CN111487966A - 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
The invention relates to a water surface unmanned ship self-adaptive path tracking control method based on waypoints, which belongs to the technical field of control and mainly aims to solve the problem that classical L OS guidance generates larger overshoot when the turning angle of an unmanned ship is larger than 90 degrees, so that the turning tracking precision is low.
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, path points can be set in advance, and therefore the path tracking is more suitable for the application requirements of path tracking engineering of the unmanned ship, most of existing path tracking control methods are based on L ine-of-Sight (L OS) to conduct guidance law design, but since the circular radius of L OS is a fixed value, when the path deviation is large, the convergence time is easy to be too long, and the traditional L OS guidance angle cannot conduct online adjustment compensation according to the path deviation and the 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 smaller than 90 degrees, the tracking requirements can be basically met by adopting classical L OS guidance, when the turning angle of the unmanned ship is larger than 90 degrees, the classical L OS guidance can generate larger overshoot, and meanwhile, the tracking speed of the unmanned ship is generally set to be a fixed value, when the speed is relatively too fast when the unmanned ship turns, the turning speed is relatively low, the tracking accuracy is reduced, and the required tracking time is increased.
Disclosure of Invention
The invention mainly aims to solve the problem that the turning tracking precision is low due to the fact that classical L OS guidance generates large overshoot when the turning angle of an unmanned boat is larger than 90 degrees.
A method for controlling adaptive path tracking of an unmanned surface vehicle based on waypoints, which is characterized by comprising the following steps:
resolving the line-of-sight angle based on a L OS guidance law corresponding to the self-adaptive L OS circle radius, and then compensating the line-of-sight angle according to the path deviation and the heading deviation to obtain a final expected heading angle, so that the unmanned ship continuously moves to an expected path under the guidance of the final expected heading 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 Pk-1、PkAnd Pk+1The coordinates are respectively (x)k-1,yk-1)、(xk,yk) And (x)k+1,yk+1) At Pk-1PkSet up a virtual turning point A at PkPk+1Setting a virtual steering point C; A. b, C have coordinates of (x)A,yA)、(xB,yB) And (x)C,yC) And line segment APkIs equal to the line segment PkDistance of C, coordinates of point B adopt △ APkThe geometric center of C;
calculating coordinates of points A and C according to the steering angle:
when x isk-xk-1When equal to 0, xA＝xk-1＝xk，yA＝yk-μk8θtRtmin；
When y isk-yk-1When equal to 0, yA＝yk-1＝yk，xA＝xk-Θk8θtRtmin；
When x isk-xk-1≠0，yk-yk-1When the signal is not equal to 0, the signal is transmitted,
when x isk+1-xkWhen equal to 0, xC＝xk＝xk+1，yC＝yk+μk8θtRtmin；
When y isk+1-ykWhen equal to 0, yC＝yk＝yk+1，xC＝xk+Θk8θtRtmin；
When x isk+1-xk≠0，yk+1-ykWhen the signal is not equal to 0, the signal is transmitted,
wherein k is8Is the coefficient of gyration, θtIs the steering angle, RtminIs the minimum radius of gyration and,
and when xk+1＞xkOr xk＞xk-1When theta is equal to 1, otherwise theta is equal to-1; when y isk+1＞ykOr yk＞yk-1When μ ═ 1, otherwise μ ═ 1.
When no one is along ∠ Pk-1PkPk+1When navigating, if the turning angle is more than 90 degrees, the transition is to be along ∠ Pk-1ABCPk+1And (5) sailing.
Further, the specific process of performing line-of-sight angle calculation based on L OS guidance law corresponding to the adaptive L OS circle radius comprises the following steps:
the adaptive L OS circle radius is as follows:
in the formula, RminIs the minimum circle radius of L OS, is the thickness of the transition layer, k1Is L OS circle radius adjustable coefficient, yeIs the path deviation; when ye|＞Rmin+ time, the unmanned boat converges to the desired path at the current minimum forward-looking distance, when the path deviates by ye|≤Rmin-time, unmanned boat with minimum inscribed circle radius RminTends towards the desired path, when Rmin-＜|ye|≤Rmin+ at, L OS circle radius can be at [ R ]min,Rmin+]With smooth transition between them.
A series of waypoint coordinates are noted as P1,P2,…,Pk-1,Pk,Pk+1,…,Pn，Pk(xk,yk) Is the k coordinate, PLOS(xLOS,yLOS) Position coordinates of L OS, αk-1Is the desired path azimuth, RminIs the minimum line of sight circle radius, RIs the radius of the line of sight circle, R, of the transition layerkIs 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:
(xLOS-x)2+(yLOS-y)2＝R2
wherein R is L OS circle radius which is taken by the unmanned boat as the center, namely the self-adaptive L OS circle radius, (x, y) is the real-time position of the unmanned boat, (xk-1,yk-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 algorithmLOSComprises 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.
Further, the process of compensating the line-of-sight angle according to the path deviation and the heading deviation to obtain the final expected heading angle is realized by an L OS line-of-sight angle compensator based on the heading deviation and a L OS line-of-sight angle compensator based on the path deviation;
the L OS line-of-sight angle compensator based on heading bias is as follows:
where Δ ψ is the heading angle deviation, ψrIs the actual heading, psi, of the unmanned shipHIs the angle of the course compensation and is,maxis the maximum steering rudder angle k in the actual sailing of the unmanned ship2Is the adjustable coefficient of the course deviation compensator;
the L OS line-of-sight angle compensator based on path deviation is as follows:
in the formula, #PIs the path deviation compensation angle, k3Is an adjustable coefficient of the path deviation compensator;
the final desired heading angle for the unmanned boat is:
ψd＝ψLOS+ψH+ψP。
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.psidIs the deviation of the actual course from the actual desired course, vdIs the desired speed, v, of the unmanned boatmaxIs the maximum speed of the unmanned boat,. DELTA.l is the distance from the next waypoint, k4、k5Is 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-surface course controller;
the intelligent self-adaptive S-surface course controller comprises the following components:
wherein f ishIndicating a heading control output, ehAnd echRespectively 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. ofvRepresenting the speed control output, k is the integration step, evAnd ecvSpeed 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 L OS circle radius, then compensating the line angle according to the path deviation and the course deviation, enabling the unmanned ship to converge to an expected path more quickly, meanwhile, providing a steering strategy based on a virtual point, adopting three small-angle steering transition large-angle steering to overcome the problem that the traditional L OS generates serious overshoot when the turning angle is larger, and greatly improving the path tracking precision of the unmanned ship.
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 integral technical scheme of the invention not only can solve the problem of low turning tracking precision caused by large overshoot generated by classical L OS guidance when the turning angle is larger than 90 degrees in the prior art, but also can solve the problems of low convergence speed, poor tracking precision and low tracking efficiency of an unmanned ship on an expected path during path tracking.
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 adaptive L OS 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]Tthe position and heading angle of the USV under a geodetic coordinate system { E }; v ═ u, v, r]TLongitudinal speed, transverse speed and angular speed of heading of USV in ship body coordinate system B, J (psi) ∈ R3×3For rotation matrix from ship body coordinate system to earth coordinate system M ∈ R3×3Is an inertia matrix, C (v) ∈ R3×3Is a matrix of Coriolis forces and centripetal forces, D ∈ R3×3Is a damping force matrix, B ∈ R3×2Configuring a matrix for the actuator; f ═ fu,fr]TIs an input quantity of control, whereinuIs propeller thrust, frIs the moment produced by the rudder angle; d ═ du,dv,dr]TDisturbance force/moment caused by external sea wind, sea wave and ocean current; rminIs LMinimum circle radius of OS; is the thickness of the transition layer; delta psi is the course angle deviation; psirThe actual course of the unmanned ship; psiLOSIs the angle of the line of sight; psiHCompensating the angle for the course;maxthe steering angle is the maximum steering rudder angle of the unmanned boat in actual navigation; thetatIs a steering angle; rtminIs the minimum radius of gyration.
The related key technology is as follows:
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, defining L OS circle radius related to the path deviation, namely self-adaptive L OS circle radius, then compensating a line angle according to the path deviation and the course deviation, enabling the unmanned ship to converge to an expected path more quickly, finally, providing a steering strategy based on a virtual point for overcoming the serious overshoot generated when the traditional L OS is large in turning angle, adopting three small-angle steering to transit large-angle steering, designing a speed resolver for improving the tracking efficiency, calculating the optimal expected speed of the unmanned ship in real time, and designing an intelligent self-adaptive S-surface course controller and an intelligent self-adaptive integral S-surface speed controller for the complexity and the uncertainty of an unmanned ship model.
Self-adaptive L OS circle radius considering the relation between the path deviation and the guidance law performance in the path tracking process, a self-adaptive L OS radius related to the path deviation is defined, and the path deviation can be converged to a desired path at the optimal distance in real time.
L OS line-of-sight angle compensator, in the tracking process, according to the path deviation and the course deviation of the unmanned ship, a sigmod function is adopted to carry out real-time compensation adjustment on the L OS line-of-sight angle, so that the unmanned ship can be converged to the expected course angle more quickly.
The virtual point-based steering strategy is provided in order to overcome the defect that severe overshoot is generated when the turning angle of the traditional L OS is large, three small-angle steering are adopted to transit large-angle steering, and the overshoot problem when the unmanned ship is steered at a large angle is reduced.
A joint navigational speed 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 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:
the horizontal plane motion of the unmanned ship is analyzed, and the position and the heading angle under the geodetic coordinate system { E } can be represented as η ═ x, y, psi]TThe 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]TThen, 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:
wherein J (psi) ∈ R3×3M ∈ R representing a rotation matrix from a boat body coordinate system { B } to a geodetic coordinate system { E } of the unmanned boat3×3Representing an inertia matrix, C (v) ∈ R3×3Representing the matrix of Coriolis and centripetal forces, D ∈ R3×3Representing a damping force matrix, B ∈ R3×2Representing actuator configuration matrices defined respectively as:
normal amount m11、m22、m23、m32、m33、d11、d22、d23、d32Is the hydrodynamic coefficient of the unmanned ship, f ═ fu,fr]TIs a controlled input quantity, where fuIs propeller thrust, frIs the moment produced by the rudder angle; d ═ du,dv,dr]TIs 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 with the symmetrical port and starboard can be converted to enable M to be in a state of being M-1Bf＝[τu,0,τr]TIn which τ isu、τrRespectively is control force and control moment, and the converted external environment interference term can be defined as M-1d＝[du,dv,dr]TThen the component form of the under-actuated unmanned boat model can be expressed as:
in the formula:
Nu(v,r)、X(u)、Y(u)、Nr(u, v, r) is a continuous smooth function.
The specific control process of the invention comprises the following steps:
s1, designing a L OS guidance law of the adaptive radius based on the adaptive L OS circle radius:
the invention provides a guidance strategy based on an adaptive L OS circle radius of a transition layer for waypoint tracking, wherein the adaptive L OS circle radius is as follows from the practicability:
in the formula, RminIs the minimum circle radius of L OS, is the thickness of the transition layer, k1Is L OS circle radius adjustable coefficient, yeIs the path deviation; when ye|＞Rmin+ time, the unmanned boat converges to the desired path at the current minimum forward-looking distance, when the path deviates by ye|≤Rmin-time, unmanned boat with minimum inscribed circle radius RminTends towards the desired path, when Rmin-＜|ye|≤Rmin+ at, L OS circle radius can be at [ R ]min,Rmin+]With smooth transition between them.
A guidance strategy for self-adapting L OS circle radius is shown in FIG. 3, and defines a series of waypoint coordinates P1,P2,…,Pk-1,Pk,Pk+1,…,Pn，Pk(xk,yk) Is the k coordinate, PLOS(xLOS,yLOS) Position coordinates of L OS, αk-1Is the desired path azimuth, RminIs the minimum line of sight circle radius, RIs the radius of the line of sight circle, R, of the transition layerkIs the radius of the circle for the kth switching next desired 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:
(xLOS-x)2+(yLOS-y)2＝R2
wherein R is L OS circle radius which is taken by the unmanned boat as the center, namely the self-adaptive L OS circle radius, (x, y) is the real-time position of the unmanned boat, (xk-1,yk-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 algorithmLOSComprises 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 PkAnd 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, ψrIs the actual heading, psi, of the unmanned shipLOSIs the desired viewing angle, #HIs the heading compensation angle, kpIs the maximum steering rudder angle k in the actual sailing of the unmanned ship2Is an adjustable coefficient of the course deviation compensator.
L OS line-of-sight angle compensator based on path deviation:
in the formula, #PIs the path deviation compensation angle, k3Is an adjustable coefficient of a path deviation compensator, yeIs the path deviation.
The final desired heading angle for the unmanned boat is:
ψd＝ψLOS+ψH+ψP。
s3, in order to overcome the problem that severe overshoot is generated when the turning angle is large in the conventional L OS, the invention further provides a steering strategy based on a virtual point, and steering is performed by adopting three modes of small-angle steering and large-angle steering:
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; pk-1、PkAnd Pk+1Is three adjacent waypoints with the coordinates of (x)k-1,yk-1)、(xk,yk) And (x)k+1,yk+1) A, B and C are three virtual turning points with coordinates of (x) respectivelyA,yA)、(xB,yB) And (x)C,yC) And line segment APkIs equal to the line segment PkC, firstly, calculating coordinates of points A and C according to the steering angle, wherein the coordinate of the point B adopts △ APkC geometric center when unmanned surface vehicle runs along ∠ Pk-1PkPk+1When in navigation, the steering angle is larger (the steering angle is larger than 90 degrees), so that the steering wheel can be converted into the ∠ P directionk-1ABCPk+1Sailing, the overshoot in the turning process is greatly reduced.
When x isk-xk-1When equal to 0, xA＝xk-1＝xk，yA＝yk-μk8θtRtmin；
When y isk-yk-1When equal to 0, yA＝yk-1＝yk，xA＝xk-Θk8θtRtmin；
When x isk-xk-1≠0，yk-yk-1When the signal is not equal to 0, the signal is transmitted,
when x isk+1-xkWhen equal to 0, xC＝xk＝xk+1，yC＝yk+μk8θtRtmin；
When y isk+1-ykWhen equal to 0, yC＝yk＝yk+1，xC＝xk+Θk8θtRtmin；
When x isk+1-xk≠0，yk+1-ykWhen the signal is not equal to 0, the signal is transmitted,
wherein k is8Is the coefficient of gyration, θtIs the steering angle, RtminIs the minimum radius of gyration and,
and when xk+1＞xkOr xk＞xk-1When theta is equal to 1, otherwise theta is equal to-1; when y isk+1＞ykOr yk＞yk-1When 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.psidIs the deviation of the actual course from the actual desired course, vdIs the desired speed, v, of the unmanned boatmaxIs the maximum speed of the unmanned boat,. DELTA.l is the distance from the next waypoint, k4、k5Is 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 ishIndicating a heading control output, ehAnd echRespectively 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. ofvRepresenting the speed control output, k is the integration step, evAnd ecvSpeed deviation and the rate of change of speed deviation, respectively, also require normalization,
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 controllerα(·,·)、fβ(-) and f in an intelligent adaptive S-plane heading controllerα(·,·)、fβThe (·,. cndot.) functions are identical in form.
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]TMaximum velocity vmax2.5m/s, parameter Rmin＝3m，Rk＝2m，＝2m，max＝30°，k1＝3，k2＝k3＝k4＝k5＝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:
in order to meet the requirement of the unmanned ship indirect path tracking task, the invention also comprises other classical L OS guidance law calculation and the design of a course and speed controller, and the two parts are briefly introduced below and compared with the scheme of the invention.
(1) Guidance law calculation based on classical L OS:
the line-of-sight circle radius based on classical L OS is a fixed value, so although the form is simple, the convergence speed is slow, the tracking accuracy is not high, later, L iu T et al use a variable L OS circle radius, so that there is always an intersection between the L OS circle and the path, but the adjustment range of the variable radius is small, and the adaptability to the path with a small break angle is low.
The invention is innovated and improved on the basis, not only designs the adaptive L OS circle radius based on the transition layer, but also carries out real-time compensation adjustment on the L OS 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.
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 (8)
1. A method for controlling adaptive path tracking of an unmanned surface vehicle based on waypoints, which is characterized by comprising the following steps:
resolving the line-of-sight angle based on a L OS guidance law corresponding to the self-adaptive L OS circle radius, and then compensating the line-of-sight angle according to the path deviation and the heading deviation to obtain a final expected heading angle, so that the unmanned ship continuously moves to an expected path under the guidance of the final expected heading 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 Pk-1、PkAnd Pk+1The coordinates are respectively (x)k-1,yk-1)、(xk,yk) And (x)k+1,yk+1) At Pk-1PkSet up a virtual turning point A at PkPk+1Setting a virtual steering point C; A. b, C have coordinates of (x)A,yA)、(xB,yB) And (x)C,yC) And line segment APkIs equal to the line segment PkDistance of C, coordinates of point B adopt △ APkThe geometric center of C;
calculating coordinates of points A and C according to the steering angle:
when x isk-xk-1When equal to 0, xA＝xk-1＝xk，yA＝yk-μk8θtRtmin；
When y isk-yk-1When equal to 0, yA＝yk-1＝yk，xA＝xk-Θk8θtRtmin；
When x isk-xk-1≠0，yk-yk-1When the signal is not equal to 0, the signal is transmitted,
when x isk+1-xkWhen equal to 0, xC＝xk＝xk+1，yC＝yk+μk8θtRtmin；
When y isk+1-ykWhen equal to 0, yC＝yk＝yk+1，xC＝xk+Θk8θtRtmin；
When x isk+1-xk≠0，yk+1-ykWhen the signal is not equal to 0, the signal is transmitted,
wherein k is8Is the coefficient of gyration, θtIs the steering angle, RtminIs the minimum radius of gyration,/APk＝k8θtRtmin，lCPk＝k8θtRtminAnd when x isk+1＞xkOr xk＞xk-1When theta is equal to 1, otherwise theta is equal to-1; when y isk+1＞ykOr yk＞yk-1When mu is 1, otherwise mu is-1;
when no one is along ∠ Pk-1PkPk+1When navigating, if the turning angle is more than 90 degrees, the transition is to be along ∠ Pk-1ABCPk+1And (5) sailing.
2. The method for controlling the adaptive path tracking of the unmanned surface vehicle based on waypoints as claimed in claim 1, wherein the specific process of performing the line-of-sight angle calculation based on the L OS guidance law corresponding to the adaptive L OS circle radius comprises the following steps:
the adaptive L OS circle radius is as follows:
in the formula, RminIs the minimum circle radius of L OS, is the thickness of the transition layer, k1Is L OS circle radius adjustable coefficient, yeIs the path deviation; when ye|＞Rmin+ time, the unmanned boat converges to the desired path at the current minimum forward-looking distance, when the path deviates by ye|≤Rmin-time, unmanned boat with minimum inscribed circle radius RminTends towards the desired path, when Rmin-＜|ye|≤Rmin+ at, L OS circle radius can be at [ R ]min,Rmin+]Are smoothly transited;
a series of waypoint coordinates are noted as P1,P2,…,Pk-1,Pk,Pk+1,…,Pn，Pk(xk,yk) Is the k coordinate, PLOS(xLOS,yLOS) Position coordinates of L OS, αk-1Is the desired path azimuth, RminIs the minimum line of sight circle radius, RIs the radius of the line of sight circle, R, of the transition layerkIs 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:
(xLOS-x)2+(yLOS-y)2＝R2
wherein R is L OS circle radius which is taken by the unmanned boat as the center, namely the self-adaptive L OS circle radius, (x, y) is the real-time position of the unmanned boat, (xk-1,yk-1) The coordinates of a predetermined kth-1 th track point;
then calculating the unmanned ship trend by a projection algorithmViewing angle psi at desired pathLOSComprises 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.
3. The adaptive waypoint-based path-tracking control method for the unmanned surface vehicle as claimed in claim 2, wherein 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 implemented by a L OS line-of-sight angle compensator based on the course deviation and a L OS line-of-sight angle compensator based on the path deviation;
the L OS line-of-sight angle compensator based on heading bias is as follows:
where Δ ψ is the heading angle deviation, ψrIs the actual heading, psi, of the unmanned shipHIs the angle of the course compensation and is,maxis the maximum steering rudder angle k in the actual sailing of the unmanned ship2Is the adjustable coefficient of the course deviation compensator;
the L OS line-of-sight angle compensator based on path deviation is as follows:
in the formula, #PIs the path deviation compensation angle, k3Is an adjustable coefficient of the path deviation compensator;
the final desired heading angle for the unmanned boat is:
ψd＝ψLOS+ψH+ψP。
4. the method for controlling the adaptive path tracking of the unmanned surface vehicle based on waypoints according to claim 1, 2 or 3, wherein the method further comprises the step of solving the optimal expected speed of the unmanned vehicle in real time by using a speed solver, and then 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.psidIs the deviation of the actual course from the actual desired course, vdIs the desired speed, v, of the unmanned boatmaxIs the maximum speed of the unmanned boat,. DELTA.l is the distance from the next waypoint, k4、k5Is an adjustable parameter of the navigational speed resolver.
5. The method for the adaptive path tracking control of the unmanned surface vehicle based on waypoints according to claim 4, further comprising 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 ishIndicating a heading control output, ehAnd echRespectively 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.
6. The method for the adaptive path tracking control of the unmanned surface vehicle based on waypoints according to claim 5, 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. ofvRepresenting the speed control output, k is the integration step, evAnd ecvSpeed 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.
7. The adaptive path tracking control method for the unmanned surface vehicle based on waypoints as claimed in claim 6, wherein the unmanned surface vehicle adopts a three-degree-of-freedom kinematic equation and a dynamic non-fully symmetric model.
8. The method for controlling adaptive path tracking of unmanned surface vehicle based on waypoints according to claim 7, wherein the equations of kinematics with three degrees of freedom and the dynamic non-complete symmetry model with three degrees of freedom are as follows:
wherein J (psi) ∈ R3×3M ∈ R representing a rotation matrix from a boat body coordinate system { B } to a geodetic coordinate system { E } of the unmanned boat3×3Representing an inertia matrix, C (v) ∈ R3×3Representing the matrix of Coriolis and centripetal forces, D ∈ R3×3Representing a damping force matrix, B ∈ R3×2Representing the actuator configuration matrix, η ═ x, y, ψ]TPositions and heading angles under a geodetic coordinate system { E }; v ═ u, v, r]TThe longitudinal speed, the transverse speed and the angular speed of the heading under a ship body coordinate system { B }; d ═ du,dv,dr]TDisturbance force/moment caused by external sea wind, sea wave and ocean current; f is the input amount of the control.
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