A heading disturbance rejection control method for an unmanned surface vehicle

Abstract

The application provides a heading disturbance rejection control method of an unmanned surface vehicle, a tracking differentiator is used to track an input desired heading angle signal quickly to obtain a tracking value, a high-gain extended observer is designed to observe a current state of the unmanned surface vehicle to obtain an observed value, an error feedback control rate is used to output a rudder angle desired value by calculating an error between the observed value and the tracking value, and an estimation of the total disturbance by the observer is used as compensation to obtain a heading disturbance rejection control law, and the unmanned surface vehicle is controlled according to the above steps to achieve the heading disturbance rejection effect. The application has a strong filtering effect on matching sea conditions, can make the steering engine steer more smoothly, realizes the stability of the USV heading, ensures that the unmanned surface vehicle completes a series of complex tasks such as path tracking, target tracking, cluster motion, and has strong robustness to external disturbances and parameter perturbations.

Description

Technical Field

[0001] This invention relates to the field of bow disturbance rejection control technology for unmanned surface vessels (USVs), specifically a bow disturbance rejection control method for USVs. Background Technology

[0002] Heading stability control of unmanned surface vehicles (USVs) is a prerequisite for ensuring that USVs can complete a series of complex tasks such as path tracking, target tracking, and swarm movement. Ship navigation control is a typical error feedback control structure, which uses the difference between the desired heading and the actual heading as an adjustment factor to adjust the output rudder angle through the feedback system until the required accuracy is achieved.

[0003] Due to the time-varying sea wave interference in the navigation environment, the additional rolling motion caused by the waves will cause the bow control controller to frequently steer, which will reduce the life of the servo motor, shorten the endurance of the unmanned surface vessel, and reduce the overall navigation control efficiency over a long period of time.

[0004] In the 1920s, the classic PID algorithm was applied to bow control to create automatic steering systems, but the resulting fluctuations, oscillations, and overshoots led to excessively frequent steering. With the maturation of modern control theory, many emerging control theories have been applied to ship bow disturbance rejection control, such as H... ∞ There are various types of disturbance rejection control, such as passive control, humanoid intelligent control, and iterative sliding mode control. However, these methods usually require a precise mathematical model of the controlled system, which is difficult to implement in engineering. At the same time, these passive methods based on error feedback to achieve the desired value often lag behind the impact of disturbances. Therefore, a number of active disturbance rejection control technologies, which are different from passive disturbance rejection control, have gradually emerged.

[0005] In reality, disturbances and uncertainties are widespread in USV control systems. These include: USV model parameter perturbations, unmodeled hydrodynamics of the environment, additional forces from wind, waves, and currents, as well as high-frequency bow changes and low-frequency lateral drift of the hull, all of which can significantly impact USV motion. To address the disturbance rejection problem of USVs, some researchers have adopted active disturbance rejection methods to suppress disturbances and uncertainties, enabling the controller to achieve a degree of object independence. A classic example is Active Disturbance Rejection Control (ADRC), proposed by Han Jingqing. Its core idea is to actively extract disturbance information from the output of the controlled system and eliminate it using control signals before the disturbance significantly affects the overall system output.

[0006] The classic ADRC completely abandons the model and uses a general nonlinear function to estimate the system state, which leads to large fluctuations in state observations when the system parameters are perturbed. Summary of the Invention

[0007] The purpose of this invention is to solve the problem that the additional rolling motion caused by waves due to time-varying sea wave interference in the navigation environment causes the bow control controller to frequently steer, which over time reduces the lifespan of the servo motor, shortens the endurance of the unmanned surface vessel (USV), and reduces the overall navigation control efficiency. This invention provides a bow disturbance rejection control method for USVs that has a strong filtering effect on the matching sea state, enabling smoother servo steering, achieving bow stability of the USV, and ensuring that the USV can complete a series of complex tasks such as path tracking, target tracking, and swarm movement. It also exhibits strong robustness against external interference and parameter perturbations.

[0008] The objective of this invention is achieved through the following technical solution:

[0009] A method for bow disturbance rejection control of an unmanned surface vessel includes the following steps:

[0010] Step 1: Under the condition of sea wave interference, measure various physical parameters of the unmanned surface vessel (USV) to obtain the second-order Nomoto nonlinear model of the USV's bow direction. Based on the second-order Nomoto nonlinear model, derive the ship and rudder control model under the condition of sea wave interference.

[0011] Step 2: Determine the desired heading angle ψ of the unmanned surface vessel. d The input to the second-order tracking differentiator yields the tracking signal x1 and the differential signal x2;

[0012] Step 3: The sensor inputs the current unmanned surface vessel heading value ψ into the high-gain extended state observer, and outputs the observed state value: heading angle. Bow angular velocity Total interference;

[0013] Step 4: Subtract the heading and angular velocity information output from the high-gain extended state observer from the tracking signal x1 and the differential signal x2 output from the second-order tracking differentiator to obtain the error signal. Input the error signal and the observed total disturbance signal into the PD error feedback controller, and the PD error feedback controller outputs the desired rudder angle δ of the control system. d ;

[0014] Step 5: Input the desired rudder angle δ of the control system into the ship and steering gear control model. d The actual heading angle is used to control the heading of the unmanned surface vessel, and then the process returns to the second step to perform the next disturbance rejection control.

[0015] Furthermore, the ship and steering gear control model under wave interference described in step one is as follows:

[0016]

[0017] in: δ is the USV's heading angular velocity; ψ is the heading angle; δ is the servo angle; T is the USV's time constant, i.e., the following exponent; K is the USV's heading control gain, i.e., the gyratory exponent; ΔT is the USV's time constant perturbation; ΔK is the USV's heading control gain and perturbation; ω is the external disturbance experienced by the USV; a in the nonlinear term i (i = 0, 1, 2, 3) are constant coefficients, which are determined through parameter identification calculation.

[0018] Furthermore, the differential equation of the second-order differential tracker is expressed as:

[0019]

[0020] fst(v1,v2,v,r,h0) is the steepest synthesis function, specifically expressed as:

[0021]

[0022] Where v is the desired heading value, v1 is the tracking estimate of v, v2 is the first-order differential signal of v, r is the tracking velocity factor, and h0 is the filtering factor.

[0023] Furthermore,

[0024] The observed unmanned surface vessel's expansion state is represented as follows:

[0025]

[0026] Where: x1 = ψ, x3=Φ(x,w,δ)=f(x2)+ω(t)+(b-b0)δ represents the uncertain dynamics with model parameter perturbations, ω(t) is the external disturbance, and b is the indeterminate control gain, estimated as b≈b0, and The high-gain extended state observer is then represented as:

[0027]

[0028] In the formula: All are observer observations, α i (i = 1, 2, 3) are all positive constants, and α i (i = 1, 2, should be reasonably selected to make the polynomial For Hurwitz; ε (ε << 1) is the high-gain parameter, φ0 is the nominal model of φ, used as a model-aided tracking for the observer.

[0029] Furthermore, the PD error feedback controller is:

[0030]

[0031] Wherein, the saturation function is sat(y) = min{1,|y|}·sign(y), and x1 = ψ. k represents the disturbance propagation state estimated by the observer. P k d The control gain of the PD controller, S is the saturated output value of the rudder angle, and δ is the control gain of the PD controller. d This represents the desired rudder angle output.

[0032] This invention designs a model-aided, fast-converging observer that combines classical ADRC, high-gain observers, and model-aided extended state observers. This solves the problem of heading disturbance rejection control accuracy caused by model perturbations in disturbed environments, and achieves rapid tracking of the desired heading. It makes the unmanned surface vessel (USV) highly robust to external disturbances and parameter perturbations, has a strong filtering effect on matching sea states, and enables smoother steering. This achievement has practical significance in both theoretical research and engineering fields for USV heading stability. Attached Figure Description

[0033] Figure 1 This is a structural diagram of an improved active disturbance rejection control system;

[0034] Figure 2 This is a diagram of the ship's bow motion control structure;

[0035] Figure 3 The equivalent interference of the simulated ocean waves in this embodiment of the invention is obtained by setting the main frequency of the simulated ocean waves ω0=0.61rad / s and the adjustable gain K0=0.0244;

[0036] Figure 4 The simulation test is a constant expected heading angle under the nominal model without disturbance. (a) shows the heading angle control effect of three controllers without external interference when the expected heading angle is 30°, and (b) shows the corresponding steering angle output.

[0037] Figure 5 (a) is a schematic diagram of the bow angle control effect in the simulation test of the fixed expected bow angle under the nominal model to simulate sea wave disturbance, and (b) is the corresponding steering angle output;

[0038] Figure 6 Simulation experiment of sinusoidal desired heading angle under nominal model to simulate sea wave disturbance, where (a) is the desired heading angle of ψ. desire (a) shows the heading angle control effect of three controllers with external disturbances under 10sin(0.05πt), and (b) shows the corresponding steering angle output.

[0039] Figure 7 This is a simulation experiment of the constant expected heading angle under the perturbation model to simulate wave disturbance, with the perturbation parameter set to K. * =K + 0.2*ηw ,T * =T-0.3*η w (a) shows the heading angle control effect of three controllers with disturbances and model parameter perturbations, and (b) shows the corresponding steering angle output.

[0040] Figure 8 This is a flowchart of the bow disturbance rejection control method for the unmanned surface vessel of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] This invention provides a method for bow disturbance rejection control of an unmanned surface vessel (USV). The method involves using a tracking differentiator to rapidly track the input desired bow angle signal to obtain a tracking value, designing a high-gain extended observer to observe the current state of the USV to obtain an observed value, calculating the error between the observed and tracked values, using an error feedback control law to output the desired rudder angle, and using the observer's estimate of the total disturbance as compensation to obtain the bow disturbance rejection control law. Following these steps, the USV is controlled to achieve bow disturbance rejection.

[0043] like Figure 1 As shown in the figure, this embodiment of the invention designs a bow disturbance rejection controller for an unmanned surface vessel, which consists of three parts connected in series: a second-order tracking differentiator, a high-gain extended state observer, and a PD error feedback controller. The high-gain parameter ε in the high-gain extended state observer can quickly observe and compensate for the state expanded by internal and external disturbances, and the control law output is realized through the PD error feedback controller.

[0044] like Figure 8 As shown, the method specifically includes:

[0045] Step 1: Under conditions of wave interference (such as...) Figure 3 As shown, various physical parameters of the unmanned surface vessel (USV) are measured through parameter identification and other methods to obtain a second-order Nomoto nonlinear model of the USV's heading. This second-order Nomoto nonlinear model is a heading response model, a differential equation describing the relationship between the rudder angle and the heading. It describes the ideal ship and rudder control model under no-interference conditions. Then, based on this second-order Nomoto nonlinear model, the ship and rudder control model under wave interference is derived, i.e.:

[0046]

[0047] in: δ is the USV's heading angular velocity; ψ is the heading angle; δ is the servo angle; T is the USV's time constant, i.e., the following exponent; K is the USV's heading control gain, i.e., the gyratory exponent; ΔT is the USV's time constant perturbation; ΔK is the USV's heading control gain and perturbation; ω is the external disturbance experienced by the USV; a in the nonlinear term i (i = 0, 1, 2, 3) are constant coefficients, which are generally determined through parameter identification calculation.

[0048] Step 2: Determine the desired heading angle ψ of the unmanned surface vessel. d The second-order tracking differentiator is input to obtain the tracking signal x1 and the differential signal x2; the TD differential equation of the second-order differential tracker is expressed as:

[0049]

[0050] fst(v1,v2,v,r,h0) is the steepest synthesis function, specifically expressed as:

[0051]

[0052] Where v is the desired heading value, v1 is the tracking estimate of v, v2 is the first-order differential signal of v, r is the tracking velocity factor, and h0 is the filtering factor.

[0053] Step 3: The sensor inputs the current unmanned surface vessel heading value ψ into the high-gain extended state observer, and outputs the observed state value: heading angle. Bow angular velocity Total interference. The observed unmanned surface vessel's expanded state is represented as:

[0054]

[0055] Where: x1 = ψ, x3=Φ(x,w,δ)=f(x2)+ω(t)+(b-b0)δ represents the uncertain dynamics with model parameter perturbations, ω(t) is the external disturbance, and b is the indeterminate control gain, estimated as b≈b0, and The high-gain extended state observer is then represented as:

[0056]

[0057] In the formula: All are observer observations, α i (i = 1, 2, 3) are all positive constants, and α i (i = 1, 2, should be reasonably selected to make the polynomial For Hurwitz; ε (ε<<1) is the high-gain parameter, and φ0 is the nominal model of φ, which serves as the model-aided tracking for the observer.

[0058] The sensor can be an inertial navigation system containing a magnetometer, which can measure the due north direction to calculate the bow heading value ψ of the unmanned surface vessel.

[0059] Step 4: Subtract the heading and angular velocity information from the internal state information of the heading response system output by the high-gain extended state observer from the desired heading approximation and its approximate derivative output by the tracking differentiator to obtain the error signal. Input the error signal and the observed total disturbance signal into the PD error feedback controller, and the PD error feedback controller outputs the desired rudder angle δ of the control system. d The PD error feedback controller is:

[0060]

[0061] Wherein, the saturation function is sat(y) = min{1,|y|}·sign(y), and x1 = ψ. k represents the disturbance propagation state estimated by the observer. P k d The control gain of the PD controller, S is the saturated output value of the rudder angle, and δ is the control gain of the PD controller. d This represents the desired rudder angle output.

[0062] Step 5: As Figure 2 As shown, the actuator (ship and steering gear control model) is input with the desired rudder angle δ. d Steering is performed to control the ship's heading, and then the process returns to step two for the next disturbance control operation.

[0063] This invention addresses the bow disturbance rejection control problem of unmanned surface vessels in the presence of wave interference and parameter perturbations. It proposes an improved active disturbance rejection control method based on a model-aided high-gain extended state observer and conducts simulation experiments on this type of bow disturbance rejection controller. Figures 4-7 Simulations were performed under both disturbed and undisturbed conditions using PID control and nonlinear active disturbance rejection control as a comparison, for example: Figure 7 Under the perturbation model, the maximum fluctuation of the desired heading angle under simulated wave disturbance is 8.14% for PID control, 4.8% for nonlinear active disturbance rejection control, and 0.35% for improved active disturbance rejection control. The comparison shows that the HGESO designed in this invention has good filtering characteristics against wave disturbance and can achieve rapid tracking of the USV state under the perturbation model, making the USV more robust to external disturbances and parameter perturbations.

[0064] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for bow disturbance rejection control of an unmanned surface vessel, characterized in that: Includes the following steps: Step 1: Under the condition of sea wave interference, measure various physical parameters of the unmanned surface vessel (USV) to obtain the second-order Nomoto nonlinear model of the USV's bow direction. Based on the second-order Nomoto nonlinear model, derive the ship and rudder control model under the condition of sea wave interference. Step 2: Set the desired heading value of the unmanned surface vessel. The tracking signal is obtained by inputting a second-order tracking differentiator. and differential signal ; Step 3: The sensor will register the current heading value of the unmanned surface vessel. Input a high-gain extended state observer, output observed state value: heading angle angular velocity of the bow Total interference; Step 4: Combine the heading angle and angular velocity information output from the high-gain extended state observer with the tracking signal output from the second-order tracking differentiator. and differential signal The error signal is obtained by subtraction. The error signal and the observed total disturbance signal are input into the PD error feedback controller, which then outputs the desired rudder angle for the control system. ; Step 5: Input the desired rudder angle into the ship and steering gear control model. The actual heading angle is used to control the heading of the unmanned surface vessel, and then the process returns to step two for the next disturbance rejection control. The observed unmanned surface vessel's expansion state is represented as follows: (1.4)； in: , , For uncertain dynamics with perturbations in model parameters, External disturbances For indeterminate control gain, the estimate is: ,and ; The high-gain extended state observer is then represented as: (1.5)； In the formula: , , All are observations from the observer. , , The appropriate value should be selected to make the polynomial For Hurwitz; ,in , for The nominal model serves as the model-aided tracking for the observer; The PD error feedback controller is: (1.6)； Wherein, saturation function , , , The disturbance spread state estimated by the observer. , The control gain of the PD controller. This represents the saturation output value of the rudder angle. This represents the desired rudder angle output.

2. The bow disturbance rejection control method for an unmanned surface vessel as described in claim 1, characterized in that: The ship and steering gear control model under wave interference described in step one is as follows: (1.1)； in: Let be the bow angular velocity of the unmanned surface vessel; Heading angle; The rudder angle of the servo motor; The unmanned surface vessel's time constant is the following index. This refers to the bow control gain of the unmanned surface vessel, also known as the gyrability index. Perturbation of the time constant of the unmanned surface vessel; For unmanned surface vessel (USV) bow control gain and perturbation; External disturbances experienced by the unmanned surface vessel; nonlinear terms in The constant coefficients are determined through parameter identification calculations, where .

3. The bow disturbance rejection control method for an unmanned surface vessel as described in claim 2, characterized in that: The differential equation of the second-order tracking differentiator is expressed as: (1.2)； The fastest synthesis function is specifically expressed as: (1.3)； in, For the desired heading value, right Perform tracking and estimation. for The first-order differential signal, It is the tracking speed factor. It is the filter factor.

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