CN-122018552-A - Method for controlling cooperative surrounding guidance and preset performance of machine/ship in following detection task

CN122018552ACN 122018552 ACN122018552 ACN 122018552ACN-122018552-A

Abstract

The invention discloses a method for controlling cooperative surrounding guidance and preset performance of a ship/a ship in a following detection task, which comprises the steps of improving a surrounding mode of a ship-unmanned aerial vehicle system, constructing a dynamic surrounding guidance strategy, not only realizing uniform angular velocity surrounding of the unmanned aerial vehicle, but also switching surrounding radius at any time according to the detection task requirement, ensuring smooth transition of the whole surrounding conversion process in two dimensions of speed and acceleration, respectively defining standard preset performance functions according to ship and attitude errors, constructing a dynamic compensation term of the preset performance functions according to the standard preset performance functions to obtain position and attitude conversion errors, constructing a virtual control law of the ship system according to the position and attitude conversion errors, constructing the preset performance control law and the self-adaptive law, and realizing high-precision control under the conditions of considering a nonlinear term of the system of unknown model parameters, uncertain marine environment interference and unknown actuator gain.

Inventors

ZHANG GUOQING
Xu Diehui
Xing Yingshuo
ZHU MINGXU
XIAO HEYE
LI JIQIANG
ZHANG WENJUN
YANG XUE

Assignees

大连海事大学
西北工业大学

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (8)

1. The method for controlling the cooperative surrounding guidance and the preset performance of the machine/ship in the follow-up detection task is characterized by comprising the following steps: S1, constructing a nonlinear mathematical model for constructing a ship system by 1 ship and N unmanned aerial vehicles, wherein the nonlinear mathematical model comprises a ship kinematic model and an unmanned aerial vehicle kinematic model; S2, setting a waypoint path, acquiring a ship reference signal according to a preset virtual ship, and acquiring a ship error according to a ship kinematic model based on the ship reference signal, wherein the ship error comprises a ship position error and a ship attitude error; s3, setting a virtual unmanned aerial vehicle according to a ship kinematic model and combining an unmanned aerial vehicle surrounding radius dynamic transformation strategy to obtain an unmanned aerial vehicle reference signal, and obtaining an unmanned aerial vehicle error according to the unmanned aerial vehicle kinematic model based on the unmanned aerial vehicle reference signal, wherein the unmanned aerial vehicle error comprises an unmanned aerial vehicle position error and an unmanned aerial vehicle attitude error; S4, defining a first standard preset performance function according to the ship position error and the unmanned aerial vehicle position error, and constructing a first preset performance function dynamic compensation item according to the first standard preset performance function to obtain a position conversion error; S5, introducing a dynamic surface technology to perform reduced order processing on the first virtual control law, acquiring a dynamic surface signal of the first virtual control law to define a kinematic error of the ship system, and constructing a first preset performance control law and a self-adaptive law according to the kinematic error; S6, based on a first preset performance control law and a self-adaptive law, acquiring a reference roll angle signal and a reference pitch angle signal of the unmanned aerial vehicle according to a yaw angle reference signal of the unmanned aerial vehicle so as to acquire a roll angle error and a pitch angle error, defining a second standard preset performance function by combining a ship attitude error and the unmanned aerial vehicle attitude error, and constructing a second preset performance function dynamic compensation term according to the second standard preset performance function so as to acquire an attitude conversion error; S7, introducing a dynamic surface technology to perform order reduction processing on the second virtual control law, acquiring a dynamic surface signal of the second virtual control law to define an attitude error of the ship system, and constructing a second preset performance control law and a self-adaptive law according to the attitude error of the ship system; And S8, realizing cooperative surrounding guidance and preset performance control of the machine/ship in the follow-up detection task according to the first preset performance control law and the self-adaptive law and the second preset performance control law and the self-adaptive law.
2. The method for controlling cooperative surrounding guidance and preset performance of a ship in a following detection task according to claim 1, wherein the expression of the ship kinematic model in S1 is: (1) (2) wherein: Representing forward displacement, lateral displacement and yaw angle vector of ship , Representing forward, roll and yaw velocity vectors of a vessel ; Representing the nonlinear terms of the system in which the vessel acts in the forward, yaw and yaw directions and ; Representing the added mass of the ship in the forward, yaw and yaw directions ; Representing a ship actuator gain matrix and , Representing the gain of an actuator on the rotating speed and rudder angle of the ship propeller; Representing a vessel control input and , , Respectively representing the rotating speed and rudder angle of the ship propeller; Representing external interference force/moment applied to ship in forward, horizontal and bow directions and ; Representation of Is a first order derivative of (a); representing a rotation matrix; First, the The kinematic model of the unmanned aerial vehicle is as follows: (3) (4) wherein: representing displacement vectors of forward, horizontal drifting and heave of unmanned aerial vehicle and , Vector representing unmanned aerial vehicle roll angle, pitch angle and yaw angle and ; Representing the unmanned aerial vehicle along a preset coordinate system Shaft speed vector and rotational angular speed vector ; Representing system non-linear terms acting in the direction of forward, lateral and heave of an unmanned aerial vehicle and ; Representing system non-linear terms acting in the roll, pitch and yaw directions of the drone and ; Representing a quality matrix of the drone and ; Representing unmanned aerial vehicle along Shaft rotates inertial matrix and ; Representing an actuator gain matrix of the unmanned aerial vehicle; representing a position control input conversion matrix of the unmanned aerial vehicle; conversion matrix representing unmanned aerial vehicle attitude control input and , Representing the distance from the center of the unmanned aerial vehicle to each rotor; Representing a drone control input; representing external interference force/moment applied to unmanned aerial vehicle in advancing, drifting and heave directions and ; Representing external interference force/moment applied to unmanned aerial vehicle in rolling, pitching and heading directions and ; Representing a gravitational acceleration vector and Indicating the gravitational acceleration.
3. The method for controlling cooperative surrounding guidance and preset performance of a machine/ship in a following detection task according to claim 2, wherein S2 specifically comprises the steps of: S21, setting a waypoint path and a ship turning radius, selecting target points before and after each waypoint except a starting waypoint and a terminating waypoint according to the set ship turning radius, and planning and acquiring ship reference signals in real time according to a preset virtual ship, wherein the expression is as follows: (5) (6) wherein: representing the advancing distance, the horizontal drifting distance and the heading angle of the virtual ship; representing the advancing speed and the bow swing angular speed of the virtual ship; Representation of Is a first order derivative of (a); Representing the lateral acceleration of the virtual ship; Representing azimuth angle of virtual ship to target point and ; Representing the azimuth of the virtual vessel to the target point; Representing the distance of the virtual ship to the target point; S22, acquiring a ship error according to a ship kinematic model based on the ship reference signal, and acquiring the azimuth angle from the real ship to the virtual ship according to the ship error The method comprises the following steps: (7) (8) wherein: representing the ship position error, namely the forward distance error and the horizontal drift distance error of the ship; s23, according to azimuth angle from real ship to virtual ship Acquiring attitude error of ship The method comprises the following steps: (9)。
4. the method for controlling cooperative surrounding guidance and preset performance of a machine/ship in a following detection task according to claim 3, wherein S3 specifically comprises the steps of: s31, constructing a dynamic transformation strategy of the unmanned aerial vehicle surrounding radius, wherein the expression is as follows: (10) wherein: Representing the wrap-around radius before conversion; Indicating the desired wrap-around radius i.e. the converted wrap-around radius, Representing a transition time; Indicating the moment at which radius conversion starts; The output of the unmanned aerial vehicle surrounding radius dynamic transformation strategy is represented; S32, setting a virtual unmanned aerial vehicle according to a ship kinematic model and combining an unmanned aerial vehicle surrounding radius dynamic transformation strategy to acquire unmanned aerial vehicle reference signals as follows: (11) wherein: representing the advancing and transverse drifting distance of the virtual unmanned aerial vehicle; Representing unmanned aerial vehicle surrounding periods; representing azimuth angle of ship to virtual unmanned aerial vehicle and An initial value representing an azimuth angle of the vessel to the virtual drone; Representing a desired heave height of the unmanned aerial vehicle; S33, acquiring unmanned aerial vehicle position errors based on unmanned aerial vehicle reference signals according to an unmanned aerial vehicle kinematic model, and acquiring bow and swing angle reference signals of the unmanned aerial vehicle according to the unmanned aerial vehicle position errors Is that (12) (13) Wherein: Representing the position error of the unmanned aerial vehicle, namely the forward distance error, the transverse movement distance error and the heave distance error of the unmanned aerial vehicle; S34, according to the bow and swing angle reference signals of the unmanned aerial vehicle Acquiring unmanned aerial vehicle attitude error The method comprises the following steps: (14)。
5. the method for controlling cooperative surrounding guidance and preset performance of a machine/ship in a following detection task according to claim 4, wherein S4 specifically comprises the steps of: s41, defining a first standard preset performance function according to the ship position error and the unmanned plane position error, namely defining a corresponding error Is a first standard preset performance function of (2) The method comprises the following steps: (15) (16) wherein: Representation of In shorthand form; And (3) with Representation of Is set to the initial value and the final convergence value; Representing a positive constant; S42, defining a dynamic compensation term of a first preset performance function, wherein the expression is as follows: (17) wherein: Representing the corresponding error Is also referred to as a general term; representing the design tuning parameters and satisfying ; Representing a dynamic compensation term; Representation of Is a first order derivative of (a); s43, constructing a position error conversion formula according to the dynamic compensation term and the first standard preset performance function to obtain a position conversion error And the position error conversion formula is as follows: (18) s44, constructing an updating law of the first setting performance self-adaptive parameter according to the position conversion error, wherein the updating law is as follows: (19) wherein: representing preset performance adaptive parameters; Representation of Is a function of the estimated value of (2); An update law for indicating the adaptive parameters of the setting performance; Representing design parameters; Representation of Is set to an initial value of (1); s45, constructing a first virtual control law of the ship system according to the update law of the first setting performance self-adaptive parameter, wherein the first virtual control law is as follows: (20) wherein: representing a first virtual control law Is a positive design parameter of (a); Representing design parameters.
6. The method for controlling cooperative surrounding guidance and preset performance of a machine/ship in a following detection task according to claim 5, wherein S5 specifically comprises the steps of: S51, introducing a dynamic plane technology to perform reduced order processing on the first virtual control law, and acquiring a dynamic plane signal of the first virtual control law as follows: (21) wherein: representing a first virtual control law Is a dynamic surface signal of (1); representing a time constant greater than zero; Representation of Is set to an initial value of (1); Representation of Is a first order derivative of (a); S52, defining the kinematic error of the ship system according to the dynamic surface signal of the first virtual control law The expression is: (22) s53, deriving the kinematic error to obtain a kinematic error derivative as follows: (23) wherein: Representing vector form of dynamic surface signal and ; Representing error vectors and = ; Representation of Is a first order derivative of (a); s54 systematic non-linear terms in derivatives of kinematic errors by MLP techniques Interference from outside The approximation reduction is carried out, and the expression is as follows: (24) wherein: , Representation of A neural network weight update law; Representing a gaussian function; Representing an approximation error; representing approximation errors Is the maximum value of (2); a generic term representing external environmental disturbances; Representing intermediate parameters and ; Representation of Is a norm of (2); S55, acquiring an actual control input, and converting the actual control input into a preset performance control law and an adaptive law of an actuator gain, wherein the adaptive law is as follows: (25) wherein: the method comprises the steps of representing a ship advancing direction, a bow swing angle, an unmanned plane advancing direction, a horizontal floating direction, a heave direction, a roll angle, a pitch angle and a preset performance control law of the bow swing angle; , , , , , ; Respectively represent adaptive parameters I.e. the adaptive law of the actuator gain; Representation of Is set to an initial value of (1); Representing design parameters; representing a preset performance control law matrix; S56, based on a nonlinear mathematical model of the ship system, combining the formula (23) to the formula (25), and constructing a first preset performance control law and an adaptive law by using an MLP technology, a coupling gain adaptive technology and a Back stepping technology, wherein the first preset performance control law and the adaptive law are as follows: (26) (27) (28) (29) wherein: Representing a design parameter greater than zero, Representation of Is the maximum value of external interference of (a) An estimated value; Representing adaptive parameters and , Representation of Is a function of the estimated value of (2); Representing intermediate variables and , Representing a positive constant; Representation of Is set to an initial value of (1); Representation of Is a first order derivative of (a); Representation of Is set to be a constant value.
7. The method for controlling cooperative surrounding guidance and preset performance of a machine/ship in a following detection task according to claim 6, wherein S6 specifically comprises the steps of: s61, acquiring a reference roll angle signal of the unmanned aerial vehicle according to the roll angle reference signal of the unmanned aerial vehicle based on the first preset performance control law and the self-adaptive law With reference pitch angle signal The method comprises the following steps: (30) S62, obtaining a roll angle error and a pitch angle error according to the reference roll angle signal and the reference pitch angle signal, and defining the attitude error of the ship system by combining the ship attitude error and the unmanned plane attitude error as follows: , , , (31) s63, defining a second standard preset performance function according to the attitude error of the ship system, namely defining a corresponding error Is a second standard preset performance function of (2) The method comprises the following steps: (32) wherein: , Representation of Is a convergence value; Representing a positive constant; S64, constructing a second preset performance function dynamic compensation term according to the second standard preset performance function, wherein the second preset performance function dynamic compensation term is: (33) wherein: Representing the corresponding error Is also referred to as a general term; representing the design tuning parameters and satisfying ; Representing a dynamic compensation term; Representation of Is a first order derivative of (a); S65, according to dynamic compensation term Constructing an attitude error conversion formula by combining a second standard preset performance function to obtain an attitude conversion error And the attitude error conversion formula is as follows: (34) s66, constructing an updating law of the self-adaptive parameters of the second preset performance according to the posture conversion error, wherein the updating law is as follows: (35) wherein: representing preset performance adaptive parameters; Is that Is an estimated value of (2); An update law for indicating the adaptive parameters of the setting performance; Representing design parameters; Representation of Is set to an initial value of (1); s67, constructing a second virtual control law of the ship system according to the update law of the second setting performance self-adaptive parameter, wherein the second virtual control law is as follows: (36) wherein: representing a second virtual control law Is set, and control parameters of the same.
8. The method for controlling cooperative surrounding guidance and preset performance of a machine/ship in a following detection task according to claim 7, wherein S7 specifically comprises the steps of: s71, introducing a dynamic plane technology to perform reduced order processing on the second virtual control law, and acquiring a dynamic plane signal of the second virtual control law is as follows: (37) wherein: representing a second virtual control law Is a dynamic surface signal of (1); representing a time constant greater than zero; Representation of Is set to an initial value of (1); Representation of Is a first order derivative of (a); S72, defining the attitude error of the ship system according to the dynamic surface signal of the second virtual control law The method comprises the following steps: (38) s73, deriving the kinematic error to obtain a kinematic error derivative as follows: (39) wherein: Representing vector form of dynamic surface signal and ; Representing error vectors and ; Representation of Is a first order derivative of (a); S74 systematic nonlinear term of derivative of kinematic error in S73 by MLP technique Interference from outside The approximation reduction is carried out, and the expression is as follows: (40) wherein: , Representation of A neural network weight update law; Representing a gaussian function; Representing an approximation error; Representation of Is the maximum value of (2); a generic term representing external environmental disturbances; , Representation of Is a norm of (2); s75, based on a nonlinear mathematical model of the ship system, constructing a second preset performance control law and an adaptive law by using an MLP technology, a coupling gain adaptive technology and a Back stepping technology according to the same technical principles as in the steps S55 to S56, wherein the second preset performance control law and the adaptive law are as follows: (41) (42) (43) (44) wherein: Representing a design parameter greater than zero; representing the quality of the unmanned aerial vehicle; Representation of Is the maximum value of external interference of (a) An estimated value; Representing adaptive parameters and ; Representation of Is a function of the estimated value of (2); Representing intermediate variables and ; Representing a positive constant; Representation of Is set to an initial value of (1); Representation of Is set to an initial value of (1); Representation of Is a first order derivative of (a).

Description

Method for controlling cooperative surrounding guidance and preset performance of machine/ship in following detection task Technical Field The invention relates to the technical field of motion control research of ships and unmanned aerial vehicles, in particular to a method for controlling cooperative surrounding guidance and preset performance of a ship/airplane in a follow-up detection task. Background The path tracking control system executed by the ship-unmanned plane cooperative system consists of 3 parts of subsystems of guidance, control and navigation. The navigation system can automatically construct a reference signal according to the position relation between the current gesture of the ship-unmanned aerial vehicle system and the expected path, the control system can realize effective convergence by stabilizing the error between the current gesture and the reference signal, and the navigation system can transmit the position and gesture information of a controlled object to the navigation system and the control system through the sensor. Guidance and control are two important subsystems in path tracking control, and effective path tracking control fundamentally depends on a robust guidance strategy to realize track generation. In the existing method, a line of sight (LOS) technique is widely used because of its high computational efficiency, and its working principle is to adjust a yaw angle by a target deviation. While LOS guidance performs well in a stable environment, it is limited in performance in a dynamic environment while being sensitive to path curvature and not suitable for use in a circular path. Vector field guidance has excellent tamper resistance by constructing a vector field. However, this approach relies on accurate system models and environmental parameters on the one hand and cannot be directly applied to USV-UAV heterogeneous systems on the other hand, because vector fields need to be built for USV and UAV respectively, and practical implementation is challenging. The three-dimensional mapping guidance method proposed in the prior art can realize three-dimensional collaborative guidance of the whole USV-UAV system, but requires that the unmanned aerial vehicle must keep a fixed relative position with the USV. In terms of USV and UAV control, preset Performance Control (PPC) has been widely studied and applied in recent years for its accuracy advantage. The basic PPC method ensures that the system error is always within a preset boundary through the design of the performance function, and simultaneously accelerates the convergence rate. There are studies that propose a fixed time preset performance consistency controller that enhances the error convergence rate and ensures that all tracking errors are entered and maintained within specified boundaries for a fixed time. While PPC significantly improves the control accuracy and response speed of the USV-UAV system, its inherent vulnerability in dynamic environments remains a critical limitation to be addressed. Therefore, coping with environmental interference effects becomes an important improvement direction when PPC is applied. A great deal of researches combine PPC with an interference observer, and prove that the mixing method can not only effectively inhibit the destabilization effect of environmental interference, but also maintain the transient performance characteristics of the mixing method. However, the above-described control schemes employing a constant Preset Performance Function (PPF) may suffer from singular value problems under real-environment time-varying disturbances. The event-triggered self-adaptive PPC proposed in the prior art dynamically updates the performance function when the failure of tracking the reference signal is detected through an event-driven mechanism. The prior art also includes introducing a dynamically adjustable preset performance function as a constraint boundary adjustment method to effectively solve the singular value problem by adapting to external interference and measurement noise in real time, but such PPF can continuously generate boundary change in the whole control process, even under the minimum environmental interference. Based on the analysis, the traditional guidance control method is directly applied to the ship-unmanned aerial vehicle surrounding detection task, and mainly comprises the following 2 point defects: 1) In the past, unmanned aerial vehicle is often used for assisting ship navigation in a ship position synchronous mode, so that the unmanned aerial vehicle can also provide surrounding environment information for a ship and early warn potential danger, but the advantage of high maneuverability of the unmanned aerial vehicle cannot be effectively utilized by the cooperative mode, in the surrounding detection, the unmanned aerial vehicle makes uniform angular velocity surrounding movement around the ship while accompanying the progress of the ship, and therefore, t