller, 6. Front body right motor controller, 7. Rear body left motor controller, 8. Rear body right motor controller, 9. Front body left wheel hub motor, 10. Front body right wheel hub motor, 11. Rear body left wheel hub motor, 12. Rear body right wheel hub motor. DETAILED DESCRIPTION

[0078] See also Figure 1 and Figure 2 As shown, a loader safety boundary adaptive sliding mode path tracking control method of the present invention requires the construction of a hardware system, which includes: a host computer 1, an electronic control unit (ECU) 2, a laser radar 3, an articulation angle sensor 4, a front body left motor controller 5, a front body right motor controller 6, a rear body left motor controller 7, a rear body right motor controller 8, a front body left wheel hub motor 9, a front body right wheel hub motor 10, a rear body left wheel hub motor 11, and a rear body right wheel hub motor 12;

[0079] The host computer 1 is connected to the laser radar 3 and the electronic control unit 2 through circuits;

[0080] The electronic control unit 2 is connected to the articulation angle sensor 4, the front body left motor controller 5, the front body right motor controller 6, the rear body left motor controller 7, and the rear body right motor controller 8 through circuits;

[0081] The front body left side motor controller 5 is connected to the front body left side wheel hub motor 9 through a circuit;

[0082] The front body right side motor controller 6 is connected to the front body right side wheel hub motor 10 through a circuit;

[0083] The rear body left side motor controller 7 is connected to the front body left side wheel hub motor 11 through a circuit;

[0084] The rear body right side motor controller 8 is connected to the front body right side wheel hub motor 12 through a circuit;

[0085] The wheel hub motors include a front body left wheel hub motor 9, a front body right wheel hub motor 10, a rear body left wheel hub motor 11 and a rear body right wheel hub motor 12, which are respectively connected to the wheels on their corresponding sides through mechanical structures;

[0086] The articulation angle sensor 4 is located at the articulation point of the front and rear bodies of the loader;

[0087] The laser radar 3 is located above the cab of the rear body of the loader.

[0088] The method comprises the following steps:

[0089] Step S1: Setting the reference vehicle speed v in the electronic control unit ref , hinge angle safety boundary threshold θ safe , endpoint error threshold value e dthThe preset parameters mentioned in this step are non-inherent structural parameters of the vehicle and are parameter values ​​set within the system. The parameters in the formula below are either intermediate quantities, inherent structural parameters of the vehicle, or parameters calculated or measured by sensors, not preset parameters.

[0090] Step S2: The electronic control unit reads the articulation angle sensor and the rotation speed values ​​of each wheel hub motor, and the host computer reads the front body positioning information x collected by the laser radar in real time. f ,y f , δ f and longitudinal acceleration a x ;

[0091] Step S3: The host computer plans the vehicle driving path according to the starting point based on the real-time positioning information of the front body of the loader collected by the laser radar, and sends the planned path point information x ref ,y ref , δ ref and the vehicle longitudinal acceleration a x Transmitted to the electronic control unit; The present invention is mainly based on the planned path for tracking control, the purpose is to minimize the error between the vehicle's driving path and the planned path, wherein the current position information of the vehicle can be known through the laser radar, and the parameters such as xf are the current coordinate information of the front vehicle body measured by the laser radar, including the horizontal coordinate, the vertical coordinate and the heading angle, and the path planning content is obtained through the path planning related algorithm planning inside the host computer;

[0092] Step S4, the electronic control unit calculates the vehicle speed v according to the rotation speed of each wheel hub motor;

[0093] Step S5: The electronic control unit determines the longitudinal acceleration a x and the calculated vehicle speed v, to estimate the loader mass m; the longitudinal acceleration a x That is, the least squares method estimates the velocity part v x The derivative of

[0094] Step S6, the electronic control unit performs a sliding mode path tracking control based on safety margin adaptation according to the estimated vehicle mass m;

[0095] Step S7, the electronic control unit determines whether the vehicle has reached the destination according to the current location information and the destination location information of the vehicle. If so, the path tracking operation is terminated; otherwise, the process returns to step S6.

[0096] Preferably, the calculation process of the vehicle speed v in step S4 is specifically as follows:

[0097]

[0098] Among them, w1, w2, w3, and w4 are the rotation speeds of the wheels corresponding to the left wheel hub motor of the front body, the right wheel hub motor of the front body, the left wheel hub motor of the rear body, and the right wheel hub motor of the rear body, respectively. The wheel speed here is equal to the motor speed because the wheel hub motor is connected to the tire and there is no transmission loss between the two. R is the tire radius, g is the acceleration of gravity, and t is the braking time.

[0099] Preferably, the estimation process of the loader vehicle mass m in step S5 is specifically as follows:

[0100] A longitudinal climbing model of the loader is established, and the recursive least squares method with a forgetting factor is used to estimate the vehicle mass m. The longitudinal climbing model of the loader ignores the rotating mass inertia resistance moment and the rolling resistance moment, that is:

[0101]

[0102] In the formula, F t is the driving force of the loader, F i is the road slope resistance, F w is the air resistance, F f is the rolling resistance, F a is the acceleration resistance of the loader; v x is the longitudinal speed of the vehicle; I δ is the rotation mass conversion factor; I wi is the moment of inertia of each wheel; T wi is the torque of each wheel hub motor; C D is the wind resistance coefficient; A is the frontal area of ​​the vehicle; ρ is the air density; f is the rolling resistance coefficient; σ s Road slope; δ f is the heading angle;

[0103] The rolling resistance coefficient f is converted into:

[0104] f=tanσ f

[0105] Here f is an intermediate quantity, and expressing f in the form of an angle is a mathematical transformation;

[0106] The vehicle longitudinal dynamics equation is transformed into:

[0107]

[0108] The process is to simplify the above kinetic equation and convert it into the form of state equation to correspond to the calculation format of the least squares method.

[0109] The recursive least squares method with forgetting factor is used to estimate the mass m of the loader. In the recursive least squares algorithm, the relationship between the measured value and the system parameters is as follows:

[0110]

[0111] Where Z(k) is the measured value; H(k) is the coefficient matrix; is the parameter to be estimated;

[0112] Then the least squares algorithm with forgetting factor is:

[0113]

[0114] In the formula, L1(k) and L2(k) are gain matrices respectively; P1(k) and P2(k) are covariance matrices respectively; x1 and x2 are state quantities, k-1 is the previous moment, k is the current moment, and h is the same. It corresponds to the quantity in the matrix equation above and is an expression of the state equation. T is the matrix transpose;

[0115] The forgetting factor λ f , s It is expressed as:

[0116]

[0117] In the formula, λ base1 , base2 are the basic forgetting factors respectively.

[0118] Direct calculation using the dynamic equation is not accurate because there are many omissions when writing the dynamic equation, and there will be external disturbances in the vehicle form process to interfere with the calculation results. The present invention uses the least squares method to estimate the mass m through the dynamic equation, which can effectively compensate for the loss, reduce interference, and improve calculation accuracy.

[0119] Preferably, the step S6 specifically includes:

[0120] Step S61: Establish a kinematic model of the loader, assuming that the tires do not slip, that is:

[0121]

[0122] In the formula, v f is the longitudinal velocity of the front vehicle; v r is the longitudinal velocity of the rear vehicle body; L f L is the distance between the front wheel hub motor and the hinge point; r is the distance between the rear wheel hub motor and the hinge point; θ is the hinge angle w f is the front vehicle body yaw angle, i.e. the heading angle δ f ;w r is the rear vehicle body yaw angle, i.e. the heading angle δ r ;

[0123] Simplify the above formula, that is:

[0124]

[0125] Step S62: Establish a loader path tracking error model, namely:

[0126]

[0127] In the formula, x e is the x-direction error of the front vehicle; e is the y-direction error of the front vehicle body; e is the heading angle error of the front vehicle; d1, d2, d3 are disturbance terms;

[0128] Step S63, design of sliding surface, namely:

[0129] s=ξ1x e +ξ2y e +ξ3δ e +ξ4sat(θ-θ safe )

[0130] Where, ξ1 is the weight of the error in the x direction; ξ2 is the weight of the error in the y direction; ξ3 is the weight of the error in the heading angle; ξ4 is the trigger weight of the safety boundary of the articulation angle;

[0131] The saturation function sat(x) is in the form of:

[0132]

[0133] Step S64, deriving the sliding surface, we can obtain:

[0134]

[0135] Where, ξ1 is the weight of the error in the x direction; ξ2 is the weight of the error in the y direction; ξ3 is the weight of the error in the heading angle; ξ4 is the trigger weight of the safety boundary of the articulation angle;

[0136] Step S65: In order to ensure that the system can converge on the sliding surface, the control law needs to satisfy:

[0137]

[0138] Where k is a constant and k>0;

[0139] Step S66: Control the articulation angular velocity It can be solved as:

[0140]

[0141] By calculating the articulation angular velocity and processing it by the VCU into a signal for hardware action, the vehicle can reach this articulation angular velocity to achieve the effect of tracking control.

[0142] Preferably, the calculation process for determining whether the loader has reached the terminal position in step S7 is as follows:

[0143] First, calculate the end point distance error e d :

[0144]

[0145] In the formula, x s is the horizontal coordinate of the end point; s is the ordinate of the end point position;

[0146] Then, it is determined whether the end position has been reached, namely:

[0147]

[0148] Wherein, T means reaching the end position; F means not reaching the end position.

[0149] In order to prove that the designed controller is stable, we can analyze it by selecting a Lyapunov function. The main operations are as follows:

[0150] Select the sliding surface s as the Lyapunov function:

[0151]

[0152] Compute the derivative of a Lyapunov function:

[0153]

[0154] According to the sliding mode control law, we can get:

[0155]

[0156] Since k>0, And when s=0, Therefore, the Lyapunov function is stable when s=0, which proves that the system can stably converge to the sliding surface.

[0157] The dotted symbols in this article are all corresponding derivative representations, which are the expressions of the state equation, such as The point is the rotation acceleration.

[0158] The driving mode of the hardware system of the present invention is different from that of the existing drive axle. It adopts wheel hub motor drive, and the hardware system is combined with the control method. The laser radar deployment position and sensor installation are different from those of traditional loaders. In the hardware architecture of the loader, the industrial computer collects real-time data of the laser radar, the electronic control unit (ECU) collects real-time data of the articulation angle sensor, and the electronic control unit (ECU) controls the four wheel hub motors of the loader to realize the real-time path tracking operation of the loader; by establishing a longitudinal climbing model of the loader based on the designed hardware architecture, the recursive least squares method with forgetting factor is used to estimate the vehicle mass of the loader, thereby improving the accuracy of path tracking control; and by the designed safety boundary-based adaptive sliding mode path tracking control method, the articulation angular velocity of the loader is controlled, and it is ensured that the vehicle can travel and operate within the designed safe steering boundary, while improving the vehicle tracking accuracy, the active safety performance of the vehicle is also improved.

[0159] Although the specific implementation modes of the present invention are described above, those skilled in the art should understand that the specific implementation modes described are only illustrative and are not intended to limit the scope of the present invention. Equivalent modifications and changes made by those skilled in the art in accordance with the spirit of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A loader safety margin adaptive sliding mode path tracking control method, characterized in that: A hardware system needs to be built, which includes: a host computer, an electronic control unit, a laser radar, an articulation angle sensor, a front body left motor controller, a front body right motor controller, a rear body left motor controller, a rear body right motor controller, a front body left wheel hub motor, a front body right wheel hub motor, a rear body left wheel hub motor, and a rear body right wheel hub motor; The host computer is connected to the laser radar and the electronic control unit respectively through circuits; The electronic control unit is respectively connected to the articulation angle sensor, the front body left motor controller, the front body right motor controller, the rear body left motor controller, and the rear body right motor controller through a circuit; The front body left motor controller, the front body right motor controller, the rear body left motor controller, and the rear body right motor controller are connected to the front body left wheel hub motor, the front body right wheel hub motor, the rear body left wheel hub motor, and the rear body right wheel hub motor through circuits in a one-to-one correspondence; The wheel hub motors include a front body left wheel hub motor, a front body right wheel hub motor, a rear body left wheel hub motor and a rear body right wheel hub motor, which are respectively connected to their corresponding side wheels through a mechanical structure; The articulation angle sensor is located at the articulation point of the front and rear bodies of the loader; The laser radar is located above the cab of the rear body of the loader; The method comprises the following steps: Step S1: Setting the reference vehicle speed v in the electronic control unit ref , hinge angle safety boundary threshold θ safe , endpoint error threshold value e dth Related parameters of Step S2: The electronic control unit reads the articulation angle sensor and the rotation speed values ​​of each wheel hub motor, and the host computer reads the front body positioning information x collected by the laser radar in real time. f ,y f ,δ f and longitudinal acceleration a x ; Step S3: The host computer plans the vehicle driving path according to the starting point based on the real-time positioning information of the front body of the loader collected by the laser radar, and sends the planned path point information x ref ,y ref ,δ ref and the vehicle longitudinal acceleration a x Transmitted to the electronic control unit; Step S4, the electronic control unit calculates the vehicle speed v according to the rotation speed of each wheel hub motor; Step S5: The electronic control unit determines the longitudinal acceleration a x and the calculated vehicle speed v, to estimate the loader's vehicle mass m; Step S6, the electronic control unit performs a sliding mode path tracking control based on safety margin adaptation according to the estimated vehicle mass m; Step S7, the electronic control unit determines whether the vehicle has reached the destination according to the current location information and the destination location information of the vehicle. If so, the path tracking operation is terminated; otherwise, the process returns to step S6.

2. The method for adaptive sliding mode path tracking control of a loader safety margin according to claim 1, characterized in that: The calculation process of the vehicle speed v in step S4 is specifically as follows: Among them, w1, w2, w3, and w4 are the rotation speeds of the wheels corresponding to the left wheel hub motor of the front body, the right wheel hub motor of the front body, the left wheel hub motor of the rear body, and the right wheel hub motor of the rear body, respectively, R is the tire radius, g is the acceleration of gravity, and t is the braking time.

3. The method for adaptive sliding mode path tracking control of a loader safety margin according to claim 1, characterized in that: The specific process of estimating the loader vehicle mass m in step S5 is as follows: A longitudinal climbing model of the loader is established, and the recursive least squares method with a forgetting factor is used to estimate the vehicle mass m. The longitudinal climbing model of the loader ignores the rotating mass inertia resistance moment and the rolling resistance moment, that is: In the formula, F t is the driving force of the loader, F i is the road slope resistance, F w is the air resistance, F f is the rolling resistance, F a is the acceleration resistance of the loader; v x is the longitudinal speed of the vehicle; I δ is the rotation mass conversion factor; I wi is the moment of inertia of each wheel; T wi is the torque of each wheel hub motor; C D is the wind resistance coefficient; A is the frontal area of ​​the vehicle; ρ is the air density; f is the rolling resistance coefficient; σ s Road slope; δ f is the heading angle; The rolling resistance coefficient f is converted into: f=tanσ f The vehicle longitudinal dynamics equation is transformed into: The recursive least squares method with forgetting factor is used to estimate the mass m of the loader. In the recursive least squares algorithm, the relationship between the measured value and the system parameters is as follows: Where Z(k) is the measured value; H(k) is the coefficient matrix; is the parameter to be estimated; Then the least squares algorithm with forgetting factor is: Where, L1(k) and L2(k) are gain matrices respectively; P1(k) and P2(k) are covariance matrices respectively; The forgetting factor λ f , s It is expressed as: In the formula, λ base1 , base2 are the basic forgetting factors respectively.

4. The method for adaptive sliding mode path tracking control of a loader safety margin according to claim 1, characterized in that: The step S6 specifically includes: Step S61: Establish a kinematic model of the loader, assuming that the tires do not slip, that is: In the formula, v f is the longitudinal velocity of the front vehicle; v r is the longitudinal velocity of the rear vehicle body; L f L is the distance between the front wheel hub motor and the hinge point; r is the distance between the rear wheel hub motor and the hinge point; θ is the hinge angle; w f is the front vehicle body yaw angle, i.e. the heading angle δ f ;w r is the rear vehicle body yaw angle, i.e. the heading angle δ r ; Simplify the above formula, that is: Step S62: Establish a loader path tracking error model, namely: In the formula, x e is the x-direction error of the front vehicle; e is the y-direction error of the front vehicle body; e is the heading angle error of the front vehicle; d1, d2, d3 are disturbance terms; Step S63, design of sliding surface, namely: s=ξ1x e +ξ2y e +ξ3δ e +ξ4sat(θ-θ safe ) Where, ξ1 is the weight of the error in the x direction; ξ2 is the weight of the error in the y direction; ξ3 is the weight of the error in the heading angle; ξ4 is the trigger weight of the safety boundary of the articulation angle; The saturation function sat(x) is in the form of: Step S64, deriving the sliding surface, we can obtain: Where, ξ1 is the weight of the error in the x direction; ξ2 is the weight of the error in the y direction; ξ3 is the weight of the error in the heading angle; ξ4 is the trigger weight of the safety boundary of the articulation angle; Step S65: In order to ensure that the system can converge on the sliding surface, the control law needs to satisfy: Where k is a constant and k>0; Step S66: Control the articulation angular velocity It can be solved as:

5. The method for adaptive sliding mode path tracking control of a loader safety margin according to claim 1, characterized in that: The calculation process for determining whether the loader has reached the end position in step S7 is as follows: First, calculate the end point distance error e d : In the formula, x s is the horizontal coordinate of the end point; s is the ordinate of the end point position; Then, it is determined whether the end position has been reached, namely: Wherein, T means reaching the end position; F means not reaching the end position.

Images