CN116225000A - Unmanned heavy-duty vehicle for surface mine and path tracking control method and device thereof - Google Patents

Unmanned heavy-duty vehicle for surface mine and path tracking control method and device thereof Download PDF

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CN116225000A
CN116225000A CN202310025988.6A CN202310025988A CN116225000A CN 116225000 A CN116225000 A CN 116225000A CN 202310025988 A CN202310025988 A CN 202310025988A CN 116225000 A CN116225000 A CN 116225000A
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vehicle
heavy
surface mine
path tracking
distance
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胡满江
陈亮
秦兆博
边有钢
谢国涛
王晓伟
秦洪懋
秦晓辉
徐彪
丁荣军
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Hunan University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle

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Abstract

The invention discloses an unmanned heavy-duty vehicle for an open mine and a path tracking control method and device thereof, wherein the method comprises the following steps: and a forward path tracking step: according to preset path information and vehicle state information, controlling path tracking control when the surface mine heavy-load vehicle advances by using a new Stanley controller, wherein the new Stanley controller considers the time lag characteristic of a vehicle steering device, the vehicle size and the forward running speed; and (3) a backward path tracking step: the new rear wheel feedback controller is used for controlling the path tracking control when the surface mine heavy-load vehicle backs, and the new rear wheel feedback controller considers the time lag characteristic of the steering gear of the vehicle, the size of the vehicle and the back-driving speed. The invention can realize the path tracking control of the heavy-duty vehicle in the forward and backward directions, and carry out self-adaptive adjustment on the control parameters under different working conditions so as to achieve better control effect.

Description

Unmanned heavy-duty vehicle for surface mine and path tracking control method and device thereof
Technical Field
The invention relates to the technical field of automatic driving, in particular to an unmanned heavy-duty vehicle for an open mine and a path tracking control method and device thereof.
Background
As one of the key links of the unmanned system of the surface mine, the performance of path tracking control directly influences the operation safety and the transportation efficiency of the unmanned vehicle, and has important academic research significance and social and economic values. Classical path-tracking control algorithms include PID (Proportional Integral Derivative, proportional-integral-derivative control), pure tracking, stanley, etc. PID control parameters have important influence on control effects, and optimal effects can be obtained by setting PID parameters based on a model under ideal conditions, but when the model is uncertain, a trial-and-error method is generally adopted for setting, so that the workload is high. In addition, PID cannot be compensated for in a targeted manner when system uncertainty and external disturbances are present at the same time. The pure tracking control algorithm is a classical path tracking control algorithm, the core idea is based on a vehicle monorail model, the center of a rear axle of a vehicle is taken as a tangent point, the longitudinal center line is taken as a tangent line, and a self-vehicle is driven along an arc passing through a pre-aiming point by controlling the front wheel steering angle, so that the control method is based on geometric tracking. The pure tracking algorithm has good robustness to road curvature disturbance, but the tracking performance of the pure tracking algorithm is seriously dependent on the selection of a pretightening distance, and the optimal performance is difficult to guarantee.
With the development of artificial intelligence, many intelligent control algorithms are also applied in the unmanned path tracking control field, such as data driving, neural networks, and the like. However, the control precision of the intelligent control algorithms is seriously dependent on mass data, and the dynamic behavior of the system cannot be further predicted and analyzed. The MPC (Model Predictive Control ) is widely applied to unmanned path tracking control and has significant advantages for mine card path tracking control. The model predictive controller is a multivariable controller which can control the complex multiple-input multiple-output system of the mine truck. However, the calculation amount of the MPC algorithm is large, the calculation time is long, and the real-time performance of the algorithm is required by the automatic driving automobile, so that the method is difficult to directly use for the actual automobile. In order to solve the practical problem encountered in the engineering application, a method and a system for controlling the path tracking of the unmanned heavy-duty vehicle in the surface mine are researched.
Disclosure of Invention
It is an object of the present invention to provide an unmanned heavy-duty vehicle for an open mine and a path tracking control method, apparatus and system therefor, which overcome or at least alleviate at least one of the above-mentioned drawbacks of the prior art.
In order to achieve the above purpose, the invention provides a method for controlling the path tracking of an unmanned heavy-duty vehicle in a surface mine, which comprises the following steps:
and a forward path tracking step: according to the preset path information and vehicle state information, a new Stanley controller shown in the following formula (1) is used for controlling path tracking control when the surface mine heavy-load vehicle advances, and the new Stanley controller considers the time lag characteristic of the steering gear, the vehicle size and the forward running speed of the vehicle:
Figure BDA0004044606930000021
in delta c For front wheel steering angle command e p V is the lateral distance error f For the forward running speed of the vehicle,
Figure BDA0004044606930000022
for angle error, Δt is the system sampling time, τ δ K is self-adaptive adjustment control gain for time lag factor,)>
Figure BDA0004044606930000023
For the forward acceleration of the vehicle, delta is the front wheel angle of the vehicle, C rp Curvature corresponding to the nearest path point;
and (3) a backward path tracking step: the method comprises the following steps of controlling path tracking control when a surface mine heavy-duty vehicle backs by using a new rear wheel feedback controller, wherein the new rear wheel feedback controller considers the time lag characteristic of a steering gear of the vehicle, the size of the vehicle and the back driving speed:
Figure BDA0004044606930000024
in delta c Is a front wheel steering angle command, L is an wheelbase, c r For the curvature corresponding to the nearest path point,
Figure BDA0004044606930000025
for the rate of change of the curvature corresponding to the nearest waypoint, < ->
Figure BDA0004044606930000026
E is yaw angle error r Is a lateral distance error>
Figure BDA0004044606930000027
Is the scale factor corresponding to yaw angle error, k e For the corresponding proportion shadow of the transverse distance error, tau δ As a time lag factor, v r Vehicle reverse travel speed of positive value, +.>
Figure BDA0004044606930000028
Is the vehicle yaw rate.
Further, the new Stanley controller also determines the pretightening distance d according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using the dynamic selection method provided by the following formulas (6) to (8) p ：
d p ＝max{d pv ，d pc } (6)
d pv ＝k pv v f Δt (7)
Figure BDA0004044606930000029
Wherein d pv According to v f The obtained pretighted distance, k pv Is a scale factor, d pc According to c rp Calibrated pretarget distance d hc 、d mc 、d lc Respectively C according to different numerical values rp Calibrated pretarget distance.
Further, the new Stanley controller also determines an adaptive adjustment control gain k according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using the following formula (11):
Figure BDA0004044606930000031
wherein, kappa 1 And kappa (kappa) 2 Is a dimensionless scale factor.
Further, the new rear wheel feedback controller also determines the pre-aiming distance according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using a dynamic selection method provided by the following formula (12):
Figure BDA0004044606930000032
wherein d pr According to C rp Calibrated pretarget distance d hr 、d mr 、d lr Respectively c according to different values rp Calibrated pretarget distance.
The invention also provides a path tracking control device of the unmanned heavy-duty vehicle in the surface mine, which comprises the following components:
a new Stanley controller for controlling a path-following control when the surface mine heavy-duty vehicle advances according to vehicle information and running characteristics of the surface mine heavy-duty vehicle, the new Stanley controller taking into consideration a vehicle steering time lag characteristic, as shown in the following formula (1):
Figure BDA0004044606930000033
in delta c For front wheel steering angle command e p V is the lateral distance error f For the forward speed of the vehicle,
Figure BDA0004044606930000034
for angle error, Δt is the system sampling time, τ δ K is self-adaptive adjustment control gain for time lag factor,)>
Figure BDA0004044606930000035
For the forward acceleration of the vehicle, δ is the front wheel angle of the vehicle, c rp Curvature corresponding to the nearest path point;
a new rear wheel feedback controller for controlling a path following control when the surface mine heavy-duty vehicle backs, the new rear wheel feedback controller taking into consideration a vehicle steering time lag characteristic and a vehicle backing characteristic, as shown in the following formula:
Figure BDA0004044606930000036
in delta c Is a front wheel steering angle command, L is an wheelbase, c r For the curvature corresponding to the nearest path point,
Figure BDA0004044606930000037
for the rate of change of the curvature corresponding to the nearest waypoint, < ->
Figure BDA0004044606930000038
E is yaw angle error r Is a lateral distance error>
Figure BDA0004044606930000039
Is the scale factor corresponding to yaw angle error, k e For the corresponding proportion shadow of the transverse distance error, tau δ As a time lag factor, v r Vehicle reverse travel speed of positive value, +.>
Figure BDA0004044606930000041
Is the vehicle yaw rate.
Further, the new Stanley controller also determines the pretightening distance d according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using the dynamic selection method provided by the following formulas (6) to (8) p ：
d p ＝max{d pv ，d pc } (6)
d pv ＝k pv v f Δt (7)
Figure BDA0004044606930000042
Wherein d pv According to v f The obtained pretighted distance, k pv Is a scale factor, d pc According to c rp Calibrated pretarget distance d hc 、d mc 、d lc Respectively c according to different values rp Calibrated pretarget distance.
Further, the new Stanley controller also determines an adaptive adjustment control gain k according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using the following formula (11):
Figure BDA0004044606930000043
wherein, kappa 1 And kappa (kappa) 2 Is a dimensionless scale factor.
Further, the new rear wheel feedback controller also determines the pre-aiming distance according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using a dynamic selection method provided by the following formula (12):
Figure BDA0004044606930000044
wherein d pr According to c rp Calibrated pretarget distance d hr 、d mr 、d lr Respectively c according to different values rp Calibrated pretarget distance.
The invention also provides an unmanned heavy-duty vehicle for the surface mine, which comprises a vehicle body, wherein the size and the structure of the vehicle body are as follows: the length of the vehicle body is 14.75 meters, the width of the vehicle body is 7.44 meters, the ground clearance of the front bumper is 1.42 meters, the wheelbase is 6.35 meters, the front suspension length is 4.25 meters, the rear suspension length is 3.43 meters, the maximum rotation angle of the front wheel is 31 degrees, the forward running speed range of the vehicle is 0-30 kilometers per hour, and the backward running speed range of the vehicle is 0-10 kilometers per hour; it also includes:
the inertial navigation combined equipment is used for acquiring vehicle state information;
an unmanned computing platform which is provided with the surface mine unmanned heavy-duty vehicle path tracking control device in advance and calculates a front wheel steering angle command delta c And will delta c Transmitting to a vehicle drive-by-wire interface unit;
steering-by-wire unit for receiving delta received over can bus c And according to delta c The vehicle is controlled to travel along a desired path.
Further, the steer-by-wire unit comprises a full hydraulic steering gear with an electrical control system.
According to the invention, as the time lag characteristic of the steering gear of the vehicle is considered aiming at the operation working condition of the unmanned heavy-duty vehicle in the surface mine, a new Stanley controller and a new rear wheel feedback controller are provided, so that the path tracking control of the heavy-duty vehicle in the forward and backward directions is realized, the control parameters under different working conditions are adaptively adjusted, and a better control effect is achieved.
Drawings
Fig. 1 is a schematic diagram of connection relationships between modules according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of the size and structure of a surface mine heavy-duty vehicle to which the present invention is applicable.
Fig. 3 is a schematic diagram of a frame principle of path tracking control of an unmanned heavy-duty vehicle in an open mine according to an embodiment of the invention.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings and examples.
The embodiment of the invention provides a method and a system for controlling the path tracking of an unmanned heavy-duty vehicle in an open-pit mine, which are used for respectively designing a path tracking controller responsible for forward and reverse by utilizing a Stanley and rear wheel feedback model by considering the time lag characteristic of a steering actuator of the heavy-duty vehicle, and performing pre-aiming and control parameter setting aiming at the road environment, the heavy-duty vehicle and the reference track characteristic of the open-pit mine, so as to finally realize the accurate path tracking control of the unmanned heavy-duty vehicle in the open-pit mine.
As shown in fig. 1, the method for controlling path tracking of unmanned heavy-duty vehicles in surface mine provided by the embodiment of the invention comprises the following steps:
and a forward path tracking step: according to the preset path information and vehicle state information, a new Stanley controller shown in the following formula (1) is used for controlling path tracking control when the surface mine heavy-load vehicle advances, and the new Stanley controller considers the time lag characteristic of the steering gear, the vehicle size and the forward running speed of the vehicle:
Figure BDA0004044606930000051
in delta c For front wheel steering angle command e p V is the lateral distance error f For the forward running speed of the vehicle,
Figure BDA0004044606930000052
for angle error, Δt is the system sampling time, τ δ As a time lag factor, τ δ The value of (2) is obtained through calibration, the time lag factor of the open-air heavy-duty vehicle is approximately equal to 1 second, k is the self-adaptive adjustment control gain, and +.>
Figure BDA0004044606930000053
For the forward acceleration of the vehicle, δ is the front wheel angle of the vehicle, c rp Is the curvature corresponding to the nearest path point. />
And (3) a backward path tracking step: the method comprises the following steps of controlling path tracking control when a surface mine heavy-duty vehicle backs by using a new rear wheel feedback controller, wherein the new rear wheel feedback controller considers the time lag characteristic of a steering gear of the vehicle, the size of the vehicle and the back driving speed:
Figure BDA0004044606930000061
in delta c Is a front wheel steering angle command, L is an wheelbase, c r For the curvature corresponding to the nearest path point,
Figure BDA0004044606930000062
for the rate of change of the curvature corresponding to the nearest waypoint, < ->
Figure BDA0004044606930000063
E is yaw angle error r Is a lateral distance error>
Figure BDA0004044606930000064
Is a scale factor corresponding to yaw angle error, and k is expressed by the following formula (3) e As a proportional shadow corresponding to the lateral distance error, τ is represented by the following formula (4) δ As a time lag factor, v r Vehicle reverse travel speed of positive value, +.>
Figure BDA0004044606930000065
Is the vehicle yaw rate.
Figure BDA0004044606930000066
k e ＝a 2 (4)
Where a is a positive number and ζ is a damping coefficient, for example: ζ=1.85, a=0.28.
In one embodiment, the closest waypoint corresponds to curvature c r Is differentiated positive and negative according to the specific numerical value of the steering wheel.
In the above embodiment, the nearest waypoint selection angle constraint is set to the following formula (5):
Figure BDA0004044606930000067
wherein,,
Figure BDA0004044606930000068
for the waypoint heading angle from the path information, +.>
Figure BDA0004044606930000069
Is the yaw angle of the vehicle from the inertial navigation assembly.
Based on the forward travel speed feedback of the vehicle from inertial navigation and the curvature of the nearest waypoint from the route information, the nearest waypoint is determined by the formula (5), and the information contained in the waypoint is: coordinates, heading angle, curvature, speed. The nearest path point is found out through the coordinates and course angle information of the path point, and then all the information of the nearest path point is used for path tracking control.
In one embodiment, the new Stanley controller also determines the pretightening distance d based on the vehicle information and driving characteristics of the surface mine heavy load vehicle using the dynamic selection method provided by formulas (6) through (8) below p ：
d p ＝max{d pv ，d pc } (6)
d pv ＝k pv v f Δt (7)
Figure BDA00040446069300000610
Wherein d pv According to v f The obtained pretighted distance, k pv For example, the value of the scale factor can be 0.5, d pc According to c rp Calibrated pretarget distance d hc 、d mc 、d lc Respectively c according to different values rp Calibrated pretarget distance.
According to the pretarget distance d p Selecting a pre-aiming point: sequentially to the traveling directionTraversing the path points until a path point is found, wherein the distance between the path point and the nearest path point is larger than or equal to the pretightening distance after all traversed path points are added up, and the path point is the pretightening point.
Then the angle error is calculated by the following formula (9)
Figure BDA0004044606930000071
Then the transverse distance error e is calculated by using the following formula (10) p ：
Figure BDA0004044606930000072
Wherein,,
Figure BDA0004044606930000073
for the yaw angle of the vehicle->
Figure BDA0004044606930000074
Is the heading angle of the pretarget point.
Figure BDA0004044606930000075
Wherein x is 0 And y 0 Respectively the horizontal and vertical coordinates, x of the center of the front axle of the vehicle in the global coordinate system p And y p Is the horizontal and vertical coordinates of the pretightening point in the global coordinate system.
In general, k can be specified by a specific value of experimental calibration. However, in one embodiment, to ensure path tracking accuracy, the control gain k is adaptively adjusted according to the pre-aiming path point curvature and the lateral distance error, as shown in the following equation (11):
Figure BDA0004044606930000076
wherein, kappa 1 And kappa (kappa) 2 For a dimensionless scale factor, the specific values of the two are usually empirical values, such as: kappa (kappa) 1 ＝12，κ 2 ＝0.15。
In one embodiment, the new rear wheel feedback controller also determines the pre-aiming distance based on the vehicle information and the driving characteristics of the surface mine heavy load vehicle using a dynamic selection method provided by the following equation (12):
Figure BDA0004044606930000077
wherein d pr According to c rp Calibrated pretarget distance d hr 、d mr 、d lr Respectively c according to different values rp Calibrated pretarget distance.
According to the pretarget distance d pr Selecting a pre-aiming point, and calculating a transverse distance error e by using the following formula (13) r ：
Figure BDA0004044606930000078
Wherein x is r And y r Respectively the horizontal and vertical coordinates, x of the center of the rear axle of the vehicle in the global coordinate system pr And y pr Is the horizontal and vertical coordinates of the pretightening point in the global coordinate system.
The invention also provides a path tracking control device of the unmanned heavy-duty vehicle of the surface mine, which comprises a new Stanley controller and a new rear wheel feedback controller, wherein:
the new Stanley controller is used for controlling the path tracking control of the surface mine heavy-duty vehicle when advancing according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle, and the new Stanley controller considers the time lag characteristics of the vehicle steering device as shown in the above formula (1).
The new rear wheel feedback controller is used for controlling the path tracking control when the surface mine heavy-duty vehicle backs, and the new rear wheel feedback controller considers the time lag characteristic of the steering device of the vehicle and the characteristic when the vehicle backs, and is shown in the above formula.
The embodiment of the invention also provides an unmanned heavy-duty vehicle for the surface mine, which comprises a vehicle body. As shown in fig. 2, the vehicle body has a dimensional structure of: the length of the vehicle body is 14.75 meters, the width of the vehicle body is 7.44 meters, the ground clearance of the front bumper is 1.42 meters, the wheelbase is 6.35 meters, the front suspension length is 4.25 meters, the rear suspension length is 3.43 meters, the maximum rotation angle of the front wheel is 31 degrees, the forward running speed of the vehicle is in the range of 0-30 kilometers per hour, and the backward running speed of the vehicle is in the range of 0-10 kilometers per hour.
As shown in fig. 3, the surface mine unmanned heavy-duty vehicle provided by the embodiment of the invention further comprises an inertial navigation combined device, an unmanned computing platform and a steer-by-wire unit, wherein:
the inertial navigation combined equipment is used for acquiring vehicle state information;
the unmanned computing platform is provided with the surface mine unmanned heavy-duty vehicle path tracking control device in advance, and calculates the front wheel steering angle command delta c And will delta c To the vehicle drive-by-wire interface unit.
The steer-by-wire unit is used for receiving delta through can bus c And according to delta c The vehicle is controlled to travel along a desired path. In this embodiment, the steer-by-wire unit comprises a full hydraulic steering with an electrical control system.
The path tracking controller in each of the above embodiments is designed based on Stanley and rear wheel feedback algorithm, and may be replaced with "path tracking control based on vehicle dynamics model".
Finally, it should be pointed out that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting. Those of ordinary skill in the art will appreciate that: the technical schemes described in the foregoing embodiments may be modified or some of the technical features may be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. The unmanned heavy-duty vehicle path tracking control method for the surface mine is characterized by comprising the following steps of:
and a forward path tracking step: according to the preset path information and vehicle state information, a new Stanley controller shown in the following formula (1) is used for controlling path tracking control when the surface mine heavy-load vehicle advances, and the new Stanley controller considers the time lag characteristic of the steering gear, the vehicle size and the forward running speed of the vehicle:
Figure FDA0004044606920000011
in delta c For front wheel steering angle command e p V is the lateral distance error f For the forward running speed of the vehicle,
Figure FDA0004044606920000012
for angle error, Δt is the system sampling time, τ δ K is self-adaptive adjustment control gain for time lag factor,)>
Figure FDA0004044606920000013
For the forward acceleration of the vehicle, δ is the front wheel angle of the vehicle, c rp Curvature corresponding to the nearest path point;
and (3) a backward path tracking step: the method comprises the following steps of controlling path tracking control when a surface mine heavy-duty vehicle backs by using a new rear wheel feedback controller, wherein the new rear wheel feedback controller considers the time lag characteristic of a steering gear of the vehicle, the size of the vehicle and the back driving speed:
Figure FDA0004044606920000014
in delta c Is a front wheel steering angle command, L is an wheelbase, c r For the curvature corresponding to the nearest path point,
Figure FDA0004044606920000015
for the rate of change of the curvature corresponding to the nearest waypoint, < ->
Figure FDA0004044606920000016
E is yaw angle error r Is a lateral distance error>
Figure FDA0004044606920000017
Is the scale factor corresponding to yaw angle error, k e For the corresponding proportion shadow of the transverse distance error, tau δ As a time lag factor, v r Vehicle reverse travel speed of positive value, +.>
Figure FDA0004044606920000018
Is the vehicle yaw rate.
2. The method for controlling path tracking of unmanned heavy-duty vehicle in surface mine as set forth in claim 1, wherein the new Stanley controller further determines the pretightening distance d based on the vehicle information and the driving characteristics of the heavy-duty vehicle in surface mine by using the dynamic selection method provided by the following formulas (6) to (8) p ：
d p ＝max{d pv ，d pc } (6)
d pv ＝k pv v f Δt (7)
Figure FDA0004044606920000021
Wherein d pv According to v f The obtained pretighted distance, k pv Is a scale factor, d pc According to c rp Calibrated pretarget distance d hc 、d mc 、d lc Respectively c according to different values rp Calibrated pretarget distance.
3. The surface mine unmanned heavy-duty vehicle path tracking control method according to claim 2, wherein the new Stanley controller further determines the adaptive adjustment control gain k according to the vehicle information and the running characteristics of the surface mine heavy-duty vehicle using the following formula (11):
Figure FDA0004044606920000022
wherein, kappa 1 And kappa (kappa) 2 Is a dimensionless scale factor.
4. A surface mine unmanned heavy-duty vehicle path tracking control method as set forth in any one of claims 1-3, wherein the new rear wheel feedback controller further determines the pre-aiming distance based on vehicle information and driving characteristics of the surface mine heavy-duty vehicle using a dynamic selection method provided by the following equation (12):
Figure FDA0004044606920000023
wherein d pr According to c rp Calibrated pretarget distance d hr 、d mr 、d lr Respectively c according to different values rp Calibrated pretarget distance.
5. An unmanned heavy-duty vehicle path tracking control device for a surface mine, comprising:
a new Stanley controller for controlling a path-following control when the surface mine heavy-duty vehicle advances according to vehicle information and running characteristics of the surface mine heavy-duty vehicle, the new Stanley controller taking into consideration a vehicle steering time lag characteristic, as shown in the following formula (1):
Figure FDA0004044606920000024
in delta c For front wheel steering angle command e p V is the lateral distance error f For the forward speed of the vehicle,
Figure FDA0004044606920000025
for angle error, Δt is the system sampleTime τ δ K is self-adaptive adjustment control gain for time lag factor,)>
Figure FDA0004044606920000026
For the forward acceleration of the vehicle, δ is the front wheel angle of the vehicle, c rp Curvature corresponding to the nearest path point;
a new rear wheel feedback controller for controlling a path following control when the surface mine heavy-duty vehicle backs, the new rear wheel feedback controller taking into consideration a vehicle steering time lag characteristic and a vehicle backing characteristic, as shown in the following formula:
Figure FDA0004044606920000031
in delta c Is a front wheel steering angle command, L is an wheelbase, c r For the curvature corresponding to the nearest path point,
Figure FDA0004044606920000032
for the rate of change of the curvature corresponding to the nearest waypoint, < ->
Figure FDA0004044606920000033
E is yaw angle error r Is a lateral distance error>
Figure FDA0004044606920000034
Is the scale factor corresponding to yaw angle error, k e For the corresponding proportion shadow of the transverse distance error, tau δ As a time lag factor, v r Vehicle reverse travel speed of positive value, +.>
Figure FDA0004044606920000035
Is the vehicle yaw rate.
6. The surface mine unmanned heavy-duty vehicle path tracking control device of claim 5, wherein the new Stanley controller is further configured toDetermining the pre-aiming distance d according to the vehicle information and the driving characteristics of the surface mine heavy-duty vehicle by using the dynamic selection method provided by the following formulas (6) to (8) p ：
d p ＝max{d pv ，d pc } (6)
d pv ＝k pv v f Δt (7)
Figure FDA0004044606920000036
Wherein d pv According to v f The obtained pretighted distance, k pv Is a scale factor, d pc According to c rp Calibrated pretarget distance d hc 、d mc 、d lc Respectively c according to different values rp Calibrated pretarget distance.
7. The surface mine unmanned heavy-duty vehicle path tracking control apparatus of claim 6, wherein the new Stanley controller further determines the adaptive adjustment control gain k based on vehicle information and driving characteristics of the surface mine heavy-duty vehicle using the following equation (11):
Figure FDA0004044606920000037
wherein, kappa 1 And kappa (kappa) 2 Is a dimensionless scale factor.
8. The surface mine unmanned heavy-duty vehicle path tracking control apparatus of any one of claims 5 to 7, wherein the new rear wheel feedback controller further determines the pre-aiming distance based on vehicle information and driving characteristics of the surface mine heavy-duty vehicle using a dynamic selection method provided by the following equation (12):
Figure FDA0004044606920000041
wherein d pr According to c rp Calibrated pretarget distance d hr 、d mr 、d lr Respectively c according to different values rp Calibrated pretarget distance.
9. The unmanned heavy-duty vehicle for the surface mine comprises a vehicle body, wherein the size and the structure of the vehicle body are as follows: the length of the vehicle body is 14.75 meters, the width of the vehicle body is 7.44 meters, the ground clearance of the front bumper is 1.42 meters, the wheelbase is 6.35 meters, the front suspension length is 4.25 meters, the rear suspension length is 3.43 meters, the maximum rotation angle of the front wheel is 31 degrees, the forward running speed range of the vehicle is 0-30 kilometers per hour, and the backward running speed range of the vehicle is 0-10 kilometers per hour; characterized by further comprising:
the inertial navigation combined equipment is used for acquiring vehicle state information;
an unmanned computing platform, which is provided with the surface mine unmanned heavy-duty vehicle path tracking control device according to any one of claims 5 to 8 in advance, and calculates a front wheel steering angle command delta c And will delta c Transmitting to a vehicle drive-by-wire interface unit;
steering-by-wire unit for receiving delta received over can bus c And according to delta c The vehicle is controlled to travel along a desired path.
10. The unmanned heavy-duty surface mine vehicle of claim 9, wherein the steer-by-wire unit comprises a full hydraulic steering with an electrical control system.
CN202310025988.6A 2023-01-09 2023-01-09 Unmanned heavy-duty vehicle for surface mine and path tracking control method and device thereof Pending CN116225000A (en)

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