CN113359710B - LOS theory-based agricultural machinery path tracking method - Google Patents

LOS theory-based agricultural machinery path tracking method Download PDF

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CN113359710B
CN113359710B CN202110561035.2A CN202110561035A CN113359710B CN 113359710 B CN113359710 B CN 113359710B CN 202110561035 A CN202110561035 A CN 202110561035A CN 113359710 B CN113359710 B CN 113359710B
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CN113359710A (en
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丁世宏
刘壮壮
魏新华
刘陆
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Jiangsu University
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    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0219Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory ensuring the processing of the whole working surface
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
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Abstract

The invention relates to an agricultural machinery path tracking method based on LOS theory, which belongs to the field of agricultural machinery intelligent control, wherein when an agricultural machinery runs on a set straight path, a navigation positioning module acquires real-time position information of the agricultural machinery; transmitting the position information to an LOS algorithm device through parameters such as coordinates and transverse tracking errors analyzed by an upper computer system to obtain a current driving course angle; and finally, the front wheel feedback controller outputs the wheel steering angle expected by the system according to the course angle and the transverse tracking error, so that the steering deviation angle of the wheels can be obtained, and the steps are repeated to realize path tracking control. The agricultural machinery system based on the LOS navigation method can be suitable for different agricultural machinery operation scenes, effectively solves the problem of overlarge path tracking error, and has the characteristics of robustness, accuracy and the like. The method has clear and simple thought, and can enable the change of the wheel turning angle of the agricultural machinery to be more smooth and stable in the process of tracking the expected path under the condition of external interference or uncertain system model parameters.

Description

LOS theory-based agricultural machinery path tracking method
Technical Field
The invention relates to an agricultural machinery path tracking method based on an LOS theory, and belongs to the technical field of intelligent control of agricultural machinery.
Background
China is a big agricultural country, agriculture is the basis of social and economic development and guarantees of people's material life, in order to promote the improvement of agricultural productivity and realize the development of agricultural modernization, people put forward the concept of precision agriculture, and the concept mainly utilizes the technologies such as navigation satellite positioning technology, sensor technology and remote sensing control to finish the autonomous operation of agricultural machinery, and the purpose of automatic navigation is achieved, so that the farmland farming time is effectively reduced, the farming efficiency is improved, the manpower can be replaced to realize automatic driving, the working fatigue of a driver is relieved, the production accident rate is reduced, and the production safety is improved.
The agricultural machinery path tracking method is used as a key technology of agricultural machinery automatic navigation and is a research hotspot in the technical field of agricultural machinery intelligent control. The existing agricultural machinery path tracking technology mainly depends on the navigation positioning technology of an agricultural machinery upper computer system and the accuracy and hydraulic steering of a lower computer system sensor to control, so that the complexity of system design and the dependency of a control model are greatly increased, the production cost is improved, the production benefit is reduced, and the adaptability of the agricultural machinery operation environment is not strong. Therefore, how to optimize a set of path tracking controller with strong robustness and high accuracy on the premise of simplifying the structure of the agricultural machinery automatic navigation system is a key point for realizing agricultural accuracy and intellectualization.
Disclosure of Invention
The invention provides an agricultural machinery path tracking control method based on LOS theory, which can stably and effectively track and control the path of an unmanned agricultural machinery under the condition of uncertain system model parameters or large disturbance of operating environment, so that the agricultural machinery ensures the stability and the accuracy of a nonlinear feedback controller on the basis of simplifying the structure of an original hardware system.
In order to solve the technical problems, the invention adopts the following technical scheme:
an agricultural machinery path tracking method based on an LOS theory comprises the following steps:
s1, when an agricultural machine runs on a set straight path, acquiring real-time position information of the agricultural machine by a navigation positioning module;
s2, transmitting the position information to an LOS (LOSs of distance) algorithm through parameters such as coordinates and transverse tracking errors analyzed by an upper computer system to obtain a current driving course angle;
and S3, outputting the wheel steering angle expected by the system by the front wheel feedback controller according to the course angle and the transverse tracking error, so that the steering deviation angle of the wheels can be obtained, and repeating the steps to realize path tracking control.
Further, the step S1 specifically includes:
s11, setting the boundary of the agricultural machinery working field through the Beidou RTK positioning module and the vision recognition CDD module, and then dotting to obtain a plurality of parallel linear tracks.
And S12, the Beidou RTK navigation module outputs the position and track point information of the agricultural machine in real time, simultaneously converts the position and track point information of the agricultural machine and three vertex coordinates of the rectangular field block into a Gaussian plane coordinate system, and stores the planned path into a navigation system in a two-dimensional array form to realize navigation path planning.
Further, the step S11 specifically includes:
determining three coordinate vertexes of a test field by using an RTK-CCD positioning vision sensor fusion system to determine a rectangle, and assuming positioning coordinates of head nodes A, B, C and D; taking the longest distance of each operation line as a principle, combining the actual geometric shape of the land, selecting a boundary AD as a datum line of operation line planning, taking the boundary AD as a datum line to define a plurality of parallel operation lines, wherein the parallel line distance is determined according to the operation line spacing, the shortest distance between the last operation line and the boundary BC is not less than 1/2 of the operation spacing, taking the focuses of all Q parallel operation lines and the boundaries AB and CD as planning operation line nodes, and storing the corresponding operation line nodes into a two-dimensional array for being called by navigation control software based on a LOS algorithm.
Further, the step S2 specifically includes:
s21: determining a two-way path point
Figure BDA0003077752650000021
And
Figure BDA0003077752650000022
the defined straight line traces the path, and the origin of the path coordinate system is at
Figure BDA0003077752650000023
The coordinate of the agricultural machine in the coordinate system with the fixed path is p n (t)=[x(t),y(t)]And satisfies the formula:
Figure BDA0003077752650000024
in the formula:
Figure BDA0003077752650000025
α k =atan2(y k+1 -y k ,x k+1 -x k )∈S;
α k for the north and the south of the geodetic coordinate system and the expected path P k And P k+1 A is a coefficient;
s22: let ε (t) = [ s (t), e (t) ]] T ∈R 2 Wherein:
s(t)=[x(t)-x k ]cos(α k )+[y(t)-y k ]sin(α k )
e(t)=-[x(t)-x k ]sin(α k )+[y(t)-y k ]cos(α k )
s (t) is the tracking distance of the agricultural machinery path, e (t) is the transverse tracking error, and in the actual path tracking process, only the transverse deviation of the travel of the agricultural machinery itself needs to be concerned, because when the transverse deviation e (t) =0, the agricultural machinery is converged on the expected tracking path, the path tracking control target is as follows:
Figure BDA0003077752650000031
s23: the LOS navigation algorithm is set as follows:
Figure BDA0003077752650000032
in the formula:
Figure BDA0003077752650000033
Figure BDA0003077752650000034
is the speed-path correlation angle, where Δ is the forward-looking distance of the agricultural machine and e is the lateral tracking error;
if the agricultural machinery is used as the driving direction angle
Figure BDA0003077752650000035
The course angle is:
Figure BDA0003077752650000036
further, the step S3 specifically includes:
s31: the method comprises the following steps of acquiring information such as real-time positions, wheel speeds and corners of agricultural machinery through a navigation positioning system and a pose acquisition system respectively, and performing kinematic modeling by combining structural parameters of the agricultural machinery and a two-degree-of-freedom model theory, wherein the kinematic modeling specifically comprises the following steps:
considering the path tracking process of the agricultural machinery as low-speed motion in an X-Y plane coordinate system, the following results are obtained according to the upper triangular chord and the lower triangular chord theorem:
Figure BDA0003077752650000037
wherein delta f 、δ r Respectively a front wheel corner and a rear wheel corner; l f 、l r Respectively a front wheel base and a rear wheel base; beta is the direction angle of the running speed of the agricultural machine; r is a turning radius;
two-way degeneracy is multiplied on both sides
Figure BDA0003077752650000041
Obtaining:
Figure BDA0003077752650000042
under the condition of low-speed running working condition of the agricultural machinery, the change rate of the vehicle direction is as follows:
Figure BDA0003077752650000043
namely that
Figure BDA0003077752650000044
Since the agricultural machinery does not take into account the rear wheel steering situation, i.e. tan (delta) r ) When the color is =0, finishing:
Figure BDA0003077752650000045
wherein
Figure BDA0003077752650000046
Is a course angle, v is a running speed, and delta is a front wheel rotation angle;
in a low-speed working environment, assuming that a wheel rotation angle direction is consistent with a speed direction, namely δ = β, a kinematic model is:
Figure BDA0003077752650000047
s32: the front wheel steering angle can be obtained according to the steering characteristics of the agricultural machinery:
Figure BDA0003077752650000048
wherein
Figure BDA0003077752650000049
The course angle can be obtained by an LOS algorithm; delta e (t) is the steering deviation angle;
the larger the lateral tracking error e (t) and the larger the front wheel steering angle without considering the driving tracking deviation, the following nonlinear proportional function is obtained according to the geometrical relationship, assuming that the expected trajectory of the vehicle intersects the nearest tangent on a given path from the front wheel extension line d (t):
Figure BDA0003077752650000051
where d (t) is related to vehicle speed, represented by vehicle speed v (t) and gain parameter k.
The front wheel steering deviation angle coincides with the desired path tangent direction without taking into account the lateral tracking error, i.e. in the absence of lateral error the front wheel direction is the same as the desired path direction:
Figure BDA0003077752650000052
as the lateral tracking error increases, the non-linear proportional function produces a front wheel slip angle that points directly to the desired path, and:
Figure BDA0003077752650000053
in order to enable the two differential equations to have global gradual stable balance at the zero point error junction, the nonlinear front wheel feedback controller is designed by integrating two control factors as follows:
Figure BDA0003077752650000054
and from the geometrical relationships:
Figure BDA0003077752650000055
therefore, it is possible to
Figure BDA0003077752650000056
Therefore, the convergence rate of e (t) is between the linear convergence rate of v (t) and the exponential convergence rate of gain parameter k, and when the lateral tracking error e (t) is small, (ke (t)/v (t)) 2 Approaching 0, then
Figure BDA0003077752650000057
Integration can give:
e(t)=e(0)*exp -kt
Figure BDA0003077752650000058
for any transverse error, the differential equation is monotonously converged to 0, and the path tracking control target is realized.
And further, wheel steering deviation information obtained by the navigation controller is transmitted to an agricultural machinery lower computer system, the real deviation value is corrected by the values of the steering sensor and the photoelectric encoder, and the corrected deviation value is transmitted to a control mechanism hydraulic system to control the flow and the flow direction of the hydraulic system, so that the steering of the wheels is finally controlled, and the vehicle can run according to a set route.
Through the technical scheme, compared with the prior art, the invention has the following beneficial effects:
in order to solve the problems of poor adaptability, complex system design and unstable control of the agricultural machinery path tracking technology, the invention discloses an agricultural machinery path tracking method based on an LOS theory; the course angle tracked by the agricultural machinery path is obtained by using the LOS algorithm, and the tracking path target point can be automatically switched, so that the updating of state parameters such as the transverse tracking error and the like input by the current controller is ensured, the real-time control on the steering is realized, and the expected tracking path can be converged quickly and stably; and the LOS algorithm does not depend on a system parameter model, can output an accurate agricultural machinery course angle when external disturbance is large, enhances the adaptability of the agricultural machinery operating environment by combining the designed front wheel feedback nonlinear controller, simplifies the whole control system frame, has high robustness and is suitable for agricultural machinery.
Drawings
FIG. 1 is a diagram of a path tracking system of agricultural machinery based on LOS theory;
FIG. 2 is a LOS control algorithm schematic;
FIG. 3 is a diagram of an agricultural machinery kinematics model;
FIG. 4 is a simulation comparison of two system control methods; (a) comparing the expected tracking path with the actual tracking path; (b) The path is traced for the desired trace and based on the LOS method.
Detailed Description
So that the manner in which the features and advantages of the invention, as well as the manner in which the above recited features and functions are attained and can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings.
As shown in a system structure diagram of fig. 1, an agricultural machinery path tracking method based on LOS theory includes the following steps:
s1, when an agricultural machine runs on a set straight path, acquiring real-time position information of the agricultural machine by a navigation positioning module;
s2, transmitting the position information to an LOS algorithm through parameters such as coordinates and transverse tracking errors analyzed by an upper computer system to obtain a current driving course angle;
and S3, outputting the wheel steering angle expected by the system by the front wheel feedback controller according to the course angle and the transverse tracking error, thus obtaining the steering deviation angle of the wheel, and repeating the steps to realize path tracking control.
The step S1 specifically includes:
s11, setting the boundary of the agricultural machine working field block through the Beidou RTK positioning module and the visual recognition CDD module, and then dotting a plurality of parallel linear tracks.
And S12, the Beidou RTK navigation module outputs the position and track point information of the agricultural machine in real time, simultaneously converts the position and track point information and three vertex coordinates of the rectangular field block into a Gaussian plane coordinate system, and stores the planned path into a navigation system in a two-dimensional array form to realize navigation path planning.
The step S11 specifically includes:
determining three coordinate vertexes of a test field by using an RTK-CCD positioning vision sensor fusion system to determine a rectangle, and assuming positioning coordinates of head nodes A, B, C and D; taking the longest distance of each operation line as a principle, combining the actual geometric shape of the plot, selecting a boundary AD as a reference line of operation line planning, using the boundary AD as the reference line to define a plurality of parallel operation lines, wherein the distance of the parallel lines is determined according to the operation line spacing, the shortest distance between the last operation line and the boundary BC is not less than 1/2 of the operation spacing, using the focuses of all Q parallel operation lines and the boundaries AB and CD as planning operation line nodes, and storing the corresponding operation line nodes into a two-dimensional array for being called by navigation control software based on an LOS algorithm.
As shown in fig. 2, based on the LOS navigation algorithm processing procedure, step S2 specifically includes:
s21: determining a two-way path point
Figure BDA0003077752650000071
And
Figure BDA0003077752650000072
the defined straight line traces the path, and the origin of the path coordinate system is at
Figure BDA0003077752650000073
The coordinate of the agricultural machine in the coordinate system with the fixed path is p n (t)=[x(t),y(t)]And satisfies the formula:
Figure BDA0003077752650000074
in the formula:
Figure BDA0003077752650000075
α k =atan2(y k+1 -y k ,x k+1 -x k )∈S;
α k for the north and the south of the geodetic coordinate system and the expected path P k And P k+1 The included angle of (a).
S22: let ε (t) = [ s (t), e (t) ]] T ∈R 2 Wherein:
s(t)=[x(t)-x k ]cos(α k )+[y(t)-y k ]sin(α k )
e(t)=-[x(t)-x k ]sin(α k )+[y(t)-y k ]cos(α k )
s (t) is the tracking distance of the agricultural machinery path, e (t) is the transverse tracking error, and in the actual path tracking process, we only need to pay attention to the transverse deviation of the agricultural machinery driving, because when the transverse deviation e (t) =0, it means that the agricultural machinery has converged on the expected tracking path, the path tracking control target is:
Figure BDA0003077752650000081
s23: the LOS navigation algorithm is set as follows:
Figure BDA0003077752650000082
in the formula:
Figure BDA0003077752650000083
Figure BDA0003077752650000084
is the velocity-path correlation angle. Wherein, delta is the forward looking distance of the agricultural machine, and e is the transverse tracking error;
if the agricultural machinery is used as the driving direction angle
Figure BDA0003077752650000085
The course angle is:
Figure BDA0003077752650000086
the step S3 specifically includes:
s31: as shown in fig. 3, information such as real-time position, wheel speed and turning angle of the agricultural machine is acquired through a navigation positioning system and a pose acquisition system, and kinematic modeling is performed by combining structural parameters of the agricultural machine and a two-degree-of-freedom model theory, specifically:
considering the path tracking process of the agricultural machinery as low-speed motion in an X-Y plane coordinate system, the following results are obtained according to the upper triangular chord and the lower triangular chord theorem:
Figure BDA0003077752650000087
wherein delta f 、δ r Respectively a front wheel corner and a rear wheel corner; l f 、l r Respectively a front wheel base and a rear wheel base;
beta is the direction angle of the running speed of the agricultural machine; r is a turning radius;
two-way degeneracy is multiplied on both sides
Figure BDA0003077752650000088
Obtaining:
Figure BDA0003077752650000091
under the condition of low-speed running working condition of the agricultural machinery, the change rate of the vehicle direction is as follows:
Figure BDA0003077752650000092
namely that
Figure BDA0003077752650000093
Since the agricultural machinery does not take into account the rear wheel steering situation, i.e. tan (delta) r ) Finishing when the color is not less than 0:
Figure BDA0003077752650000094
wherein
Figure BDA0003077752650000095
Is the heading angle, v is the speed of travel, and δ is the front wheel turning angle.
In a low-speed working environment, assuming that a wheel rotation angle direction is consistent with a speed direction, namely δ = β, a kinematic model is:
Figure BDA0003077752650000096
s32: the front wheel steering angle can be obtained by the steering characteristic of the agricultural machinery:
Figure BDA0003077752650000097
wherein
Figure BDA0003077752650000098
The course angle can be obtained by an LOS algorithm; delta. For the preparation of a coating e (t) is a steering deviation angle.
The larger the lateral tracking error e (t) and the larger the front wheel steering angle without considering the driving tracking deviation, the following nonlinear proportional function is obtained according to the geometrical relationship, assuming that the expected trajectory of the vehicle intersects the nearest tangent on a given path from the front wheel extension line d (t):
Figure BDA0003077752650000099
where d (t) is related to vehicle speed, represented by vehicle speed v (t) and gain parameter k.
Front wheel steering deviation angle from desired path without considering lateral tracking errorThe diametric tangent line direction is coincident, i.e. the front wheel direction is the same as the desired path direction in the absence of lateral error:
Figure BDA0003077752650000101
as the lateral tracking error increases, the non-linear proportional function produces a front wheel slip angle that points directly to the desired path, and:
Figure BDA0003077752650000102
in order to enable the two differential equations to have global gradual stable balance at the zero error junction, and integrate two control factors, the nonlinear front wheel feedback controller is designed as follows:
Figure BDA0003077752650000103
and from the geometrical relationships:
Figure BDA0003077752650000104
therefore, it is possible to
Figure BDA0003077752650000105
Therefore, the convergence rate of e (t) is between the linear convergence rate of v (t) and the exponential convergence rate of gain parameter k, and when the lateral tracking error e (t) is small, (ke (t)/v (t)) 2 Approaching to 0, then
Figure BDA0003077752650000106
Integration can give:
e(t)=e(0)*exp -kt
Figure BDA0003077752650000107
for any transverse error, the differential equation is monotonically converged to 0, and the path tracking control target is realized.
Through auxiliary equipment such as a GPS, a pose sensor, an angle sensor and the like of an upper computer and a lower computer of the agricultural machine, the acquired information such as the position, the angle and the like is not repeated in the feedback process part between the controller and the hydraulic steering transmission system.
As shown in fig. 4, by comparing the simulations of the path tracking control, it can be concluded that: the agricultural machinery path tracking control method based on the LOS theory can enable the control target to be converged to the expected path more quickly and stably, and has the advantages of less rotation angle change times in the path tracking process, more gentle process and good control effect.
The above description is only for the preferred embodiment of the present invention and is not intended to limit the present invention, and any modification, replacement or improvement without departing from the principle and principle of the present invention is within the protection scope of the present invention.

Claims (4)

1. An agricultural machinery path tracking method based on an LOS theory is characterized by comprising the following steps:
s1, when an agricultural machine runs on a set straight path, a navigation positioning module acquires real-time position information of the agricultural machine;
s2, transmitting the position information to an LOS algorithm through coordinates and transverse tracking error parameters analyzed by an upper computer system to obtain a current driving course angle;
the step S2 specifically includes:
s21: determining a two-way path point
Figure FDA0003832741280000011
And
Figure FDA0003832741280000012
the defined straight line traces the path, and the origin of the path coordinate system is at
Figure FDA0003832741280000013
The coordinate of the agricultural machine in the coordinate system with the fixed path is p n (t)=[x(t),y(t)]And satisfies the formula:
Figure FDA0003832741280000014
in the formula:
Figure FDA0003832741280000015
α k =a tan2(y k+1 -y k ,x k+1 -x k )∈S;
α k for the north and the north of the geodetic coordinate system and the expected path P k And P k+1 A is a coefficient;
s22: let ε (t) = [ s (t), e (t) ]] T ∈R 2 Wherein:
s(t)=[x(t)-x k ]cos(α k )+[y(t)-y k ]sin(α k )
e(t)=-[x(t)-x k ]sin(α k )+[y(t)-y k ]cos(α k )
s (t) is the tracking distance of the agricultural machinery path, e (t) is the transverse tracking error, and in the actual path tracking process, only the transverse deviation of the agricultural machinery running is needed to be concerned, because when the transverse deviation e (t) =0, the agricultural machinery is converged on the expected tracking path, the path tracking control target is as follows:
Figure FDA0003832741280000016
s23: the LOS navigation algorithm is set as follows:
Figure FDA0003832741280000017
in the formula:
Figure FDA0003832741280000018
Figure FDA0003832741280000019
is the speed-path correlation angle, where Δ is the forward-looking distance of the agricultural machine and e is the lateral tracking error;
if the agricultural machine is used as the driving direction angle
Figure FDA00038327412800000110
The course angle is then:
Figure FDA0003832741280000021
s3, the front wheel feedback controller outputs the wheel steering angle expected by the system according to the course angle and the transverse tracking error, so that the steering deviation angle of the wheels can be obtained, and the steps are repeated to realize path tracking control;
the step S3 specifically includes:
s31: the method comprises the steps of acquiring real-time position, wheel speed and corner information of the agricultural machine through a navigation positioning system and a pose acquisition system respectively, and performing kinematic modeling by combining structural parameters of the agricultural machine and a two-degree-of-freedom model theory, wherein the method specifically comprises the following steps:
considering the path tracking process of the agricultural machinery as low-speed motion in an X-Y plane coordinate system, the following results are obtained according to the upper triangular chord and the lower triangular chord theorem:
Figure FDA0003832741280000022
wherein delta f 、δ r Respectively a front wheel corner and a rear wheel corner; l. the f 、l r Respectively a front wheel base and a rear wheel base; beta is the direction angle of the running speed of the agricultural machine; r is a turning radius;
two-way degeneracy is multiplied on both sides
Figure FDA0003832741280000023
Obtaining:
Figure FDA0003832741280000024
under the condition of low-speed running working condition, the direction change rate of the agricultural machine is as follows:
Figure FDA0003832741280000025
namely that
Figure FDA0003832741280000026
Since the agricultural machinery does not take into account the rear wheel steering situation, i.e. tan (delta) r ) When the color is =0, finishing:
Figure FDA0003832741280000027
wherein
Figure FDA0003832741280000031
Is a course angle, v is a running speed, and delta is a front wheel rotation angle;
under a low-speed working environment, assuming that a wheel rotation angle direction is consistent with a speed direction, namely δ = β, a kinematic model is as follows:
Figure FDA0003832741280000032
s32: the front wheel steering angle can be obtained by the steering characteristic of the agricultural machinery:
Figure FDA0003832741280000033
wherein
Figure FDA0003832741280000034
The course angle can be obtained by an LOS algorithm; delta e (t) is the steering deviation angle;
the larger the lateral tracking error e (t) and the larger the front wheel steering angle without considering the driving tracking deviation, the following nonlinear proportional function is obtained according to the geometrical relationship, assuming that the expected trajectory of the vehicle intersects the nearest tangent on a given path from the front wheel extension line d (t):
Figure FDA0003832741280000035
wherein d (t) is related to vehicle speed, represented by vehicle speed v (t) and gain parameter k;
the front wheel steering deviation angle coincides with the desired path tangent direction without considering the lateral tracking error, i.e. the front wheel direction is the same as the desired path direction in the absence of lateral error:
Figure FDA0003832741280000036
as the lateral tracking error increases, the non-linear proportional function produces a front wheel slip angle that points directly to the desired path, and:
Figure FDA0003832741280000037
in order to enable the two differential equations to have global gradual stable balance at the zero point error junction, the nonlinear front wheel feedback controller is designed by integrating two control factors as follows:
Figure FDA0003832741280000041
and from the geometrical relationship:
Figure FDA0003832741280000042
therefore, it is possible to
Figure FDA0003832741280000043
Therefore, the convergence rate of e (t) is between the linear convergence rate of v (t) and the exponential convergence rate of gain parameter k, and when the lateral tracking error e (t) is small, (ke (t)/v (t)) 2 Approaching 0, then
Figure FDA0003832741280000044
Integration can give:
e(t)=e(0)*exp -kt
Figure FDA0003832741280000045
for any transverse error, the differential equation is monotonously converged to 0, and the path tracking control target is realized.
2. The LOS theory-based agricultural machinery path tracking method according to claim 1, wherein the step S1 specifically comprises:
s11, setting the boundary of the agricultural machine working field block through a Beidou RTK positioning module and a visual recognition CDD module, and then dotting a plurality of parallel linear tracks;
and S12, the Beidou RTK navigation module outputs the position and track point information of the agricultural machine in real time, simultaneously converts the position and track point information of the agricultural machine and three vertex coordinates of the rectangular field block into a Gaussian plane coordinate system, and stores the planned path into a navigation system in a two-dimensional array form to realize navigation path planning.
3. The method for tracking the agricultural machinery path based on the LOS theory as claimed in claim 2, wherein the step S11 is specifically as follows:
determining three coordinate vertexes of a test field by using an RTK-CCD positioning vision sensor fusion system to determine a rectangle, and assuming positioning coordinates of ground nodes A, B, C and D; taking the longest distance of each operation line as a principle, combining the actual geometric shape of the plot, selecting a boundary AD as a reference line of operation line planning, using the boundary AD as the reference line to define a plurality of parallel operation lines, wherein the distance of the parallel lines is determined according to the operation line spacing, the shortest distance between the last operation line and the boundary BC is not less than 1/2 of the operation spacing, using the focuses of all Q parallel operation lines and the boundaries AB and CD as planning operation line nodes, and storing the corresponding operation line nodes into a two-dimensional array for being called by navigation control software based on an LOS algorithm.
4. The agricultural machinery path tracking method based on the LOS theory as claimed in claim 1, wherein the steering deviation information of the wheels obtained by the navigation controller is transmitted to an agricultural machinery lower computer system, the real deviation value is corrected by the values of the steering sensor and the photoelectric encoder, and the corrected deviation value is transmitted to a hydraulic system of a control mechanism to control the flow and the flow direction of the hydraulic system, and finally the steering of the wheels is controlled, so that the vehicle can run according to a set route.
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