CN115042791A

CN115042791A - Reversing control method, device, equipment and medium

Info

Publication number: CN115042791A
Application number: CN202210862135.3A
Authority: CN
Inventors: 吴光强; 曾奇; 陈秋石; 毛礼波; 鞠丽娟
Original assignee: Tongji University
Current assignee: Tongji University
Priority date: 2022-07-20
Filing date: 2022-07-20
Publication date: 2022-09-13

Abstract

The invention relates to the technical field of unmanned vehicles and discloses a reversing control method, a reversing control device, reversing control equipment and a reversing control medium. According to the method, a state space model corresponding to the unmanned mine car is determined according to a pre-constructed reversing dynamics model and a pre-constructed error change rate model; acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information; setting a corresponding time-varying weight matrix according to the current state quantity; determining a corresponding target front wheel corner according to the time-varying weight matrix, the state quantity space model and a preset linear quadratic regulator, and performing backing control on the unmanned mine car through the target front wheel corner; thereby realizing the accurate control of the working condition of backing the car of the unmanned mine car.

Description

Reversing control method, device, equipment and medium

Technical Field

The invention relates to the technical field of unmanned vehicles, in particular to a reversing control method, a reversing control device, reversing control equipment and reversing control media.

Background

With the pursuit of transportation safety and efficiency in the industrial field, Advanced Driving Assistance Systems (ADAS) are increasingly being widely used in transportation vehicles. The unmanned mine car combines 5G, big data and cloud computing, can independently control to come and go to loading and unloading points, and realizes high-precision independent tracking. Wherein, unloading point, parking area and shovel dress district all need the vehicle to park independently according to the orbit of backing a car.

However, the unmanned mine car is large in size, high in load capacity, narrow in discharge opening, variable in parking position and shovel loading area excavator position, and incapable of accurately controlling backing of the unmanned mine car.

Disclosure of Invention

The invention mainly aims to provide a reversing control method, a reversing control device, reversing control equipment and reversing control media, and aims to realize accurate control of the reversing working condition of an unmanned mine car.

In order to achieve the above object, the present invention provides a reverse control method, including the steps of:

determining a corresponding state space model based on a pre-constructed reversing dynamics model and a pre-constructed error change rate model, wherein the reversing dynamics model is established based on a linear two-degree-of-freedom model of the unmanned mine car, and the error change rate model is established based on a transverse error change rate and a course angle error change rate of the unmanned mine car;

acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information;

and setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel corner based on a preset linear quadratic regulator and the state space model so as to control the unmanned mine car to back up.

Preferably, before the step of determining the corresponding state space model based on the pre-constructed reverse dynamics model and the pre-constructed error change rate model, the reverse control method further includes:

acquiring a linear two-degree-of-freedom model of the unmanned mine car, front wheel side deflection rigidity, rear wheel side deflection rigidity, a distance from a vehicle mass center to a front axle, a distance from the vehicle mass center to a rear axle and a front wheel corner;

determining a front wheel side slip angle and a rear wheel side slip angle according to the linear two-degree-of-freedom model, the distance from the vehicle center of mass to the front axle, the distance from the vehicle center of mass to the rear axle and the front wheel rotation angle;

determining corresponding front wheel lateral force according to the front wheel side deflection angle and the front wheel side deflection rigidity;

determining the corresponding rear wheel lateral force according to the rear wheel lateral deflection angle and the rear wheel lateral deflection rigidity;

and carrying out stress simplification analysis on the linear two-degree-of-freedom model according to the lateral force of the front wheels and the lateral force of the rear wheels to obtain a reversing dynamics model of the unmanned mine car.

Preferably, the step of determining a corresponding state space model based on the pre-constructed reverse dynamics model and the pre-constructed error change rate model includes:

analyzing the error change rate model to obtain an analysis expression of the transverse change rate and the course angle change rate;

and determining a corresponding state space model according to the backing dynamics model, the error change rate model and the analytical expression.

Preferably, the step of determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information comprises:

traversing reference path points in the backing reference path information according to the current pose information, and determining reference path points closest to the vehicle centroid point as path projection points;

calculating the transverse error and the course angle error of the unmanned mine car according to the vehicle center of mass point and the path projection point;

acquiring a calculation period, a transverse error of a previous calculation period and a course angle error of a previous calculation period of the unmanned mine car, and determining a corresponding transverse error change rate and a corresponding course angle error change rate according to the calculation period, the transverse error of the previous calculation period, the course angle error of the previous calculation period, the transverse error and the course angle error;

and determining the current state quantity of the unmanned mine car according to the transverse error, the transverse error change rate, the course angle error and the course angle error change rate.

Preferably, the space state model includes characteristic parameters, the step of setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel rotation angle based on a preset linear quadratic regulator and the state space equation to control the unmanned mine car to back up includes:

setting a corresponding time-varying weight matrix according to the current state quantity;

calculating a corresponding feedback gain rate according to the time-varying weight matrix and the characteristic parameters and through a preset linear quadratic regulator;

determining a corresponding target corner according to the feedback gain rate and the current state quantity, and carrying out change rate limit processing on the target corner to obtain a corresponding corrected front wheel corner;

and carrying out amplitude limiting processing on the corrected front wheel steering angle, determining a corresponding target front wheel steering angle, and sending a signal of the target front wheel steering angle to an actuator of the unmanned mine car so as to carry out backing control on the unmanned mine car.

Preferably, after the step of setting a corresponding time-varying weight matrix based on the current state quantity and determining a target front wheel steering angle based on a preset linear quadratic regulator and the state space model to perform the reversing control on the unmanned mine car, the reversing control method further includes:

entering the next calculation cycle, and returning to the step: and acquiring the current pose information and the backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information.

In addition, in order to achieve the above object, the present invention also provides a reverse control device, including:

the system comprises a determining module, a state space model and a state space model, wherein the determining module is used for determining a corresponding state space model based on a pre-constructed reversing dynamics model and a pre-constructed error change rate model, the reversing dynamics model is established based on a linear two-degree-of-freedom model of the unmanned mine car, and the error change rate model is established based on the transverse error change rate and the course angle error change rate of the unmanned mine car;

the acquisition module is used for acquiring the current pose information and the backing reference path information of the unmanned mine car and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information;

and the control module is used for setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel corner based on a preset linear quadratic regulator and the state space model so as to control the unmanned mine car to back up.

In addition, in order to achieve the above object, the present invention also provides a device, which is a reverse control device, including: the reversing control method comprises a memory, a processor and a reversing control program which is stored on the memory and can run on the processor, wherein the reversing control program realizes the steps of the reversing control method when being executed by the processor.

In addition, in order to achieve the above object, the present invention further provides a medium, which is a computer readable storage medium, wherein a reverse control program is stored on the computer readable storage medium, and when being executed by a processor, the reverse control program implements the steps of the reverse control method as described above.

The invention provides a reversing control method, a reversing control device, reversing control equipment and reversing control media; the reverse control method comprises the following steps: determining a corresponding state space model based on a pre-constructed reversing dynamics model and a pre-constructed error change rate model, wherein the reversing dynamics model is established based on a linear two-degree-of-freedom model of the unmanned mine car, and the error change rate model is established based on a transverse error change rate and a course angle error change rate of the unmanned mine car; acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information; and setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel corner based on a preset linear quadratic regulator and the state space model so as to control the unmanned mine car to back up. According to the method, a state space model corresponding to the unmanned mine car is determined according to a pre-constructed reversing dynamics model and a pre-constructed error change rate model; acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information; setting a corresponding time-varying weight matrix according to the current state quantity; determining a corresponding target front wheel corner according to the time-varying weight matrix, the state quantity space model and a preset linear quadratic regulator, and performing backing control on the unmanned mine car through the target front wheel corner; thereby realizing the accurate control of the working condition of backing the car of the unmanned mine car.

Drawings

FIG. 1 is a schematic diagram of an apparatus architecture of a hardware operating environment according to an embodiment of the present invention;

FIG. 2 is a schematic flowchart of a reverse control method according to a first embodiment of the present invention;

FIG. 3 is a schematic view of a sub-flow chart of a first embodiment of a reverse control method according to the present invention;

FIG. 4 is a flowchart illustrating a reverse control method according to a second embodiment of the present invention;

FIG. 5 is a schematic flow chart of a linear two-degree-of-freedom unmanned tramcar model according to a second embodiment of the reversing control method of the invention;

FIG. 6 is a flowchart illustrating a reverse control method according to a third embodiment of the present invention;

FIG. 7 is a flowchart illustrating a reverse control method according to a fourth embodiment of the present invention;

FIG. 8 is a schematic diagram of a lateral error and a heading angle error in a fourth embodiment of the reverse control method of the present invention;

FIG. 9 is a schematic flow chart diagram of a fifth embodiment of the reverse control method of the present invention;

fig. 10 is a functional block diagram of the reverse control device according to the first embodiment of the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.

The device of the embodiment of the invention can be a mobile terminal or a server device.

As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.

Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 is not intended to be limiting of the apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a reverse control program.

The operating system is a program for managing and controlling the reversing control equipment and software resources and supports the running of a network communication module, a user interface module, a reversing control program and other programs or software; the network communication module is used for managing and controlling the network interface 1002; the user interface module is used to manage and control the user interface 1003.

In the reverse control apparatus shown in fig. 1, the reverse control apparatus calls a reverse control program stored in a memory 1005 through a processor 1001 and performs operations in various embodiments of the reverse control method described below.

Based on the hardware structure, the embodiment of the reversing control method is provided.

Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a reverse control method of the present invention, where the reverse control method includes:

step S10, determining a corresponding state space model based on a pre-constructed reversing dynamics model and a pre-constructed error change rate model, wherein the reversing dynamics model is established based on a linear two-degree-of-freedom model of the unmanned mine car, and the error change rate model is established based on the transverse error change rate and the course angle error change rate of the unmanned mine car;

step S20, acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information;

and step S30, setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel corner based on a preset linear quadratic regulator and the state space model so as to control the unmanned mine car to back.

According to the method, a state space model corresponding to the unmanned mine car is determined according to a pre-constructed reversing dynamics model and a pre-constructed error change rate model; acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information; setting a corresponding time-varying weight matrix according to the current state quantity; determining a corresponding target front wheel corner according to the time-varying weight matrix, the state quantity space model and a preset linear quadratic regulator, and performing backing control on the unmanned mine car through the target front wheel corner; thereby realizing the accurate control of the working condition of backing the car of the unmanned mine car.

The respective steps will be described in detail below:

and step S10, determining a corresponding state space model based on a pre-constructed reversing dynamics model and a pre-constructed error change rate model, wherein the reversing dynamics model is created based on a linear two-degree-of-freedom model of the unmanned mine car, and the error change rate model is created based on the transverse error change rate and the course angle error change rate of the unmanned mine car.

In this embodiment, through analysis in-process atress relation of backing a car for the dynamics model modeling of backing a car is more accurate, and it is faster to compare in fixed value convergence through the weight matrix of design time-varying, and the overshoot is littleer, makes unmanned mine car drive more steady, and control accuracy is higher. By establishing an unmanned mine car backing model, designing a time-varying weight matrix, calculating a target front wheel corner based on a linear quadratic regulator theory, and sending corner information to a lower-layer controller for response; thereby realizing the accurate control of the working condition of backing the car of the unmanned mine car.

And determining a state space model of the unmanned mine car by analyzing the pre-constructed reversing dynamics model and the pre-constructed error change rate model. The linear two-degree-of-freedom model of the unmanned mine car is used for researching the running rule of the unmanned mine car according to mechanics, and comprises changes of the position and the speed of the car, lateral force of front wheels and lateral force of rear wheels and the like; the reversing dynamics model is created according to a linear two-degree-of-freedom model of the unmanned mine car, and specifically, the reversing dynamics model of the unmanned mine car can be obtained by performing stress analysis on the linear two-degree-of-freedom model of the unmanned mine car.

By analyzing the stress relation in the backing process, the backing dynamic model is more accurate; the reverse dynamics model may include changes in the unmanned mine vehicle behavior such as longitudinal velocity, longitudinal acceleration, lateral velocity, lateral acceleration, yaw rate, and yaw acceleration of the vehicle of the unmanned mine vehicle.

Wherein the error change rate model is created according to the lateral error change rate and the course angle error change rate of the unmanned mine car, in particular to the lateral error change rate of the unmanned mine car and the course angle error change rate of the unmanned mine car respectively

And rate of change of course angle error

And analyzing and constructing a corresponding error change rate model. Wherein the lateral error e _y The component of the relative distance between the vehicle centroid and the reference path point on the y axis of the vehicle coordinate system is taken as the component; course angle error e _ψ The difference between the vehicle course and the reference waypoint course; rate of change of lateral error

Transverse error e for characterizing unmanned mine cars _y The speed of change is high or low; rate of change of course angle error

Course angle error e for representing unmanned mine car _ψ The speed of change is fast.

Wherein, the expression of the error change rate model is as follows:

wherein the content of the first and second substances,

represents the rate of change of lateral error, v _y Represents the lateral velocity, e _ψ Indicating course angle error, v _x Represents the longitudinal speed,

Indicating the rate of change of course angle error,

The expression is the yaw rate,

Represents yaw angular acceleration,

The reference yaw rate is indicated.

The error of the reversing process of the unmanned mine car is reduced through the error change rate model, and the vehicle tracking precision is improved.

The state space model of the unmanned mine car can be adjusted in time according to the implementation pose information change of the unmanned mine car; wherein, the state space model is expressed as follows:

wherein e is _y The lateral error of the unmanned mine car is shown,

indicating the rate of change of lateral error of the unmanned tramcar, e _ψ Indicating the course angle error of the unmanned mine car,

indicating the rate of change of course angle error, v, of the unmanned mine car _x The longitudinal speed of the unmanned mine car,

Indicating longitudinal acceleration, v, of unmanned tramcars _y Represents the transverse speed of the unmanned mine car,

Represents the lateral acceleration of the unmanned tramcar, m represents the mass of the unmanned tramcar, I _z Represents the rotational inertia of the unmanned mine car,

Shows the yaw angular velocity of the unmanned mine car,

Represents the yaw angular acceleration of the unmanned mine car,

A reference course angular velocity representing the backing reference path information; c _f Shows the front wheel cornering stiffness, C, of the unmanned mine car _r Indicates the cornering stiffness of the rear wheel side of the unmanned mine car, l _f Representing the distance from the vehicle's center of mass to the front axle,/ _r Representing the distance, delta, from the vehicle's center of mass to the rear axle _f Indicating the corner of the front wheel of the unmanned mine car.

Order to

That is, the final state space model is expressed as:

wherein X represents the state quantity of the unmanned mine car, and the state quantity X comprises the transverse error e of the unmanned mine car _y Rate of change of lateral error

Course angle error e _ψ And course angle error becomesChemical conversion rate

And step S20, acquiring the current pose information and the backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information.

In the embodiment, the current pose information and the backing reference path information of the unmanned mine car are obtained from different channels; the embodiment does not limit the channels of the current pose information and the backing reference path information of the unmanned mine car.

The pose information is used for representing the position and the operation posture of the unmanned mine car.

The current pose information comprises a vehicle center of mass point P of the unmanned tramcar _ego (x _ego ,y _ego ,ψ _ego )。

The backing reference path information is ideal backing path information, is obtained by calculation according to a backing starting point and a backing end point, and can be expressed by a coordinate point or a curve equation and the like.

By taking into account the center of mass point P of the vehicle _ego (x _ego ,y _ego ,ψ _ego ) And backing reference path information, calculating projection points matched with the positions of the vehicles in the reference path, namely path projection points P _proj (x _proj ,y _proj ,ψ _proj ) (ii) a According to the center of mass P of the vehicle _ego (x _ego ,y _ego ,ψ _ego ) Sum path projection point P _proj (x _proj ,y _proj ,ψ _proj ) And determining the current state quantity corresponding to the current pose information.

And step S30, setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel corner based on a preset linear quadratic regulator and the state space model so as to control the unmanned mine car to back up.

In this embodiment, a time-varying weight matrix corresponding to the current state quantity is set according to the obtained current state quantity; the time-varying weight matrix expression is as follows:

R＝r

wherein q is ₁ Indicates the lateral error e _y Weight of (q), q ₂ Indicating the rate of change of lateral error

Weight of (q), q ₃ Indicating a heading angle error e _ψ Weight of (a), and q ₄ Indicating rate of change of course angle error

The weight of (c).

Wherein q is ₁ 、q ₂ 、q ₃ And q is ₄ The larger the value of the weight is, the higher the control degree of the control system of the unmanned mine car on the state quantity is; i.e. by adjusting q ₁ 、q ₂ 、q ₃ And q is ₄ The relative weight of the mine car can adjust the reversing control precision of the unmanned mine car. R is a weight corresponding to the input of the state space model, i.e., the turning angle of the steered wheel, and the larger the weight is, the larger the limit on the turning angle of the steered wheel is, i.e., the smaller the steering angle is. Because the Q matrix and the R matrix only need to consider the relative relation during the design, the R is set as a constant value, and the weight matrix Q is designed in a time-varying manner.

Calculating a feedback gain ratio K corresponding to the current state quantity according to the time-varying weight matrix, the state space model and a preset linear quadratic regulator;

calculating a target corner according to the current state quantity and the feedback gain rate K, and determining a target front wheel corner by carrying out change rate limit value and amplitude limiting processing on the target corner; and then the reversing control is carried out on the unmanned mine car according to the target front wheel corner.

Further, in an embodiment, referring to fig. 3, after step S30, the reverse control method further includes:

step F10, enter the next calculation cycle, return to the step: and acquiring the current pose information and the backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information.

In the embodiment, a corresponding time-varying weight matrix is set according to the current state quantity; determining a corresponding target front wheel corner according to the time-varying weight matrix, the state quantity space model and a preset linear quadratic regulator, entering a next calculation cycle after the step of controlling the unmanned mine car to back through the target front wheel corner, and returning to the execution step: acquiring current pose information and backing reference path information of the unmanned mine car, and determining the current state quantity of the unmanned mine car according to the current pose information and the backing reference path information; after entering the next calculation period, repeating the operation to enable the unmanned mine car to back up according to the target front wheel steering angle; when the calculation of the target front wheel corner enters the next calculation period, the calculation is repeatedly circulated, and the backing control of the unmanned mine car is completed; thereby improving the efficiency of the backing control of the unmanned mine car.

Further, based on the first embodiment of the reverse control method, a second embodiment of the reverse control method is provided.

The second embodiment of the reverse control method is different from the first embodiment of the reverse control method in that, in this embodiment, before the step of determining the corresponding state space model based on the pre-constructed reverse dynamics model and the pre-constructed error change rate model in step S10, referring to fig. 4, the reverse control method further includes:

step A10, acquiring a linear two-degree-of-freedom model of the unmanned mine car, front wheel side deflection rigidity, rear wheel side deflection rigidity, distance from a vehicle mass center to a front axle, distance from the vehicle mass center to the rear axle and a front wheel corner;

step A20, determining a front wheel side slip angle and a rear wheel side slip angle according to the linear two-degree-of-freedom model, the distance from the center of mass of the vehicle to the front axle, the distance from the center of mass of the vehicle to the rear axle and the front wheel corner;

step A30, determining the corresponding front wheel lateral force according to the front wheel side deflection angle and the front wheel side deflection rigidity;

step A40, determining the corresponding rear wheel lateral force according to the rear wheel side deflection angle and the rear wheel side deflection rigidity;

and A50, carrying out stress simplification analysis on the linear two-degree-of-freedom model according to the lateral force of the front wheels and the lateral force of the rear wheels to obtain a reversing dynamics model of the unmanned mine car.

In the embodiment, a linear two-degree-of-freedom model of the unmanned mine car, the front wheel lateral stiffness, the rear wheel lateral stiffness, the distance from the center of mass of the vehicle to the front axle, the distance from the center of mass of the vehicle to the rear axle and the corner of the front wheel are obtained; determining a front wheel side slip angle and a rear wheel side slip angle according to the linear two-degree-of-freedom model, the distance from the center of mass of the vehicle to the front axle, the distance from the center of mass of the vehicle to the rear axle and the front wheel corner; determining the corresponding front wheel lateral force according to the front wheel side deflection angle and the front wheel side deflection rigidity; determining the corresponding rear wheel lateral force according to the rear wheel lateral deflection angle and the rear wheel lateral deflection rigidity; carrying out stress simplification analysis on the linear two-degree-of-freedom model according to the front wheel lateral force and the rear wheel lateral force to obtain a reversing dynamics model of the unmanned mine car; the accuracy of the reversing dynamics model is further improved by analyzing the stress relation in the reversing process.

The respective steps will be described in detail below:

and step A10, acquiring a linear two-degree-of-freedom model of the unmanned mine car, the front wheel side deflection rigidity, the rear wheel side deflection rigidity, the distance from the center of mass of the vehicle to the front axle, the distance from the center of mass of the vehicle to the rear axle and the front wheel corner.

In the embodiment, the linear two-degree-of-freedom model and the front wheel side deflection rigidity C of the unmanned mine car are obtained from different channels _f Rear wheel side cornering stiffness C _r Distance l from vehicle mass center to front axle _f Distance l from vehicle mass center to rear axle _r And front wheel turning angle delta _f (ii) a In the embodiment, a linear two-degree-of-freedom model and front wheel side deflection rigidity C of the unmanned mine car are obtained _f Rear wheel side cornering stiffness C _r Distance l from vehicle mass center to front axle _f Distance l from vehicle mass center to rear axle _r And front wheel turning angle delta _f The channel of (a) is not limited.

The linear two-degree-of-freedom model of the unmanned mine car is based on the mechanics research on the operation rule of the unmanned mine car, and comprises the changes of the position, the speed, the lateral force of front wheels and rear wheels and the like of the car. Referring to FIG. 5, FIG. 5 is a schematic view of a linear two-degree-of-freedom model of the unmanned mining vehicle; the expression of the linear two-degree-of-freedom model is as follows:

wherein the content of the first and second substances,

represents the lateral acceleration of the unmanned mine car,

Representing yaw angular acceleration of the unmanned mine car, m representing mass of the unmanned mine car, F _f Showing lateral force of front wheel of unmanned mine car, F _r Shows the rear wheel side force v of the unmanned mine car _x Indicating longitudinal speed, v, of unmanned tramcar _y Represents the transverse speed of the unmanned mine car,

Representing yaw rate, I, of unmanned tramcar _z Indicating rotation of unmanned mine carMoment of inertia,/ _f Representing the distance from the centre of mass of the vehicle to the front axle,/ _r Representing the distance of the vehicle's center of mass to the rear axle.

Step A20, according to the linear two-degree-of-freedom model and the distance l from the center of mass of the vehicle to the front axle _f Determining a front wheel side slip angle and a rear wheel side slip angle according to the vehicle center-of-mass to rear axle distance and the front wheel rotation angle.

In the embodiment, the linear two-degree-of-freedom model is obtained according to the longitudinal speed v in the obtained linear two-degree-of-freedom model _x Transverse velocity v _y Yaw rate

Distance l from vehicle mass center to front axle _f Distance l from vehicle mass center to rear axle _r And front wheel angle delta _f Analyzing a front wheel side deflection angle and a rear wheel side deflection angle of the unmanned mine car; an expression for obtaining the front wheel side slip angle and the rear wheel side slip angle of the unmanned tramcar is as follows:

wherein alpha is _f Indicating the front wheel side slip angle, α _r Indicating the rear wheel side slip angle.

Step a30, determining the corresponding front wheel lateral force based on the front wheel yaw angle and the front wheel yaw stiffness.

In the embodiment, the corresponding front wheel lateral force is determined according to the front wheel side deflection angle and the front wheel side deflection rigidity of the unmanned tramcar; wherein, the front wheel lateral force is the lateral force that the front wheel tire of unmanned mine car received, and the tire characteristic of front wheel lateral force in the linear range can be expressed as:

F _yf ＝2C _f α _f

wherein, F _yf Expressed as front wheel side force, C _f Expressed as front wheel cornering stiffness, α _f Indicated as front wheel slip angle.

Step a40, determining the corresponding rear wheel lateral force based on the rear wheel yaw angle and the rear wheel yaw stiffness.

In the embodiment, the corresponding rear wheel side force is determined according to the rear wheel side deflection angle and the rear wheel side deflection rigidity of the unmanned mine car; wherein, the rear wheel lateral force is the lateral force that the rear wheel tire of unmanned mine car received, and the tire characteristic that rear wheel lateral force is in the linear range can be expressed as:

F _yr ＝2C _r α _r

wherein, F _yr Expressed as rear wheel lateral force, C _r Expressed as rear wheel cornering stiffness, α _r Indicated as rear wheel slip angle.

In this embodiment, the force-bearing simplified analysis is performed on the linear two-degree-of-freedom model according to the determined front wheel lateral force and rear wheel lateral force, so as to obtain a reversing dynamics model of the unmanned mine car, wherein the reversing dynamics model has the following expression:

wherein the content of the first and second substances,

represents the lateral acceleration of the unmanned mine car,

Representing yaw angular acceleration of the unmanned mine car, m representing mass of the unmanned mine car, F _yf Showing lateral force of front wheel of unmanned mine car, F _yr Shows the rear wheel side force v of the unmanned mine car _x Indicating longitudinal speed, v, of unmanned tramcar _y Represents the transverse speed of the unmanned mine car,

Representing yaw rate, I, of unmanned tramcar _z To representMoment of inertia of unmanned mine car _f Representing the distance from the centre of mass of the vehicle to the front axle,/ _r Representing the distance, delta, of the vehicle's center of mass to the rear axle _f Indicating the front wheel turning angle.

The front wheel lateral force and the rear wheel lateral force in the linear two-degree-of-freedom model are equivalently replaced by an expression of the front wheel lateral force and the rear wheel lateral force determined by the front wheel lateral deflection rigidity and the front wheel lateral deflection angle of the unmanned mine car, and a reversing dynamics model of the unmanned mine car is obtained.

In the embodiment, a linear two-degree-of-freedom model of the unmanned mine car, the front wheel side deflection rigidity, the rear wheel side deflection rigidity, the distance from the center of mass of the car to the front axle, the distance from the center of mass of the car to the rear axle and the corner of the front wheel are obtained; determining a front wheel side deflection angle and a rear wheel side deflection angle according to the linear two-degree-of-freedom model, the distance from the vehicle center of mass to the front axle, the distance from the vehicle center of mass to the rear axle and the front wheel rotation angle; determining the corresponding front wheel lateral force according to the front wheel side deflection angle and the front wheel side deflection rigidity; determining the corresponding rear wheel lateral force according to the rear wheel lateral deflection angle and the rear wheel lateral deflection rigidity; carrying out stress simplification analysis on the linear two-degree-of-freedom model according to the front wheel lateral force and the rear wheel lateral force to obtain a reversing dynamics model of the unmanned mine car; the accuracy of the reversing dynamics model is further improved by analyzing the stress relation in the reversing process.

Further, based on the first and second embodiments of the reverse control method of the present invention, a third embodiment of the reverse control method of the present invention is provided.

The third embodiment of the reverse control method is different from the first, second, and third embodiments of the reverse control method in that the present embodiment determines refinement of a corresponding state space model based on a pre-constructed reverse dynamics model and a pre-constructed error change rate model in step S10, and with reference to fig. 6, the step specifically includes:

step S11, analyzing the error change rate model to obtain an analysis expression of the transverse change rate and the course angle change rate;

and step S12, determining a corresponding state space model according to the reversing dynamics model, the error change rate model and the analytical expression.

In the embodiment, an analysis expression of the transverse change rate and the course angle change rate is obtained by analyzing the error change rate model; determining a state space model of the unmanned mine car according to the reversing dynamics model, the error change rate model and the analytical expression; therefore, the reversing control precision of the unmanned mine car is improved through the state space model.

The respective steps will be described in detail below:

and step S11, analyzing the error change rate model to obtain an analytical expression of the transverse error change rate and the course angle error change rate.

In this embodiment, an error change rate model is analyzed, wherein an expression of the error change rate model is as follows:

wherein the content of the first and second substances,

Indicating the rate of change of course angle error,

The expression is the yaw rate,

Represents yaw angular acceleration,

The reference yaw rate is indicated.

The specific analysis process is as follows: suppose that the longitudinal velocity v of the unmanned tramcar is during the reversing of the unmanned tramcar _x For constant velocity, while assuming a reference yaw rate acceleration in the error rate model

On the basis, the error change rate model is analyzed to obtain an analytical expression of the transverse error change rate and the course angle error change rate, wherein the analytical expression is as follows:

wherein the content of the first and second substances,

indicates the rate of change of lateral error,

Indicating the rate of change of course angle error,

Representing lateral acceleration, v _x Represents the longitudinal speed,

Shows the yaw rate,

Indicates the reference yaw rate,

The yaw angular acceleration is shown.

In the embodiment, a state space model corresponding to the unmanned mine car is determined according to a reversing dynamics model, an error change rate model and an analytical expression; the specific process is as follows:

the expression of the backing dynamic model is as follows:

the expression of the error rate model is as follows:

the analytical expressions are as follows:

and determining the state space models corresponding to the unmanned mine car for combination by using the backing dynamics model, the error change rate model and the analytical expression, so as to obtain the state space models corresponding to the unmanned mine car, wherein the state space models are expressed as follows:

order to

Memo

That is, the final state space model is expressed as:

wherein X represents the state quantity of the unmanned mine car, and the state quantity X comprises the transverse direction of the unmanned mine carDirection error e _y Rate of change of lateral error

Course angle error e _ψ And rate of change of course angle error

The state space model of the unmanned mine car can be adjusted in time according to the implementation pose information change of the unmanned mine car.

Further, based on the first, second and third embodiments of the reverse control method of the present invention, a fourth embodiment of the reverse control method of the present invention is provided.

The fourth embodiment of the reverse control method is different from the first, second and third embodiments of the reverse control method in that the present embodiment determines refinement of the current state quantity of the unmanned mine car according to the current pose information and the reverse reference path information in step S20, and with reference to fig. 7, the step specifically includes:

step S21, traversing reference path points in the backing reference path information according to the current pose information, and determining the reference path point closest to the center of mass point of the vehicle as a path projection point;

step S22, calculating the transverse error and the course angle error of the unmanned mine car according to the vehicle center of mass point and the path projection point;

step S23, acquiring the calculation cycle of the unmanned mine car, the transverse error of the previous calculation cycle and the course angle error of the previous calculation cycle, and determining the corresponding transverse error change rate and course angle error change rate according to the calculation cycle, the transverse error of the previous calculation cycle, the course angle error of the previous calculation cycle, the transverse error and the course angle error;

and step S24, determining the current state quantity of the unmanned mine car according to the transverse error, the transverse error change rate, the course angle error and the course angle error change rate.

According to the method, the reference path points in the backing reference path information are traversed according to the current pose information, and the reference path point closest to the center of mass point of the vehicle is determined as a path projection point; according to the vehicle center of mass point and the path projection point, calculating the transverse error and the course angle error of the unmanned mine car; acquiring a calculation cycle of the unmanned mine car, a transverse error of a previous calculation cycle and a course angle error of the previous calculation cycle, and determining a corresponding transverse error change rate and a corresponding course angle error change rate according to the calculation cycle, the transverse error of the previous calculation cycle, the course angle error of the previous calculation cycle, the transverse error and the course angle error; determining the current state quantity of the unmanned mine car according to the transverse error, the transverse error change rate, the course angle error and the course angle error change rate; thereby improving the accuracy of the current state quantity.

The respective steps will be described in detail below:

and step S21, traversing the reference path points in the backing reference path information according to the current pose information, and determining the reference path point closest to the vehicle centroid point as a path projection point.

In the present embodiment, referring to fig. 8, fig. 8 is a schematic diagram of a lateral error and a heading angle error; the pose information is used for representing the position and the running posture of the unmanned mine car; location includes, but is not limited to, vehicle center of mass; wherein, the current pose information comprises a vehicle center of mass point P of the unmanned mine car _ego (x _ego ,y _ego ,ψ _ego ) (ii) a Calculating projection points matched with the positions of the vehicles in the reference path according to the center of mass points of the vehicles, namely path projection points P _proj (x _proj ,y _proj ,ψ _proj )。

Finding out the reference path point closest to the center of mass point of the vehicle by traversing the reference path points in the backing reference path information,and determining the reference path point as a path projection point P _proj (x _proj ,y _proj ,ψ _proj )。

And step S22, calculating the lateral error and the heading angle error of the unmanned mine car according to the vehicle center of mass point and the path projection point.

In the present embodiment, referring to fig. 8, fig. 8 is a schematic diagram of lateral error and heading angle error; according to the vehicle center of mass point P _ego (x _ego ,y _ego ,ψ _ego ) Sum path projection point P _proj (x _proj ,y _proj ,ψ _proj ) Calculating the center of mass P of the vehicle _ego (x _ego ,y _ego ,ψ _ego ) Projection point P with reference path _proj (x _proj ,y _proj ,ψ _proj ) The difference values in the global coordinate system are Δ X and Δ Y, respectively, and are calculated as follows:

defining the transverse error e of the unmanned mine car on the left side of the road _y Positive, lateral error e on the right side of the road _y Is negative; transverse error e _y The calculation method is as follows:

e _y ＝ΔYcos(ψ _proj )-ΔXsin(ψ _proj )

wherein e is _y Represents a lateral error, and Δ X represents a vehicle center of mass point P _ego (x _ego ,y _ego ,ψ _ego ) Projection point P with reference path _proj (x _proj ,y _proj ,ψ _proj ) The difference, DeltaY, in the x-axis of the global coordinate system represents the center of mass P of the vehicle _ego (x _ego ,y _ego ,ψ _ego ) Projection point P with reference path _proj (x _proj ,y _proj ,ψ _proj ) Difference, ψ, in the y-axis of the global coordinate system _ego Indicating the vehicle heading angle, psi _proj Representing a road direction angle;

defining the heading angle error when the vehicle head faces outwards as positive, and the heading angle error when the vehicle head faces inwards as negative, so that the heading angle error calculation mode is as follows:

e _ψ ＝ψ _ego -ψ _proj

wherein e is _ψ Indicating heading angle error, psi _ego Indicating the heading angle, psi of the vehicle _proj Indicating the road direction angle.

And step S23, acquiring the calculation cycle of the unmanned mine car, the transverse error of the previous calculation cycle and the course angle error of the previous calculation cycle, and determining the corresponding transverse error change rate and course angle error change rate according to the calculation cycle, the transverse error of the previous calculation cycle, the course angle error of the previous calculation cycle, the transverse error and the course angle error.

In the embodiment, the calculation cycle of the unmanned mine car, the transverse error of the previous calculation cycle and the course angle error of the previous calculation cycle are obtained from different channels; the embodiment does not limit the channel for acquiring the calculation period of the unmanned mine car, the transverse error of the previous calculation period and the course angle error of the previous calculation period.

And determining the corresponding transverse error change rate and course angle error change rate according to the calculation period, the transverse error of the previous calculation period, the course angle error of the previous calculation period, the transverse error and the course angle error.

The calculation mode of the transverse error change rate is as follows: let the lateral error at the k-th time be e _y (kT) and the course angle error at the k +1 th moment is e _y [(k+1)T]Then the rate of change of lateral error at time k +1

The calculation method of (c) is as follows:

where T represents a calculation period.

The course angle error change rate is calculated in the following mode: recording the course angle error of the kth moment as e _ψ (kT) ofThe course angle error of k +1 time is e _ψ [(k+1)T]Then the rate of change of course angle error at time k +1

The calculation of (d) is expressed as follows.

Where T represents a calculation period.

In the embodiment, the current transverse error e of the unmanned mine car is calculated according to the current transverse error e _y Rate of change of lateral error

Course angle error e _ψ And rate of change of course angle error

Determining the current state quantity X of the unmanned mine car, wherein the expression of the current state quantity is

The state quantity X includes the transverse error e of the unmanned tramcar _y Rate of change of lateral error

Course angle error e _ψ And rate of change of course angle error

In the embodiment, according to the current pose information, traversing reference path points in the backing reference path information, and determining the reference path point closest to the center of mass point of the vehicle as a path projection point; calculating the transverse error and the course angle error of the unmanned mine car according to the vehicle center of mass point and the path projection point; acquiring a calculation cycle of the unmanned mine car, a transverse error of a previous calculation cycle and a course angle error of the previous calculation cycle, and determining a corresponding transverse error change rate and a corresponding course angle error change rate according to the calculation cycle, the transverse error of the previous calculation cycle, the course angle error of the previous calculation cycle, the transverse error and the course angle error; determining the current state quantity of the unmanned mine car according to the transverse error, the transverse error change rate, the course angle error and the course angle error change rate; thereby improving the accuracy of the current state quantity.

Further, a fifth embodiment of the reverse control method is provided based on the first, second, third and fourth embodiments of the reverse control method of the present invention.

The fifth embodiment of the reverse control method is different from the first, second, third and fourth embodiments of the reverse control method in that in the present embodiment, for step S30, a corresponding time-varying weight matrix is set based on the current state quantity, and a target front wheel turning angle is determined based on a preset linear quadratic regulator and the state space equation, so as to refine the reverse control of the unmanned mine car, with reference to fig. 9, the step specifically includes:

step S31, setting a corresponding time-varying weight matrix according to the current state quantity;

step S32, calculating a corresponding feedback gain ratio according to the time-varying weight matrix and the characteristic parameters through a preset linear quadratic regulator;

step S33, determining a corresponding target corner according to the feedback gain rate and the current state quantity, and performing change rate limit processing on the target corner to obtain a corresponding corrected front wheel corner;

and step S34, carrying out amplitude limiting processing on the corrected front wheel steering angle, determining a corresponding target front wheel steering angle, and sending a signal of the target front wheel steering angle to an actuator of the unmanned mine car so as to carry out backing control on the unmanned mine car.

The embodiment sets a corresponding time-varying weight matrix according to the current state quantity; calculating a corresponding feedback gain rate according to the time-varying weight matrix and the characteristic parameters of the state space model and through a preset linear quadratic regulator; determining a corresponding target corner according to the feedback gain rate and the current state quantity, and carrying out change rate limit processing on the target corner to obtain a corresponding corrected front wheel corner; carrying out amplitude limiting processing on the corrected front wheel steering angle, determining a corresponding target front wheel steering angle, and sending a signal of the target front wheel steering angle to an actuator of the unmanned mine car so as to carry out backing control on the unmanned mine car; thereby realizing the control precision of the backing of the unmanned mine car.

The respective steps will be described in detail below:

and step S31, setting a corresponding time-varying weight matrix according to the current state quantity.

In this embodiment, according to the current state quantity X, a time-varying weight matrix corresponding to the current state quantity X is set, where the time-varying weight matrix includes a Q matrix and an R matrix, and an expression of the time-varying weight matrix is as follows:

R＝r

The weight of (c).

Wherein q is ₁ 、q ₂ 、q ₃ And q is ₄ The larger the value of the weight is, the higher the control degree of the control system of the unmanned mine car on the state quantity is; i.e. by adjusting q ₁ 、q ₂ 、q ₃ And q is ₄ Can be adjusted to haveThe reversing control precision of the man-and-car vehicle. R is a weight corresponding to the input of the state space model, i.e., the turning angle of the steered wheel, and the larger the weight is, the larger the limit on the turning angle of the steered wheel is, i.e., the smaller the steering angle is. Because the Q matrix and the R matrix only need to consider the relative relation during the design, the R is set as a constant value, and the weight matrix Q is designed in a time-varying manner.

For lateral error e _y Error e from course angle _ψ Corresponding weight q ₁ And q is ₃ If q is ₁ And q is ₃ Too large, it may cause an overshoot of the control system of the unmanned tramcar; if q is ₁ And q is ₃ If it is too small, the adjustment time is long. In the process of backing a car, the heading of the car should be corrected as soon as possible in the early stage of backing a car, and the position of the car head should be adjusted, namely the heading angle error e is emphasized more _ψ The course angle error e should be properly increased _ψ Weight q of ₃ (ii) a In the later stage of backing a car, in order to avoid the collision with other vehicles or fixed obstacles, the high tracking precision of the vehicles is ensured, namely the transverse error e is emphasized _y Weighting, thus raising the lateral error weight q appropriately ₁ 。

In order to avoid overlarge parameter adjusting difficulty caused by excessive control parameters of the unmanned mine car and ensure the change rate of the transverse error

And rate of change of course angle error

Small, design lateral error rate of change

Rate of change of angle error with heading

Corresponding weight q ₂ And q is ₄ Is a fixed value.

And step 32, calculating a corresponding feedback gain ratio through a preset linear quadratic regulator according to the time-varying weight matrix and the characteristic parameters.

In this embodiment, the state space model includes characteristic parameters, wherein the expression of the state space model is:

the characteristic parameters are preferably parameters a and B in the state space model. The preset linear quadratic regulator is preferably a linear quadratic regulator.

The time-varying weight matrix comprises a Q matrix and an R matrix; on the basis, according to the linear quadratic regulator theory, calculating the corresponding feedback gain rate, wherein the specific calculation mode is as follows:

solving the Riccati equation by iteration, wherein the Riccati equation has the following expression:

P＝A ^T PA-A ^T PB(R+B ^T PB) ^-1 B ^T PA+Q

wherein the maximum iteration frequency is set to be 150 times, and the iteration limit difference is set to be 0.01. And setting the initial iteration value of the matrix P as Q, and exiting iteration when the maximum iteration times or the iteration limit difference is reached through repeated iteration.

After the iteration is completed, the feedback gain ratio K can be obtained by the following formula, and the calculation mode of the feedback gain ratio K is as follows:

K＝(R+B ^T PB) ^-1 B ^T PA

where K represents the feedback gain ratio and A represents the parameter A, B in the state space model represents the R matrix in the time varying weight matrix represented by the parameter B, R in the state space model.

And step 33, determining a corresponding target corner according to the feedback gain rate and the current state quantity, and performing change rate limit processing on the target corner to obtain a corresponding corrected front wheel corner.

In this embodiment, a corresponding target steering angle δ is determined according to the feedback gain ratio K and the current state quantity X, and the target steering angle δ is calculated as follows:

δ＝-KX

where δ represents a target steering angle, K represents a feedback gain rate, and X represents a current state quantity.

For safety, the steering wheel angle needs to be limited:

carrying out the limiting value processing of the change rate on the target corner delta to obtain the corresponding corrected front wheel corner delta (kT), wherein the specific processing process is as follows: note that the front wheel steering angle at the previous time is δ [ (k-1) T ], the steering wheel steering angle at this time is δ (kT), and the front wheel steering angle change amplitude in the adjacent calculation cycle is Δ δ. The expression of the corrected front wheel angle is as follows:

where δ (kT) represents the corrected front wheel steering angle, Δ δ represents the front wheel steering angle change amplitude of the adjacent calculation cycle, and δ [ (k-1) T ] represents the front wheel steering angle at the previous time.

And step 34, carrying out amplitude limiting processing on the corrected front wheel steering angle, determining a corresponding target front wheel steering angle, and sending a signal of the target front wheel steering angle to an actuator of the unmanned mine car so as to carry out backing control on the unmanned mine car.

In this embodiment, the amplitude limiting process is performed on the corrected front wheel steering angle to determine a corresponding target front wheel steering angle δ (kT), and the specific process is as follows: recording the maximum value of front wheel steering angle as delta _max Taking 40 degrees generally; minimum value of front wheel steering angle delta _min Typically-40. The expression of the target front wheel steering angle δ (kT) is as follows:

where δ (kT) is expressed as a target front wheel steering angle δ _max Expressed as the maximum value of the front wheel steering angle, delta _min Expressed as the front wheel steering angle minimum.

After a target front wheel steering angle delta (kT) is obtained, sending a signal of the target front wheel steering angle delta (kT) to an actuator of the unmanned mine car so as to carry out backing control on the unmanned mine car; thereby realizing the control precision of the backing of the unmanned mine car.

In the embodiment, a corresponding time-varying weight matrix is set according to the current state quantity; calculating corresponding feedback gain through a preset linear quadratic regulator according to the time-varying weight matrix and the characteristic parameters of the state space model; determining a corresponding target corner according to the feedback gain and the current state quantity, and carrying out change rate limit processing on the target corner to obtain a corresponding corrected front wheel corner; carrying out amplitude limiting processing on the corrected front wheel steering angle, determining a corresponding target front wheel steering angle, and sending a signal of the target front wheel steering angle to an actuator of the unmanned mine car so as to carry out backing control on the unmanned mine car; thereby realizing the control precision of the backing of the unmanned mine car.

The invention also provides a reversing control device. Referring to fig. 10, the reverse control apparatus of the present invention includes:

the determining module 10 is used for determining a corresponding state space model based on a pre-constructed reversing dynamics model and a pre-constructed error change rate model, wherein the reversing dynamics model is established based on a linear two-degree-of-freedom model of the unmanned mine car, and the error change rate model is established based on the transverse error change rate and the course angle error change rate of the unmanned mine car;

the acquisition module 20 is configured to acquire current pose information and backing reference path information of the unmanned mining vehicle, and determine a current state quantity of the unmanned mining vehicle according to the current pose information and the backing reference path information;

and the control module 30 is used for setting a corresponding time-varying weight matrix based on the current state quantity, and determining a target front wheel corner based on a preset linear quadratic regulator and the state space model so as to control the backing of the unmanned mine car.

In addition, the present invention also provides a medium, which is a computer readable storage medium, and the reverse control program is stored on the medium, and when being executed by a processor, the reverse control program realizes the steps of the reverse control method.

The method implemented when the reversing control program running on the processor is executed may refer to each embodiment of the reversing control method of the present invention, and details are not described herein.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims

1. A reverse control method is characterized by comprising the following steps:

2. The reverse control method according to claim 1, wherein prior to the step of determining the corresponding state space model based on the pre-constructed reverse dynamics model and the pre-constructed error rate of change model, the reverse control method further comprises:

3. The reverse control method according to claim 1, wherein the step of determining a corresponding state space model based on a pre-constructed reverse dynamics model and a pre-constructed error rate of change model comprises:

analyzing the error change rate model to obtain an analytical expression of the transverse error change rate and the course angle error change rate;

4. The reverse control method according to claim 1, wherein the step of determining the current state quantity of the unmanned mining vehicle from the current pose information and the reverse reference path information includes:

traversing reference path points in the backing reference path information according to the current pose information, and determining the reference path point closest to the center of mass point of the vehicle as a path projection point;

acquiring a calculation period of the unmanned mine car, a transverse error of a previous calculation period and a course angle error of the previous calculation period, and determining a corresponding transverse error change rate and a corresponding course angle error change rate according to the calculation period, the transverse error of the previous calculation period, the course angle error of the previous calculation period, the transverse error of the previous calculation period and the course angle error;

5. The method of claim 1, wherein the spatial state model includes characteristic parameters, and the step of setting a corresponding time-varying weight matrix based on the current state quantities and determining a target front wheel steering angle based on a preset linear quadratic regulator and the state space equation to control the unmanned tramcar to reverse comprises:

6. The reversing control method according to claim 1, wherein after the step of setting a corresponding time-varying weight matrix based on the current state quantity and determining a target front wheel steering angle based on a preset linear quadratic regulator and the state space model to perform reversing control on the unmanned mining vehicle, the reversing control method further comprises:

7. A reverse control apparatus, characterized in that the reverse control apparatus comprises:

8. An apparatus which is a reverse control apparatus, characterized by comprising: a memory, a processor and a reverse control program stored on the memory and executable on the processor, the reverse control program when executed by the processor implementing the steps of the reverse control method according to any one of claims 1 to 6.

9. A medium which is a computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a reverse control program which, when executed by a processor, implements the steps of the reverse control method according to any one of claims 1 to 6.