Robust control method, device and system for under-actuated unmanned ship, and storage medium

Abstract

The invention discloses an underactuated unmanned ship robust control method, device and system and a storage medium, and the method comprises the steps: measuring signals through a measurement sensor according to the course, motion attitude, rudder angle and the like of an unmanned ship, and employing an improved ESO and backstepping control combination method under an external effect; and the dynamic compensation-based unmanned ship water surface control of the unmanned ship in a random interference state is realized. By adopting the technical scheme of the invention, the accurate identification and estimation of the external disturbance are realized, and the robustness problem of the course control of the unmanned ship under the influence of random disturbance can be effectively solved through dynamic compensation, so that the course control precision and the adaptive capacity of the unmanned ship are improved.

Description

Technical Field

[0001] The present invention belongs to the field of ship motion control, and in particular relates to a robust control method and device, a system and a storage medium for an underactuated unmanned boat. Background Art

[0002] Since the beginning of the 21st century, the ocean has become a strategic location for promoting economic development and improving the comprehensive strength of countries around the world. With the rapid development of computer technology and artificial intelligence, unmanned systems have been widely studied and applied. As a representative of surface intelligent equipment, unmanned boats have good surface autonomous navigation capabilities and are increasingly widely used in military and civilian fields, such as sea area detection and reconnaissance, cargo transportation, marine exploration, and maritime rescue.

[0003] In various complex mission scenarios, reliable heading control is the key technology for unmanned boats to complete autonomous navigation. After years of development, related control theories have achieved many valuable practical application results. At present, the control methods of unmanned boat heading mainly include PID algorithm, sliding mode control, optimal control, backstepping control, etc. However, the motion process of ships has characteristics such as nonlinearity and obvious time lag. Practice has found that the above controllers are difficult to meet higher control accuracy and wind and wave resistance requirements. In actual work, PID is still the most widely used control method, but its parameter setting has a great influence on the control. When the dynamic characteristics of the control object change, the controller parameters must be re-adjusted to ensure the performance of the control system. In order to solve this problem, Professor Han Jingqing proposed active disturbance rejection control using the extended state observer, but it has many parameters to adjust and is difficult to apply to engineering practice. Professor Gao Zhiqiang developed a linear active disturbance rejection controller (LADRC) based on active disturbance rejection control, using the linear extended state observer (LESO) and the state error feedback control law to estimate and eliminate disturbances respectively. It has been applied to control applications such as power systems, aerospace, shipbuilding industry and hydraulic systems.

[0004] Conventional backstepping control methods are sensitive to external disturbances and show certain limitations in dealing with external disturbances in the system. When the system is subject to greater disturbances or uncertainties, the control performance of the backstepping method will be greatly affected. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method and device, system and storage medium for robust control of an underactuated unmanned boat, so as to effectively solve the problem of compensation of the unmanned boat's heading control for external interference, and to accurately identify and estimate the nonlinear terms and external disturbances in the system, thereby reducing the influence of external interference on the accuracy of the unmanned boat's heading control.

[0006] To achieve the above object, the present invention adopts the following technical solution:

[0007] A robust control method for an underactuated unmanned boat, comprising:

[0008] Step S1, constructing a heading control model of the unmanned boat;

[0009] Step S2, constructing a steering gear model of the unmanned boat;

[0010] Step S3, constructing a disturbance model of the unmanned boat being subjected to external disturbance forces during navigation;

[0011] Step S4, constructing an improved extended state observer according to the heading control model of the unmanned boat, the steering gear model of the unmanned boat and the interference model;

[0012] Step S5: Compensate for interference in real time according to the improved extended state observer.

[0013] Preferably, in step S5, a backstepping controller is designed for the heading control system according to the Lyapunov stability principle, and interference is compensated in real time based on an improved extended state observer.

[0014] Preferably, in the improved extended state observer, the fal function in the ESO is designed as a falN function.

[0015] The present invention also provides a robust control device for an underactuated unmanned boat, comprising:

[0016] The first building module is used to build a heading control model of the unmanned boat;

[0017] The second building module is used to build a steering gear model of the unmanned boat;

[0018] The third building module is used to build a disturbance model of the unmanned boat being subjected to external disturbance forces during navigation;

[0019] The fourth building module is used to build an improved extended state observer according to the heading control model of the unmanned boat, the steering gear model of the unmanned boat and the interference model;

[0020] A control module is provided for real-time compensation of disturbances based on an improved extended state observer.

[0021] Preferably, the control module designs a backstepping controller for the heading control system according to the Lyapunov stability principle, and performs real-time compensation for interference based on an improved extended state observer.

[0022] Preferably, in the improved extended state observer, the fal function in the ESO is designed as a falN function.

[0023] The present invention also provides an underactuated unmanned boat robust control system, characterized in that it comprises: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes the underactuated unmanned boat robust control method when executed by the processor.

[0024] The present invention also provides a storage medium, on which a computer program is stored, and the computer program executes the robust control method of the under-actuated unmanned boat when running.

[0025] The present invention adopts an improved extended state observer, which can effectively estimate the lumped disturbance of nonlinearity and external interference by measuring only the ship input signal and the heading signal, without the need for other measurement means; the control law designed by the present invention can effectively compensate for the external interference and enhance the robustness of the heading control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0027] Figure 1 This is a flow chart of a robust control method for an underactuated unmanned boat according to an embodiment of the present invention;

[0028] Figure 2 This is the model diagram of the unmanned boat rudder response;

[0029] Figure 3 This is the effect diagram of heading control without interference;

[0030] Figure 4 This is the effect diagram of heading control under sinusoidal interference;

[0031] Figure 5 This is the effect diagram of heading control under random interference;

[0032] Figure 6 This is the effect diagram of heading control under constant interference. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] Embodiment 1:

[0036] like Figure 1 As shown, an embodiment of the present invention provides a robust control method for an underactuated unmanned boat, which uses a combination of improved ESO and backstepping method to accurately identify and estimate external interference according to the heading signal of the unmanned boat heading measurement equipment and the input signal of the steering gear feedback, thereby achieving effective compensation for the total interference and control of the unmanned boat, including:

[0037] Step S1: Establishing the heading control model of the unmanned boat

[0038] According to the characteristics of the ship motion model, the heading control model of the unmanned boat is established based on the second-order linear response mathematical model.

[0039]

[0040] Among them, ψ is the heading angle of the unmanned boat, r is the bow angular velocity of the unmanned boat, δ a is the rudder angle of the unmanned boat, ω is the external unknown disturbance, α w =-1 / T, K is the turning index of the ship, b=K / T is the control system gain, and τ is the control input of the ship system.

[0041] Step S2: Establishing the steering gear model of the unmanned boat

[0042] Using the first-order inertia model to express δ in equation (1) a , establish the following unmanned boat steering model:

[0043]

[0044] Among them, K E is the servo control gain, T E is the time constant of the servo, δ r is the command rudder angle, δ a is the actual rudder angle, such as Figure 2 shown.

[0045] Step S3: Establish a model of the wind, wave and current disturbances to which the unmanned boat is subjected during navigation

[0046] Establish and add the external wind, wave and current disturbance ω that the unmanned boat is subject to during navigation. The interference of ocean current on the unmanned boat is generally a constant value; the interference form of wind flow force is relatively simple and can be expressed in the form of white noise:

[0047] ω wind =c×J gn (3)

[0048] Where c is a constant, J gn is zero-mean Gaussian white noise,

[0049] The influence of wave disturbance on the unmanned boat is relatively complex. The following formula is used to simulate the wave disturbance and equate the influence of the wave to the influence on the rudder angle of the unmanned boat:

[0050]

[0051] Where ω(s) is white noise with a mean of 0, L(s) is the second-order ocean wave transfer function, and σ w is a constant describing the wave intensity, ω0 is the wave frequency, and ξ is the damping coefficient.

[0052] Step S4: Establishing an extended state observer model

[0053] Let x1 = ψ, x2 = r, and transform equation (1) into the following form:

[0054]

[0055] Among them, x1 and x2 are the state variables of the system, ω(t) is the external disturbance, b is the controller gain, and u is the input. Let z1 = x1, z2 = x2, and expand the total disturbance f(x1, x2, ω(t)) to a new state z3. For the above second-order system, it is necessary to design a third-order extended state observer, which can be written as:

[0056]

[0057] Among them, β1, β2, β3, α1, α2, δ, and b are all adjustable parameters of ESO, δ is the observer filter factor, b0 is the estimated value of b, α1 is generally taken as 1 / 2, α2 is generally taken as 1 / 4, β1, β2, and β3 are observer gain coefficients, which can be calculated by the observer bandwidth principle. The fal function expression is as follows:

[0058]

[0059] Formula (6) is improved by designing the fal function in ESO as the falN function, and the structure is improved based on the error to improve the utilization rate of the extended state observer for the error e. The specific form is as follows:

[0060]

[0061] The falN function is expressed as follows:

[0062]

[0063] The falN function is written as follows:

[0064]

[0065] Then formula (8) can be written as:

[0066]

[0067] Among them, γ1=β1, γ2(t)=β2ξ1(t), γ3(t)=β3ξ2(t). For equation (10), define e(t)=z1(t)-x1(t), e2(t)=z2(t)-x2(t), e3(t)=z3(t)-x3(t), then the derivative of the error is expressed as:

[0068]

[0069] The error equation is expressed as:

[0070]

[0071] Among them, W1=e1(t), W2=e2(t)-γ1e1(t),

[0072] Then the characteristic equation is;

[0073]

[0074] Write the above formula as

[0075] s3λ 3 +s2λ 2 +s1λ 1 +s0=0 (14)

[0076] To ensure the stability of the system, all characteristic roots of equation (13) must be negative, that is:

[0077]

[0078] Regarding the selection of parameters β1, β2, and β3, as long as the time-varying gains γ1, γ2(t), and γ3(t) are greater than 0 and bounded, the conditions required by equation (15) can be met and the global stability of the system can be guaranteed.

[0079] Substituting z1-y for the falN function, the improved ESO equation is:

[0080]

[0081] Let τ1=β1,τ2=β2s+β2β1,τ3=β3s2+β3β1s+β3β2, and make Laplace transformation to get:

[0082]

[0083] State quantity z i The error of (i=1,2,3) can be expressed as:

[0084]

[0085] Substituting equation (17) into equation (18), the Laplace transform expression of the steady-state error is:

[0086]

[0087] Define y(s) = 1 / s, u(s) = 1 / s, then the steady-state error of the system is

[0088]

[0089] Therefore, the steady-state errors of the three state quantities all converge to 0. When g(x1(t),x2(t),ω(t),t)≠0, take the constant g0>0, and stipulate that g(x1(t),x2(t),ω(t),t)<g0, then when the system reaches a stable state, and

[0090] At this point, it can be seen that the improved ESO has better convergence and observation accuracy, which helps to improve the control performance of the entire control system.

[0091] Step S5: Real-time compensation of interference is performed according to the extended state observer to achieve accurate and rapid tracking of the heading of the unmanned boat.

[0092] Let ψ = x1, r = x2, f = α w r+ω. Use the backstepping method to design the USV heading controller, assuming that the reference signal y d is continuous and has nth-order derivative, and the heading error is defined as e1 = y d -x1. According to the Lyapunov stability principle, a backstepping controller is designed for the heading control system, and the disturbance is compensated in real time based on z3 obtained by the observer in step 4.

[0093] Construct the first Lyapunov function as:

[0094]

[0095] Then we can get:

[0096]

[0097] According to Lyapunov's stability theorem, equation (22) should be negative definite, that is In order to achieve this goal, the virtual control quantity is introduced Wherein k1 is a parameter to be designed, and k1>0.

[0098] Now define the second error:

[0099] e2=x2-ρ1 (23)

[0100] Construct a second Lyapunov function:

[0101]

[0102] Then the derivative of the above formula is:

[0103]

[0104] Then the steering gear control quantity δ a Design the following control law:

[0105]

[0106] Can get Where z3 is the estimated value of the total disturbance by the improved extended state observer. According to the Lyapunov stability principle, the system reaches a stable state at this time.

[0107] Apply the control law to the heading control under different disturbance conditions. Figure 3 This is the effect diagram of heading control without interference; Figure 4 This is the effect diagram of heading control under sinusoidal interference; Figure 5 This is the effect diagram of heading control under random interference;

[0108] Figure 6 It can be seen that the method proposed in the present invention can effectively solve the robustness problem of the unmanned boat heading control under the influence of random interference, thereby improving the accuracy and adaptability of the unmanned boat heading control.

[0109] Embodiment 2:

[0110] The embodiment of the present invention further provides a robust control device for an underactuated unmanned boat, comprising:

[0111] The first building module is used to build a heading control model of the unmanned boat;

[0112] The second building module is used to build a steering gear model of the unmanned boat;

[0113] The third building module is used to build a model of the interference of wind, waves and currents on the unmanned boat during navigation;

[0114] The fourth building module is used to build an improved extended state observer according to the heading control model of the unmanned boat, the steering gear model of the unmanned boat and the interference model;

[0115] A control module is provided for real-time compensation of disturbances based on an improved extended state observer.

[0116] As an implementation method of an embodiment of the present invention, the control module designs a backstepping controller for the heading control system according to the Lyapunov stability principle, and performs real-time compensation for interference based on an improved extended state observer.

[0117] As an implementation of the embodiment of the present invention, in the improved extended state observer, the fal function in the ESO is designed as a falN function.

[0118] Embodiment 3:

[0119] An embodiment of the present invention also provides an underactuated unmanned boat robust control system, characterized in that it includes: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes the underactuated unmanned boat robust control method when executed by the processor.

[0120] Embodiment 4:

[0121] An embodiment of the present invention further provides a storage medium, on which a computer program is stored, and the computer program executes a robust control method for an underactuated unmanned boat when running.

[0122] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A robust control method for an underactuated unmanned boat, characterized in that: include: Step S1, constructing a heading control model of the unmanned boat; Step S2, constructing a steering gear model of the unmanned boat; Step S3, constructing a disturbance model of the unmanned boat being subjected to external disturbance forces during navigation; Step S4, constructing an improved extended state observer according to the heading control model of the unmanned boat, the steering gear model of the unmanned boat and the interference model; Step S5: accurately identify and estimate the total interference according to the improved extended state observer.

2. The robust control method for an underactuated unmanned vehicle according to claim 1, characterized in that: In step S5, a backstepping controller is designed for the heading control system according to the Lyapunov stability principle, and the disturbance is compensated in real time based on the improved extended state observer.

3. The robust control method for an underactuated unmanned vehicle according to claim 1, characterized in that: In the improved extended state observer, the fal function in ESO is designed as the falN function.

4. A robust control device for an underactuated unmanned boat, characterized in that: include: The first building module is used to build a heading control model of the unmanned boat; The second building module is used to build a steering gear model of the unmanned boat; The third building module is used to build a disturbance model of the unmanned boat being subjected to external disturbance forces during navigation; The fourth building module is used to build an improved extended state observer according to the heading control model of the unmanned boat, the steering gear model of the unmanned boat and the interference model; A control module is provided for real-time compensation of disturbances based on an improved extended state observer.

5. The robust control device for an underactuated unmanned boat according to claim 4, characterized in that: The control module designs a backstepping controller for the heading control system according to the Lyapunov stability principle, and performs real-time compensation for disturbances based on an improved extended state observer.

6. The robust control device for an underactuated unmanned boat according to claim 5, characterized in that: In the improved extended state observer, the fal function in ESO is designed as the falN function.

7. A robust control system for an underactuated unmanned boat, characterized in that: include: A memory and a processor, wherein the memory stores a computer program executed by the processor, and when the computer program is executed by the processor, the computer program executes the robust control method for an under-actuated unmanned boat as described in any one of claims 1 to 3.

8. A storage medium, characterized in that: The storage medium stores a computer program, which, when running, executes the robust control method for an under-actuated unmanned boat as described in any one of claims 1 to 3.

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