CN111487966B - Self-adaptive path tracking control method for unmanned surface vehicle based on waypoints - Google Patents
Self-adaptive path tracking control method for unmanned surface vehicle based on waypoints Download PDFInfo
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Abstract
A self-adaptive path tracking control method for an unmanned surface vehicle based on waypoints belongs to the technical field of control. The unmanned ship is mainly used for solving the problem that classical LOS guidance can generate large overshoot when the turning angle of the unmanned ship is larger than 90 degrees, and the turning tracking precision is low. The method is characterized in that a basic line-of-sight angle is calculated based on the radius of the proposed self-adaptive LOS circle, and the basic line-of-sight angle is compensated according to the path deviation and the course deviation to obtain a final expected line-of-sight angle; and then, a steering strategy based on virtual points is designed, and the problem of serious overshoot generated when the turning angle is large is solved by adopting three small-angle steering transition large-angle steering. Meanwhile, the invention also designs a speed resolver, an intelligent self-adaptive S-surface course controller and an intelligent self-adaptive integral S-surface speed controller, which can improve the tracking efficiency and the anti-interference capability of the unmanned ship and can well cope with the complexity and the uncertainty of an unmanned ship model. The method is mainly used for self-adaptive path tracking control of the unmanned surface vehicle.
Description
Technical Field
The invention belongs to the technical field of control, and particularly relates to a tracking control method of an unmanned surface vehicle.
Background
The unmanned surface vehicle is used as important marine intelligent equipment, plays an important role in the aspects of submarine surveying and mapping, offshore platform and offshore wind power plant inspection, marine environment monitoring, offshore investigation defense and the like, and in order to accurately and efficiently complete tasks, the influence of the underactuation property of the USV and the complicated and variable marine environment on the maneuverability of the USV is considered, so that in practical application, the requirement on the capability of the unmanned surface vehicle for tracking along a preset expected path is higher and higher.
In a path tracking control strategy of the unmanned ship, a composite straight Line path tracking based on a preset path point can be set in advance, and the path point is more in Line-of-sight (LOS) -based path tracking engineering application requirements of the unmanned ship, most of the existing path tracking control methods are designed based on a Line-of-sight (LOS) guidance law, but because the radius of an LOS circle is a fixed value, the convergence time is easily overlong when the path deviation is large, and the traditional LOS guidance angle cannot be adjusted and compensated on Line according to the path deviation and heading deviation, so that the unmanned ship cannot be converged on an expected path quickly; generally, when the turning angle of the unmanned ship is less than 90 degrees, the tracking requirement can be basically met by adopting the classical LOS guidance, but when the turning angle of the unmanned ship is more than 90 degrees, the classical LOS guidance is adopted to generate greater overshoot; meanwhile, the tracking speed of the unmanned ship is generally set as a fixed value, the speed is relatively too high when the unmanned ship turns, and the speed is relatively low when the unmanned ship is in straight line navigation, so that the tracking precision of turning is reduced, and meanwhile, the time required for completing tracking is also increased.
Disclosure of Invention
The invention mainly aims to solve the problem that the turning tracking precision is low because classical LOS guidance generates large overshoot when the turning angle of the unmanned ship is larger than 90 degrees.
A self-adaptive path tracking control method of an unmanned surface vehicle based on waypoints is characterized by comprising the following steps:
resolving the sight angle based on an LOS guidance law corresponding to the radius of the self-adaptive LOS circle, and then compensating the sight angle according to the path deviation and the course deviation to obtain a final expected course angle, so that the unmanned ship continuously moves to an expected path under the guidance of the final expected course angle;
based on the steering strategy of the virtual point, three small-angle steering transition large-angle steering modes are adopted for steering:
let three adjacent waypoints on the driving path be P k-1 、P k And P k+1 The coordinates are respectively (x) k-1 ,y k-1 )、(x k ,y k ) And (x) k+1 ,y k+1 ) At P k-1 P k Set up a virtual turning point A at P k P k+1 Setting a virtual steering point C; A. b, C have coordinates of (x) A ,y A )、(x B ,y B ) And (x) C ,y C ) And line segment AP k Is equal to the line segment P k C; coordinate of point B is represented by delta AP k The geometric center of C;
calculating coordinates of points A and C according to the steering angle:
when x is k -x k-1 When equal to 0, x A ＝x k-1 ＝x k ，y A ＝y k -μk 8 θ t R tmin ；
When y is k -y k-1 When equal to 0, y A ＝y k-1 ＝y k ，x A ＝x k -Θk 8 θ t R tmin ；
When x is k -x k-1 ≠0，y k -y k-1 When the signal is not equal to 0, the signal is transmitted,
when x is k+1 -x k When equal to 0, x C ＝x k ＝x k+1 ，y C ＝y k +μk 8 θ t R tmin ；
When y is k+1 -y k When equal to 0, y C ＝y k ＝y k+1 ，x C ＝x k +Θk 8 θ t R tmin ；
When x is k+1 -x k ≠0，y k+1 -y k When the signal is not equal to 0, the signal is transmitted,
wherein k is 8 Is the coefficient of gyration, θ t Is the steering angle, R tmin Is the minimum radius of gyration and,
and when x k+1 ＞x k Or x k ＞x k-1 When theta is equal to 1, otherwise theta is equal to-1; when y is k+1 ＞y k Or y k ＞y k-1 When μ ═ 1, otherwise μ ═ 1.
When the unmanned boat is along the angle P k-1 P k P k+1 When navigating, if the turning angle is more than 90 degrees, the angle is converted into the angle P k-1 ABCP k+1 And (5) sailing.
Further, the specific process of performing line-of-sight angle calculation based on the LOS guidance law corresponding to the adaptive LOS circle radius comprises the following steps:
the adaptive LOS circle radius is as follows:
in the formula, R min Is the minimum circle radius of the LOS, δ is the thickness of the transition layer, k 1 Is the LOS circle radius adjustable coefficient, y e Is the path deviation; when y e |＞R min + delta, the unmanned boat converges to the desired path at the current minimum forward-looking distance, when the path deviates by | y e |≤R min Delta, at minimum inscribed radius R of unmanned boat min Tends towards the desired path, when R min -δ＜|y e |≤R min + delta, the LOS circle radius can be at [ R ] min ,R min +δ]With smooth transition between them.
A series of waypoint coordinates are noted as P 1 ,P 2 ,…,P k-1 ,P k ,P k+1 ,…,P n ，P k (x k ,y k ) Is the k coordinate, P LOS (x LOS ,y LOS ) Is the location coordinate of LOS, alpha k-1 Is the desired path azimuth, R min Is the minimum line of sight circle radius, R δ Is the radius of the line of sight circle, R, of the transition layer k Is the radius of the circle of the kth switching next expected path point, and Δ > 0 is the look-ahead distance;
on the straight line unit connecting two adjacent path points, the line-of-sight reference position is solved by the following formula:
(x LOS -x) 2 +(y LOS -y) 2 ＝R 2
in the formula, R is the radius of an LOS circle which is made by taking an unmanned boat as a center, namely the radius of an adaptive LOS circle; (x, y) is the real-time position of the unmanned surface vehicle, (x) k-1 ,y k-1 ) The coordinates of a predetermined kth-1 th track point;
then calculating the sight angle psi of the unmanned boat approaching to the expected path by a projection algorithm LOS Comprises the following steps:
the unmanned boat continuously moves towards the reference point under the guidance of the visual line angle, and then gradually converges to the expected path.
Furthermore, the process of compensating the line-of-sight angle according to the path deviation and the course deviation to obtain the final expected course angle is realized by a LOS line-of-sight angle compensator based on the course deviation and a LOS line-of-sight angle compensator based on the path deviation;
the LOS line-of-sight angle compensator based on the course deviation is as follows:
where Δ ψ is the heading angle deviation, ψ r Is the actual heading psi of the unmanned ship H Is the heading compensation angle, delta max Is the maximum steering rudder angle k in the actual sailing of the unmanned ship 2 Is the adjustable coefficient of the course deviation compensator;
the LOS line-of-sight angle compensator based on path deviation is as follows:
in the formula, # P Is the path deviation compensation angle, k 3 Is an adjustable coefficient of the path deviation compensator;
the final desired heading angle for the unmanned boat is:
ψ d ＝ψ LOS +ψ H +ψ P 。
further, the water surface unmanned ship self-adaptive path tracking control method based on the waypoints further comprises the step of utilizing a speed resolver to calculate the optimal expected speed of the unmanned ship in real time, and then calculating the optimal expected speed and transmitting the optimal expected speed to a speed control link;
the speed resolver is a combined speed resolver for course deviation and path point distance, and comprises the following specific steps:
in the formula,. DELTA.psi d Is the deviation of the actual course from the actual desired course, v d Is the desired speed, v, of the unmanned boat max Is the maximum speed of the unmanned boat,. DELTA.l is the distance from the next waypoint, k 4 、k 5 Is an adjustable parameter of the navigational speed resolver.
Furthermore, the method for controlling the self-adaptive path tracking of the unmanned surface vehicle based on the waypoints further comprises the step of controlling the course by using an intelligent self-adaptive S-plane course controller;
the intelligent self-adaptive S-surface course controller comprises the following components:
wherein, f h Indicating a heading control output, e h And ec h Respectively course deviation and course deviation change rate, needs normalization processing,
and
represents a heading controller parameter reference value,
and
indicating a heading controller adjustable parameter.
Furthermore, the method for controlling the self-adaptive path tracking of the unmanned surface vehicle based on the waypoints further comprises the step of controlling the speed by using an intelligent self-adaptive integral S-plane speed controller;
the intelligent self-adaptive integral S-plane navigational speed controller comprises the following components:
in the formula: f. of v Representing the speed control output, k is the integration step, e v And ec v Speed deviation and the rate of change of speed deviation, respectively, also require normalization,
and
represents the cruise controller parameter reference value,
and
represents the adjustable parameter of the navigational speed controller, and t represents time.
Has the advantages that:
the method comprises the steps of firstly, fully considering the relation between the path deviation and the guidance law performance in the path tracking process, providing a self-adaptive LOS circle radius, and then compensating the line of sight angle according to the path deviation and the course deviation, so that the unmanned ship can be converged to a desired path more quickly; meanwhile, the invention also provides a steering strategy based on the virtual point, three small-angle steering transition large-angle steering are adopted to overcome the problem that the traditional LOS generates serious overshoot when the steering angle is larger, and the path tracking precision of the unmanned ship is greatly improved.
Meanwhile, the invention also designs a speed resolver, which can solve the optimal expected speed of the unmanned ship in real time and greatly improve the tracking precision and efficiency. The invention also designs an intelligent self-adaptive S-surface course controller and an intelligent self-adaptive integral S-surface navigational speed controller, which can well deal with the complexity and uncertainty of the unmanned ship model, improve the self-adaptive capacity of the controller and further improve the path tracking precision and efficiency of the unmanned ship.
Therefore, the overall technical scheme of the invention can solve the problem of low turning tracking precision caused by large overshoot generated by classical LOS guidance when the turning angle is larger than 90 degrees in the prior art. The problems that the convergence speed of the unmanned ship to the expected path is low, the tracking precision is poor and the tracking efficiency is low during path tracking can be solved.
The simulation shows that the path tracking method designed by the invention can effectively guide the unmanned ship to sail according to the preset path, has better inflection point performance, can be converged to the expected route at a higher speed after the path is switched, has smaller path deviation and higher tracking precision.
Drawings
FIG. 1 is a schematic view of a reference coordinate system;
FIG. 2 is a schematic view of a wide angle turn;
FIG. 3 is a schematic diagram of a guidance strategy for an adaptive LOS circle radius;
FIG. 4 is a path tracing simulation diagram;
FIG. 5 is a graph of a path deviation simulation;
FIG. 6 is a velocity response simulation diagram;
FIG. 7 is a view of a heading angle response simulation.
Detailed Description
The first embodiment is as follows:
the embodiment is a method for controlling adaptive path tracking of an unmanned surface vehicle based on waypoints, and before a specific control scheme is explained, parameters and related key technologies are explained first.
The parameters involved in the present invention are defined as follows:
η＝[x,y,ψ] T the position and heading angle of the USV under a geodetic coordinate system { E }; v ═ u, v, r] T The longitudinal speed, the transverse speed and the angular speed of the USV under a ship body coordinate system { B }; j (psi) E R 3×3 A rotation matrix from a boat body coordinate system { B } to a geodetic coordinate system { E } for the unmanned boat; m is belonged to R 3×3 Is an inertia matrix; c (v) ε R 3×3 Is a matrix of coriolis forces and centripetal forces; d is belonged to R 3×3 Is a damping force matrix; b is equal to R 3×2 Configuring a matrix for the actuator; f ═ f u ,f r ] T Is an input quantity of control, wherein u Is propeller thrust, f r Is the moment produced by the rudder angle; d ═ d u ,d v ,d r ] T Disturbance force/moment caused by external sea wind, sea wave and ocean current; r min The minimum circle radius of LOS; delta is the thickness of the transition layer; delta psi is the course angle deviation; psi r The actual course of the unmanned ship; psi LOS Is the angle of the line of sight; psi H Compensating the angle for the heading; delta max The steering angle is the maximum steering rudder angle of the unmanned boat in actual navigation; theta.theta. t Is a steering angle; r tmin Is the minimum radius of gyration.
The related key technology is as follows:
firstly, fully considering the relation between the path deviation and the guidance law performance in the path tracking process, and defining a LOS circle radius related to the path deviation, namely a self-adaptive LOS circle radius; then, the line-of-sight angle is compensated according to the path deviation and the course deviation, so that the unmanned ship can be converged to a desired path more quickly; finally, in order to overcome the problem that the traditional LOS generates serious overshoot when the turning angle is large, a virtual point-based steering strategy is provided, and three small-angle steering and large-angle steering are adopted; in order to improve the tracking efficiency, a speed resolver is designed, and the optimal expected speed of the unmanned ship can be resolved in real time; aiming at the complexity and uncertainty of the unmanned ship model, an intelligent self-adaptive S-plane course controller and an intelligent self-adaptive integral S-plane navigational speed controller are designed.
Self-adaptive LOS circle radius: considering the relation between the path deviation and the guidance law performance in the path tracking process, an adaptive LOS radius related to the path deviation is defined, and the adaptive LOS radius can be converged to a desired path at an optimal distance in real time.
LOS line-of-sight angle compensator: in the tracking process, according to the path deviation and the course deviation of the unmanned ship, the sigmod function is adopted to compensate and adjust the LOS line-of-sight angle in real time, so that the unmanned ship can be converged to the expected course angle more quickly.
Virtual point-based steering strategy: in order to overcome the problem that severe overshoot is generated when the turning angle of the traditional LOS is large, a virtual point-based steering strategy is provided, three small-angle steering transition large-angle steering are adopted, and the overshoot problem when the unmanned ship is turned at a large angle is reduced.
A joint airspeed resolver: according to the deviation between the actual course angle of the unmanned ship and the azimuth angle of the tracked path, the distances between the actual course angle of the unmanned ship and the azimuth angle of the tracked path are considered, the optimal expected navigational speed is calculated by adopting a Gaussian function and transmitted to a speed control link, and the tracking efficiency of the unmanned ship is greatly improved.
The intelligent self-adaptive S-plane course control method comprises the following steps: the parameters of the S-surface controller are adjusted in real time only by using the errors and the error change rate, but the parameters do not depend on the experience of operators, the structure is simple, and the control effect is better in practical engineering application.
The method can control the unmanned ship corresponding to the three-degree-of-freedom kinematic equation and the dynamic non-complete symmetric model, and can also control the unmanned ships corresponding to the kinematic equation and the dynamic non-complete symmetric model in other forms. The present embodiment is described by taking an unmanned ship corresponding to a three-degree-of-freedom kinematic equation and a dynamic non-completely symmetric model as an example, where the mathematical model of the motion of the unmanned ship on the water surface is as follows:
a schematic diagram of a reference coordinate system is shown in fig. 1; the horizontal plane motion of the unmanned ship is analyzed, and the position and the heading angle under a geodetic coordinate system { E } can be expressed as eta ═ x, y, psi] T The longitudinal velocity, lateral velocity and angular velocity of the heading in the boat body coordinate system { B } may be expressed as v ═ u, v, r] T Then, the three-degree-of-freedom kinematic equation and the dynamic non-completely symmetric model of the unmanned surface vehicle horizontal plane can be expressed as follows:
in the formula: j (psi) E R 3×3 Representing a rotation matrix of the unmanned ship from a ship body coordinate system { B } to a geodetic coordinate system { E }, and M epsilon R 3×3 Representing the inertia matrix, C (v) e R 3×3 Representing a matrix of Coriolis and centripetal forces, D ∈ R 3×3 Representing a damping force matrix, B ∈ R 3×2 Representing actuator configuration matrices defined respectively as:
normal amount m 11 、m 22 、m 23 、m 32 、m 33 、d 11 、d 22 、d 23 、d 32 Is the hydrodynamic coefficient of the unmanned ship, f ═ f u ,f r ] T Is a controlled input quantity, where f u Is propeller thrust, f r Is the moment produced by the rudder angle; d ═ d u ,d v ,d r ] T Is the disturbing force/moment caused by external sea wind, waves and currents.
The unmanned ship in the embodiment is only provided with one rudder and one propeller, and has no lateral direct control input, so that the unmanned ship is an under-actuated system, and the coordinate system center of the ship body of the unmanned ship can be converted for the unmanned ship with the symmetrical port and starboard sidesSo that M is -1 Bf＝[τ u ,0,τ r ] T In which τ is u 、τ r Respectively is control force and control moment, and the converted external environment interference term can be defined as M -1 d＝[d u ,d v ,d r ] T Then the component form of the under-actuated unmanned boat model can be expressed as:
in the formula:
N u (v,r)、X(u)、Y(u)、N r (u, v, r) is a continuous smooth function.
The specific control process of the invention comprises the following steps:
s1, designing a self-adaptive radius LOS guidance law based on the self-adaptive radius of the LOS circle:
the unmanned vehicle guidance system may provide a reference heading angle to the heading control system in real time for directing the USV toward the desired path. From the practicability, the invention provides a guidance strategy based on the adaptive LOS circle radius of the transition layer aiming at the waypoint tracking, and the adaptive LOS circle radius is as follows:
in the formula, R min Is the minimum circle radius of the LOS, δ is the thickness of the transition layer, k 1 Is the LOS circle radius adjustable coefficient, y e Is the path deviation; when y e |＞R min + delta, the unmanned boat converges to the desired path at the current minimum forward-looking distance, when the path deviates by | y e |≤R min Delta, at minimum inscribed radius R of unmanned boat min Tends towards the desired path, when R min -δ＜|y e |≤R min + delta, the LOS circle radius can be at [ R ] min ,R min +δ]With smooth transition between them.
The guidance strategy for the adaptive LOS circle radius is shown in FIG. 3, and defines a series of waypoint coordinates: p 1 ,P 2 ,…,P k-1 ,P k ,P k+1 ,…,P n ，P k (x k ,y k ) Is the k coordinate, P LOS (x LOS ,y LOS ) Is the location coordinate of LOS, alpha k-1 Is the desired path azimuth, R min Is the minimum line of sight circle radius, R δ Is the radius of the line of sight circle, R, of the transition layer k Is the radius of the circle for the kth switch next expected path point, and Δ > 0 is the look-ahead distance.
On the straight line unit connecting two adjacent path points, the line-of-sight reference position is solved by the following formula:
(x LOS -x) 2 +(y LOS -y) 2 ＝R 2
in the formula, R is the radius of an LOS circle which is made by taking an unmanned boat as a center, namely the radius of an adaptive LOS circle; (x, y) is the unmanned boat real-time position, (x) k-1 ,y k-1 ) The coordinates of a predetermined kth-1 th track point;
then calculating the line-of-sight angle psi of the unmanned boat which tends to be expected by a projection algorithm LOS Comprises the following steps:
the unmanned boat continuously moves to the reference point under the guidance of the visual line angle, thereby gradually converging to the expected path and quickly reaching the next path point P k And comparing the USV with the set conversion radius to judge whether the USV enters the tracking of the next straight path unit.
S2, compensating the expected line-of-sight angle according to the path deviation and the heading deviation, and enabling the unmanned ship to converge to the expected path more quickly:
the path tracking in the invention is indirectly realized in a course control mode, although the mode is very effective, the path tracking cannot be quickly converged to a desired path, and in order to realize the purpose of quickly reaching the desired path, the invention respectively designs Gaussian function course angle compensators based on course deviation and path deviation.
Designing a compensator based on course deviation:
where Δ ψ is the heading angle deviation, ψ r Is the actual heading, psi, of the unmanned ship LOS Is the desired viewing angle, # H Is the heading compensation angle, k p Is the maximum steering rudder angle k in the actual sailing of the unmanned ship 2 Is an adjustable coefficient of the course deviation compensator.
LOS line-of-sight angle compensator based on path deviation:
in the formula, # P Is the path deviation compensation angle, k 3 Is an adjustable coefficient of a path deviation compensator, y e Is the path deviation.
The final desired heading angle for the unmanned boat is:
ψ d ＝ψ LOS +ψ H +ψ P 。
s3, in order to overcome the serious overshoot generated by the traditional LOS when the turning angle is larger, the invention further provides a virtual point-based steering strategy, and the steering is carried out by adopting three small-angle steering transitional large-angle steering modes:
when the unmanned ship steers at a large angle, the invention adopts a steering strategy of three small turning angles to transit a large turning angle, as shown in figure 2; p k-1 、P k And P k+1 Is the three waypoints that are adjacent to each other,the coordinates are respectively (x) k-1 ,y k-1 )、(x k ,y k ) And (x) k+1 ,y k+1 ) A, B and C are three virtual turning points with coordinates of (x) respectively A ,y A )、(x B ,y B ) And (x) C ,y C ) And line segment AP k Is equal to line segment P k C, firstly, calculating coordinates of points A and C according to the steering angle, and adopting a delta AP for the coordinate of the point B k The geometric center of C. When the unmanned boat is along the angle P k-1 P k P k+1 During navigation, as the turning angle is larger (the turning angle is larger than 90 degrees), the angle P can be converted into k-1 ABCP k+1 Sailing, and greatly reducing overshoot in the turning process.
When x is k -x k-1 When equal to 0, x A ＝x k-1 ＝x k ，y A ＝y k -μk 8 θ t R tmin ；
When y is k -y k-1 When equal to 0, y A ＝y k-1 ＝y k ，x A ＝x k -Θk 8 θ t R tmin ；
When x is k -x k-1 ≠0，y k -y k-1 When the signal is not equal to 0, the signal is transmitted,
when x is k+1 -x k When equal to 0, x C ＝x k ＝x k+1 ，y C ＝y k +μk 8 θ t R tmin ；
When y is k+1 -y k When equal to 0, y C ＝y k ＝y k+1 ，x C ＝x k +Θk 8 θ t R tmin ；
When x is k+1 -x k ≠0，y k+1 -y k When the number is not equal to 0, the color,
wherein k is 8 Is the coefficient of gyration, θ t Is the steering angle, R tmin Is the minimum radius of gyration and,
and when x k+1 ＞x k Or x k ＞x k-1 When theta is equal to 1, otherwise theta is equal to-1; when y is k+1 ＞y k Or y k ＞y k-1 When μ ═ 1, otherwise μ ═ 1.
S4, in order to improve the tracking efficiency, the invention also designs a speed resolver which can real-timely calculate the optimal expected speed of the unmanned ship;
designing a course deviation and path point distance combined speed solver, wherein the combined speed solver can solve the optimal expected speed according to the deviation between the actual course angle of the unmanned ship and the tracked path azimuth angle and the distance between the front path point and the rear path point and transmit the optimal expected speed to a speed control link by considering the distance between the front path point and the rear path point; the design is as follows:
in the formula,. DELTA.psi d Is the deviation of the actual course from the actual desired course, v d Is the desired speed, v, of the unmanned boat max Is the maximum speed of the unmanned vehicle, Δ l is the distance from the next waypoint, k 4 、k 5 Is an adjustable parameter of the navigational speed resolver.
S5, aiming at the complexity and uncertainty of the unmanned ship model, the invention also designs an intelligent self-adaptive S-surface course controller and an intelligent self-adaptive integral S-surface navigational speed controller.
Designing an intelligent self-adaptive S-surface course controller:
although the parameters of the classical S-plane controller can be adjusted by the existing neural network control, fuzzy control and evolutionary algorithm, the methods are relatively complicated to adjust in practical application, and meanwhile, operators are required to have quite abundant field experience, so that the method has great limitation in practical application. The intelligent self-adaptive S-plane course controller comprises the following components:
wherein, f h Indicating a heading control output, e h And ec h Respectively course deviation and course deviation change rate, needs normalization processing,
and
represents a heading controller parameter reference value,
and
indicating a heading controller adjustable parameter.
An intelligent self-adaptive integral S-plane navigational speed controller is designed as follows:
in the formula: f. of v Representing the speed control output, k is the integration step, e v And ec v Respectively, the speed deviation and the rate of change of the speed deviation, also needs normalization processing,
and
represents the cruise controller parameter reference value,
and
representing the adjustable parameters of the cruise controller. F in intelligent self-adaptive integral S-plane navigational speed controller α (·,·)、f β (-) and f in an intelligent adaptive S-plane heading controller α (·,·)、f β Functional form (·,. cndot.). cndot.,. cndot..
Examples
In order to verify the effectiveness and the high efficiency of the path tracking control algorithm provided by the invention, the path tracking control algorithm is applied to an unmanned ship model for verification. Under a rectangular coordinate system, an X axis is defined as a true east direction, a Y axis is defined as a true north direction, and the X axis rotates along a Y axis positive half shaft.
The initial state of the unmanned ship is set as [ x (0), y (0), psi (0)] T ＝[31m,25m,-40°] T 、[u(0),v(0),r(0)] T ＝[0m/s,0m/s,0rad/s] T Maximum velocity v max 2.5m/s, parameter R min ＝3m，R k ＝2m，δ＝2m，δ max ＝30°，k 1 ＝3，k 2 ＝k 3 ＝k 4 ＝k 5 ＝2，
k is 0.01, and the designed path point information is as follows:
TABLE 1 Path Point information
The simulation effect of the present invention is shown in fig. 4 to 7, wherein fig. 4 is a path tracking simulation diagram, fig. 5 is a path deviation simulation diagram, fig. 6 is a speed response simulation diagram, and fig. 7 is a heading angle response simulation diagram.
The simulation shows that the path tracking method designed by the invention can effectively guide the unmanned ship to sail according to the preset path, has better inflection point performance, can be converged to the expected route at a higher speed after the path is switched, has smaller path deviation and higher tracking precision.
Compared with the prior art, the invention has the following advantages:
the indirect path tracking scheme of the unmanned ship mainly comprises two parts, wherein one part is used for calculating a guidance law, and the other part is used for designing a course and speed controller. In addition to the present invention, there are other classic LOS guidance law calculations and the design of course and speed controllers to accomplish the task of unmanned boat indirect path tracking, which are briefly described below and compared with the present invention.
(1) Classical LOS-based guidance law calculation:
the radius of the sight line circle based on the classical LOS is a fixed value, so that the form is simple, but the convergence speed is low, and the tracking accuracy is not high. Fossen et al propose proportional LOS, Khaled et al propose exponential LOS, wherein, although the exponential LOS method effectively improves the convergence of the LOS angle, the solution speed of the LOS angle is reduced due to the introduction of an exponential function and a Lambert W function.
The invention is innovated and improved on the basis, not only designs the adaptive LOS circle radius based on the transition layer, but also carries out real-time compensation adjustment on the LOS angle based on the path deviation and the course error, and simultaneously provides a steering strategy for transiting a large turn by using three small turns in order to improve the tracking precision.
(2) Course and speed controller design
The design of the course and speed controller mainly comprises two categories, namely an error-based category and a model-based category, wherein a model-based control algorithm, such as a backstepping method, robust control and the like, can achieve an accurate control effect, but the control accuracy of the algorithm is greatly influenced because the accurate motion model of the unmanned ship under different sea conditions is difficult to obtain in actual application. Although the error-based control methods such as PID, S-surface and the like do not depend on an accurate mathematical model, the control parameters cannot be adjusted in a self-adaptive manner or are relatively complex to adjust.
The invention provides an intelligent self-adaptive S-surface course controller and an intelligent self-adaptive integral S-surface navigational speed controller based on an error control method, which can not only adjust the parameters of the controller in an online self-adaptive manner, but also do not need to depend on operation experience excessively during adjustment, and are relatively simple and convenient to operate.
Meanwhile, the speed resolving problem in the tracking process is not considered in other schemes, so that the tracking efficiency is not high, and the joint speed resolver based on the course deviation and the path deviation is designed, so that the path tracking precision and efficiency of the unmanned ship are greatly improved.
It should be noted that the detailed description is only for explaining and explaining the technical solution of the present invention, and the scope of protection of the claims is not limited thereby. It is intended that all such modifications and variations be included within the scope of the invention as defined in the following claims and the description.
Claims (6)
1. A self-adaptive path tracking control method of an unmanned surface vehicle based on waypoints is characterized by comprising the following steps:
resolving the sight angle based on an LOS guidance law corresponding to the radius of the self-adaptive LOS circle, and then compensating the sight angle according to the path deviation and the course deviation to obtain a final expected course angle, so that the unmanned ship continuously moves to an expected path under the guidance of the final expected course angle;
the specific process of resolving the sight angle based on the LOS guidance law corresponding to the self-adaptive LOS circle radius comprises the following steps:
the adaptive LOS circle radius is as follows:
in the formula, R min Is the minimum circle radius of the LOS, δ is the thickness of the transition layer, k 1 Is the LOS circle radius adjustable coefficient, y e Is the path deviation; when | y e |＞R min + delta, the unmanned boat converges to the desired path at the current minimum forward-looking distance, when the path deviates by | y e |≤R min Delta, at minimum inscribed radius R of unmanned boat min Tends towards the desired path, when R min -δ＜|y e |≤R min + delta, the LOS circle radius can be at [ R min ,R min +δ]Are smoothly transited;
a series of waypoint coordinates are noted as P 1 ,P 2 ,…,P k-1 ,P k ,P k+1 ,…,P n ，P k (x k ,y k ) Is the k coordinate, P LOS (x LOS ,y LOS ) Is the location coordinate of LOS, alpha k-1 Is the desired path azimuth, R min Is the minimum line of sight circle radius, R δ Is the radius of the line of sight circle, R, of the transition layer k Is the radius of the circle of the kth switching next expected path point, and Δ > 0 is the look-ahead distance;
on the straight line unit connecting two adjacent path points, the line-of-sight reference position is solved by the following formula:
(x LOS -x) 2 +(y LOS -y) 2 ＝R 2
in the formula, R is the radius of an LOS circle which is made by taking an unmanned boat as a center, namely the radius of an adaptive LOS circle; (x, y) is the unmanned boat real-time position, (x) k-1 ,y k-1 ) The coordinates of a predetermined kth-1 th track point;
then calculating the sight angle psi of the unmanned boat approaching to the expected path by a projection algorithm LOS Comprises the following steps:
the unmanned boat continuously moves to a reference point under the guidance of the line-of-sight angle, so that the unmanned boat gradually converges to a desired path;
the process of compensating the line-of-sight angle according to the path deviation and the course deviation to obtain the final expected course angle is realized by an LOS line-of-sight angle compensator based on the course deviation and an LOS line-of-sight angle compensator based on the path deviation;
the LOS line-of-sight angle compensator based on the course deviation is as follows:
where Δ ψ is the heading angle deviation, ψ r Is the actual heading, psi, of the unmanned ship H Is the course compensation angle, delta max Is the maximum steering rudder angle k in actual navigation of the unmanned ship 2 Is an adjustable coefficient of the course deviation compensator;
the LOS line-of-sight angle compensator based on path deviation is as follows:
in the formula, # P Is the path deviation compensation angle, k 3 Is an adjustable coefficient of the path deviation compensator;
the final desired heading angle for the unmanned boat is:
ψ d ＝ψ LOS +ψ H +ψ P
based on the steering strategy of the virtual point, three small-angle steering transition large-angle steering modes are adopted for steering:
let three adjacent waypoints on the driving path be P k-1 、P k And P k+1 The coordinates are respectively (x) k-1 ,y k-1 )、(x k ,y k ) And (x) k+1 ,y k+1 ) At P k-1 P k Set up a virtual turning point A at P k P k+1 Setting a virtual steering point C; A. b, C have coordinates of (x) A ,y A )、(x B ,y B ) And (x) C ,y C ) And line segment AP k Is equal to line segment P k C; coordinate of point B adopts delta AP k The geometric center of C;
calculating coordinates of points A and C according to the steering angle:
when x is k -x k-1 When equal to 0, x A ＝x k-1 ＝x k ，y A ＝y k -μk 8 θ t R tmin ；
When y is k -y k-1 When equal to 0, y A ＝y k-1 ＝y k ，x A ＝x k -Θk 8 θ t R tmin ；
When x is k -x k-1 ≠0，y k -y k-1 When the signal is not equal to 0, the signal is transmitted,
when x is k+1 -x k When equal to 0, x C ＝x k ＝x k+1 ，y C ＝y k +μk 8 θ t R tmin ；
When y is k+1 -y k When equal to 0, y C ＝y k ＝y k+1 ，x C ＝x k +Θk 8 θ t R tmin ；
When x is k+1 -x k ≠0，y k+1 -y k When the signal is not equal to 0, the signal is transmitted,
wherein k is 8 Is the coefficient of gyration, [ theta ] t Is the steering angle, R tmin Is the minimum radius of gyration,/ APk ＝k 8 θ t R tmin ，l CPk ＝k 8 θ t R tmin And when x is k+1 ＞x k Or x k ＞x k-1 When theta is equal to 1, otherwise theta is equal to-1; when y is k+1 ＞y k Or y k ＞y k-1 When mu is 1, otherwise mu is-1;
when the unmanned boat is along the angle P k-1 P k P k+1 When navigating, if the turning angle is more than 90 degrees, the angle is converted into the angle P k-1 ABCP k+1 And (5) sailing.
2. The method for the adaptive path tracking control of the unmanned surface vehicle based on waypoints according to claim 1, further comprising the steps of solving the optimal expected speed of the unmanned vehicle in real time by using a speed resolver, and then solving the optimal expected speed to be transmitted to a speed control link;
the speed resolver is a combined speed resolver for course deviation and path point distance, and comprises the following specific steps:
in the formula,. DELTA.psi d Is the deviation of the actual course from the actual desired course, v d Is the desired speed, v, of the unmanned boat max Is the maximum speed of the unmanned boat,. DELTA.l is the distance from the next waypoint, k 4 、k 5 Is an adjustable parameter of the speed resolver.
3. The method for the adaptive path tracking control of the unmanned surface vehicle based on waypoints as claimed in claim 2, wherein the method further comprises the step of controlling the course by using an intelligent adaptive S-plane course controller;
the intelligent self-adaptive S-surface course controller comprises the following components:
wherein f is h Indicating a heading control output, e h And ec h Respectively course deviation and course deviation change rate, needs normalization processing,
and
represents a heading controller parameter reference value,
and
indicating a heading controller adjustable parameter.
4. The method for the adaptive path tracking control of the unmanned surface vehicle based on waypoints according to claim 3, further comprising the step of controlling the speed of the unmanned surface vehicle by using an intelligent adaptive integral S-plane speed controller;
the intelligent self-adaptive integral S-plane navigational speed controller comprises the following components:
in the formula: f. of v Representing the speed control output, k is the integration step, e v And ec v Speed deviation and the rate of change of speed deviation, respectively, also require normalization,
and
represents the cruise controller parameter reference value,
and
represents the adjustable parameter of the navigational speed controller, and t represents time.
5. The method for controlling the adaptive path tracking of the unmanned surface vehicle based on waypoints according to claim 4, wherein the unmanned surface vehicle adopts a three-degree-of-freedom kinematic equation and a dynamic non-fully-symmetric model.
6. The method for controlling adaptive path tracking of the unmanned surface vehicle based on waypoints as claimed in claim 5, wherein the equations of kinematics with three degrees of freedom and the dynamic non-complete symmetry model with three degrees of freedom can be expressed as follows:
in the formula: j (psi) E R 3×3 Representing a rotation matrix of the unmanned ship from a ship body coordinate system to a geodetic coordinate system, and M epsilon R 3×3 Representing the inertia matrix, C (v) e R 3×3 Representatives of the familyMatrix of force and centripetal force, D (v) E R 3×3 Representing a damping force matrix, B ∈ R 3×2 Representing an actuator configuration matrix; eta ═ x, y, psi] T The position and the heading angle under a geodetic coordinate system; v ═ u, v', r] T The longitudinal speed, the transverse speed and the angular speed of the heading under a boat body coordinate system; d ═ d u ,d v ,d r ] T Disturbance force/moment caused by external sea wind, sea wave and ocean current; f is the input amount of the control.
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