Cooperative control method of multi-under-actuated unmanned ship system under input saturation constraint

Abstract

The invention belongs to the technical field of unmanned ship control, and particularly discloses a cooperative control method of a multi-underactuated unmanned ship system under input saturation constraint, comprising the following steps: step S1, establishing an all-drive model of the multi-underactuated unmanned ship system; s2, designing a fixed time disturbance observer; s3, designing a fixed-time adaptive RBF neural network observer, and estimating an input saturation term; s4, establishing a cooperative tracking error system according to the cooperative control target and the network topology structure; s5, establishing a fixed time terminal sliding mode surface, and obtaining a distributed terminal sliding mode control law; and S6, constructing a fixed threshold event triggering mechanism, designing a distributed event triggering-terminal sliding mode controller, and realizing cooperative tracking control of the system through an output instruction of the controller. According to the invention, two indexes of'rapid cooperative control 'and'communication resource saving' are realized at the same time, and the problem of fixed-time cooperative tracking control of the multi-under-actuated unmanned ship system is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned ship control, and particularly relates to a cooperative control method for a multi-undersea-driven unmanned ship system under input saturation constraints. Background Technique

[0002] With the development of marine resource development and intelligent shipping, the cooperative control technology of multi-unmanned ships (USV) has shown important value in fields such as environmental monitoring and cluster search and rescue. Currently, in order to improve control efficiency and meet practical needs, "fast cooperative control" has become one of the focus issues concerned by experts and scholars in the control field. At the same time, considering limited communication resources, how to "save communication resources" on the basis of "fast cooperative control" and further optimize control performance is the research focus of the cooperative control of multi-unmanned ship systems. However, the existing related research results have the following deficiencies: Most of the existing results only study one of them, that is, only consider "fast cooperative control" or "save communication resources", and there are few research results considering both. In fact, event-triggered control is a consensus method to solve the problem of "saving communication resources", and the introduction of the event-triggered mechanism will inevitably reduce control efficiency. How to integrate the event-triggered control strategy into "fast cooperative control" to achieve a "win-win" in control performance still poses a huge challenge. Achieving "fast cooperative control" implies that the speed of the unmanned ship may be very fast, which also means that the corresponding control input is likely to saturate. If no compensation is made for it, the overall control will fail. However, the existing results lack research in this regard. And due to the characteristics of the unmanned ship system model such as underactuation and strong nonlinearity, the design process of the corresponding controller is very complex and the design difficulty is very large.

[0003] In summary, there is a need for a cooperative control method for a multi-undersea-driven unmanned ship system under input saturation constraints to solve the above problems in the prior art. Summary of the Invention

[0004] The present invention provides a cooperative control method for a multi-undersea-driven unmanned ship system under input saturation constraints, which solves the fixed-time cooperative tracking problem of the multi-undersea-driven unmanned ship system.

[0005] To achieve the purpose of solving the above technical problems, the present invention adopts the following technical solutions: A cooperative control method for a multi-undersea-driven unmanned ship system under input saturation constraints includes the following steps: Step S1, establish a fully actuated model of the multi-undersea-driven unmanned ship system; Step S2, design a fixed-time disturbance observer for the fully actuated model to achieve fixed-time estimation of the disturbance; Step S3: Design a fixed-time adaptive RBF neural network observer for estimating the input saturation term of the multi- underactuated unmanned surface vehicle system; Step S4: Establish a cooperative tracking error system according to the cooperative control objective and the network topology structure; Step S5: Establish a fixed-time terminal sliding mode surface and obtain an equivalent distributed terminal sliding mode control law by taking its derivative; Step S6: Construct a fixed-threshold event-triggering mechanism, design a distributed event-triggering - terminal sliding mode controller in combination with the sliding mode band idea, and realize the cooperative tracking control of the multi- underactuated unmanned surface vehicle system through the output command of the controller.

[0006] In some embodiments of the present invention, the step S1 includes the following steps: Establish a dynamic mathematical model of the three-degree-of-freedom multi- underactuated unmanned surface vehicle system under input saturation constraints; Elevate and reduce the dimension of the motion state parameters in the kinematic model to construct an equivalent fully actuated model of the underactuated unmanned surface vehicle system; Introduce saturation input constraints into the formula of the fully actuated model.

[0007] In some embodiments of the present invention, the formula of the fully actuated model is: ; where B i is the state transition matrix, q i is the position information in the inertial coordinate system, τ ci is the control input information of the multi- underactuated unmanned surface vehicle system without saturation constraints; Δτ i is the difference caused by the saturated input; d i is the external disturbance information; f i is the non-linear term information.

[0008] In some embodiments of the present invention, the calculation formula of the difference Δτ i caused by the saturated input is:

[0009] where is the control input of the fully actuated system; τ u i is the control input generated by the thruster under saturation constraints, τ r i is the control input generated by the rudder under saturation constraints; τ ci =[τ ci,1 , τ ci,2 T is the control input of the unmanned surface vehicle under saturation constraints, τ ci,1 ​The control input generated by the thruster without saturation constraint, τ ci,2 The control input generated by the rudder without saturation constraint, Δτ u i The control input τ under saturation constraint u i The difference between the control input τ under saturation constraint ci,1 and the control input τ without saturation constraint, Δτ r i The control input τ under saturation constraint r i The difference between the control input τ under saturation constraint ci,2 and the control input τ without saturation constraint; and Has an input saturation constraint and satisfies the following formula:

[0010]

[0011] where τ max Is the saturation upper limit of the system input, τ min Is the saturation lower limit of the system input.

[0012] In some embodiments of the present invention, the fixed threshold event-triggering mechanism is designed as follows:

[0013] where t i,m k+1 Represents the (k + 1)-th event-triggering moment of the m-th control input of the i-th unmanned ship; t i,m k Represents the k-th event-triggering moment of the m-th control input of the i-th unmanned ship; m = 1, 2; at t moment, the event-triggering error function e im (t) = u * i,m (t) - τ ci,m (t), where u * i,m (t) is t The fixed-time terminal sliding mode control law at moment, σ im Is a positive constant. When the absolute value of e im (t) is greater than σ im , the controller is triggered to update, otherwise it is not updated.

[0014] In some embodiments of the present invention, the formula of the fixed-time RBF neural network observer in step S3 is as follows: ;

[0015] where: Is the velocity vector wi The estimated value of B i is the transition matrix, τ ci is the control input information of the multi-undersea vehicle system without saturation constraints; f i is the non-linear term information; is the disturbance information d i The estimated value; m = 1, 2; a0, is a positive diagonal gain matrix used to adjust the convergence speed of the observer; the power , , is the estimated value of the optimal weight W of the adaptive RBF neural network i The estimated value; is a bounded neuron radial basis function vector that satisfies , is a positive constant.

[0016] In some embodiments of the present invention, the adaptive update rule of the estimated value is:

[0017] where the observation error , is the velocity observation error of the i-th undersea vehicle in the x-axis direction, is the velocity observation error of the i-th undersea vehicle in the y-axis direction, and μ1 and μ2 are positive constants, representing the learning rate and damping coefficient of weight update respectively.

[0018] In some embodiments of the present invention, a control system for a multi-undersea vehicle system under input saturation constraints is provided, including: A model conversion module for converting the mathematical model of the multi-undersea vehicle system into a fully actuated model; A disturbance observation module for estimating environmental disturbances through a designed fixed-time disturbance observer; An input saturation estimation module for estimating the input saturation term of the multi-undersea vehicle system using a fixed-time adaptive RBF neural network observer; A controller design execution module for designing a fixed-time sliding mode surface and a fixed-threshold event trigger mechanism to obtain a controller, and also for outputting control instructions to achieve cooperative tracking control of the multi-undersea vehicle; A communication module for communicating with external devices.

[0019] In some embodiments of the present invention, an electronic device is provided, including: A processor, and a memory and a transceiver communicatively connected to the processor; The memory stores computer-executable instructions; the transceiver is used for receiving and transmitting data; The processor executes the computer-executable instructions stored in the memory to implement the control method of the above-mentioned multi-underactuated unmanned ship system.

[0020] In some embodiments of the present invention, a computer-readable storage medium is provided, characterized in that, The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the control method of the above-mentioned multi-underactuated unmanned ship system.

[0021] The technical solution of the present invention has the following technical effects compared with the prior art: Based on the idea of upgraded dimensionality reduction, the present invention constructs an equivalent fully actuated model of the underactuated unmanned ship system, laying an important foundation for subsequent simplification of controller design; adopting a fixed-time terminal sliding mode surface to ensure that the cooperative tracking error of multiple unmanned ships converges within a fixed time, designing a fixed-threshold event-triggering mechanism, introducing the idea of a sliding mode band, solving the fusion problem of event-triggering control and sliding mode control, and simultaneously achieving two indicators of "fast cooperative control" and "saving communication resources"; innovatively introducing a fixed-time adaptive RBF neural network to achieve input saturation compensation control, reducing the computational burden while enhancing the robustness of the system to changes in the parameters of the distributed event-triggering controller, making the designed cooperative control method of the multi-underactuated unmanned ship system more practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for description in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0023] Figure 1 It is a flowchart of the control method involved in the present invention.

[0024] Figure 2 It is the network topology structure of the multi-underactuated unmanned ship system involved in the present invention.

[0025] Figure 3 It is the cooperative tracking route map of the multi-underactuated unmanned ship system involved in the present invention when the desired trajectory is circular.

[0026] Figure 4 It is the estimated error of the disturbance in the x-axis direction of the multi-underactuated unmanned ship system involved in the present invention when the desired trajectory is circular.

[0027] Figure 5The estimation error of the disturbance in the y-axis direction when the desired trajectory of the multi-undersea-driven unmanned ship system involved in the present invention is circular.

[0028] Figure 6 The estimation error of the saturation compensation term in the x-axis direction when the desired trajectory of the multi-undersea-driven unmanned ship system involved in the present invention is circular.

[0029] Figure 7 The estimation error of the saturation compensation term in the y-axis direction when the desired trajectory of the multi-undersea-driven unmanned ship system involved in the present invention is circular.

[0030] Figure 8 For the control input τ of the multi-undersea-driven unmanned ship system involved in the present invention when the desired trajectory is circular u The event trigger time diagram.

[0031] Figure 9 For the control input τ of the multi-undersea-driven unmanned ship system involved in the present invention when the desired trajectory is circular r The event trigger time diagram.

[0032] Figure 10 It is a schematic structural diagram of the control system.

[0033] Figure 11 It is a schematic structural diagram of the electronic device.

[0034] Reference numerals: 100, control system; 110, model conversion module; 120, disturbance observation module; 130, input saturation estimation module; 140, controller design execution module; 150, communication module; 200, electronic device; 210, processor; 220, memory; 230, transceiver. Detailed implementation manners

[0035] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0036] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0037] Example 1: Reference Figure 1 As shown, this embodiment provides a control method for a multi-underactuated unmanned vessel system under input saturation constraints, comprising the following steps: Step S1: Establishing the full drive model of the multi-underactuated unmanned ship system Step S11: The multi-underactuated unmanned ship system involved in this embodiment is composed of N The first i strip( i =1,…, N )Mathematical model of underactuated unmanned ship system with external disturbance:

[0038] where η i =[x i ,y i ,ψ i ] T For the i The pose state vector of the unmanned ship, ν i =[u i ,v i ,r i ] T is the velocity state vector of the i-th unmanned ship. Specifically, x i ,y i , i They represent the longitudinal displacement, transverse displacement and yaw angle in the earth coordinate system respectively; u i 、v i 、r i They represent the longitudinal velocity, lateral velocity and yaw angular velocity in the inertial coordinate system respectively; τ i =[τ i u , 0,τ i r ] T represents the control input of the i-th unmanned ship, τ ei =[τ ei u , τ ei v , τ ei r ] T represents the external disturbance force on the unmanned ship in three degrees of freedom. The state transfer matrix J(η i ), inertia matrix M i , Coriolis force and centripetal force matrix C(v i ), damping matrix D i They are as follows:

[0039]

[0040] where d 11 、d 22 、d 23 、d 32 、d 33 represent hydrodynamic damping, and m 11 、m 22 、m 23 、m 32 、m 33 represent inertia and added mass, and they are all positive; where m 23 =m 32 , c i 13 =m 32 r i -m 22 v i , c i 23 =m 11 u i .

[0041] Step S12: Ascend and descend the order of the motion state parameters in the kinematic model to construct an equivalent fully actuated model of the underactuated unmanned ship system; According to formula (1), it can be obtained that:

[0042] According to the dynamic equation in formula (1) and the fact in the actual system , it can be obtained that:

[0043] where:

[0044] According to formula (2) and formula (3), it can be obtained that:

[0045] where:

[0046]

[0047] Define the position information in the inertial coordinate system , the non - linear term information , the control input information , the external disturbance information , and the state transition matrix of the system is:

[0048] Obviously, there is: and , the converted all-drive model can be obtained:

[0049] Step S13: Introduce a saturation input constraint into the formula of the all-drive model.

[0050] Considering the input saturation constraint of the system, formula (7) is rewritten as:

[0051] where the control input τ of the unmanned ship without saturation constraint ci = [τ ci,1 , τ ci,2 T , τ ci,1 is the control input generated by the thruster without saturation constraint, and τ ci,2 is the control input generated by the rudder without saturation constraint. The difference caused by the saturation input ; Δτ u i is the difference between the control input τ u i under saturation constraint and the control input τ ci,1 without saturation constraint, and Δτ r i is the difference between the control input τ r i under saturation constraint and the control input τ ci,2 without saturation constraint.

[0052] For the convenience of subsequent calculations, let be the velocity information of the i th ship in the inertial coordinate system.

[0053] Therefore, the converted all-drive model can be written as:

[0054] The input function is:

[0055]

[0056] where τ max is the saturation upper limit of the system input, and τ min is the saturation lower limit of the system input.

[0057] Step S2: Design a fixed-time disturbance observer for the all-drive model to achieve fixed-time estimation of the disturbance; Define h iis the derivative of the external disturbance information d i , so formula (9) can be written in the following form

[0058] where . The above system can be regarded as a non-coupled system, so there is:

[0059]

[0060] where w im , d im , τ z im , f im , h z im represent the i -th, i -th, z i -th, i -th, z i -th elements of the vectors w m , respectively, m = 1, 2. For a given vector x = [x1, x2, …, x n T , define the vector function sig α (x) = [sig α (x1), sig α (x2), …, sig α (x n )] T , and the function sig α (x i ) = |x i | α sign (x i ), where sign(·) is the sign function.

[0061] Design the following fixed-time disturbance observer according to formula (13):

[0062] where , are the estimated values of the velocity information w im and the disturbance information d im , respectively, , , k1 and k2 are control constants and are greater than 0, and ε is a parameter with a very small value.

[0063] ​Step S3: Design a fixed-time adaptive RBF neural network observer to estimate the input saturation term of the multi- underactuated unmanned surface vehicle system; Introduce an adaptive RBF neural network:

[0064] Among them, the ideal weight matrix of the neural network , , l is the number of neurons in the hidden layer of the neural network, is the approximation error vector of the neural network and satisfies , is a bounded constant, is a bounded neuron radial basis function vector, satisfying , is a positive constant. B i Δτ i represents the influence of the saturation difference on the dynamics of the system, which is the approximation of the saturation difference by the neural network under the ideal weight. Use the neural network to dynamically estimate B i Δτ i , so as to compensate for the saturation effect in the controller design and improve the robustness of the system.

[0065] The fixed-time adaptive RBF neural network observer is designed as follows:

[0066] Among them is the estimated value of the velocity vector w i , a0, is a positive diagonal gain matrix used to adjust the convergence speed of the observer; the power , , is the estimated value of the optimal weight W i of the adaptive RBF neural network. The adaptive update rule of is:

[0067]

[0068] Among them: Observation error, μ1 and μ2 are positive constants, representing the learning rate and damping coefficient of weight update respectively.

[0069] Step S4: Establish a cooperative tracking error system according to the cooperative control objective and network topology; Step S41: Determine the cooperative control objective of the multi- underactuated unmanned surface vehicle; The given desired formation position information is , where E i ( i = 1,…, Nis a 2D time-invariant column vector. The expected tracking trajectory position information is , and the corresponding expected tracking trajectory speed information is .

[0070] For the i th unmanned boat, at any initial state, there exists a time constant T > 0, such that holds, then the multi- underactuated unmanned boat system is said to be able to achieve fixed-time cooperative tracking control.

[0071] Step S42: Determine the network topology structure in the cooperative tracking control of the multi- underactuated unmanned boat; Referring to Figure 2 shown, N the interaction communication topology formed by the

[0072] underactuated unmanned boats contains at least one directed spanning tree, and the root node can directly obtain the expected trajectory information. Define the cooperative tracking error of the underactuated unmanned boat; i Define the cooperative tracking error of the

[0073]

[0074] th boat: i where z i1 , z i2 T is the position information of the cooperative tracking error of the i th boat, z i1 is the position information in the x-axis direction, and z i2 is the position information in the y-axis direction. is the speed information of the cooperative tracking error of the ith boat, is the speed information in the x-axis direction, is the speed information in the y-axis direction.

[0075] a ij is the element in the i rd row and j th column of the graph adjacency matrix, E i is the expected formation information of the i th boat, E j is the expected formation information of the j th boat, b i is the pinning gain. q0 is the position information of the expected trajectory, and w0 is the speed information of the expected trajectory. w j is the speed information of the j th boat. a id = b i ​+d i in , where d i in is the i in-degree of the nth ship.

[0076] Step S5: Establish a fixed-time terminal sliding surface and take its derivative to obtain an equivalent distributed terminal sliding mode control law; Step S51: Design a fixed-time terminal sliding surface S i as follows:

[0077] where , and

[0078]

[0079] where m = 1, 2, known constants a s > 0, b s > 0, r1 > 1, 1 < r2 < 2, are positive numbers. and ensure the continuity of the sliding surface S i .

[0080] Step S52: According to the sliding surface (19), the fixed-time terminal sliding mode controller can be obtained as:

[0081] where: u * i (t) = [u * i,1 (t), u * i,2 (t)] T , u * i,1 (t) represents the terminal sliding mode controller of the ith unmanned ship in the x-axis direction, and u * i,2 (t) represents the terminal sliding mode controller of the ith unmanned ship in the y-axis direction.

[0082] The parameters , α n , β n , r3, r4 are all positive constants, , . is the input saturation compensation term.

[0083] is the equivalent control part, where, ; ( m=(1, 2) has the following form:

[0084] is the fixed-time control part.

[0085]

[0086]

[0087] Among them,

[0088]

[0089] Among them: m= 1, 2, is a parameter to be designed. is a non-negative function and satisfies that when at that time .

[0090] Step S6: Construct a fixed-threshold event-triggering mechanism, design a distributed event-triggering terminal sliding mode controller by combining the idea of the sliding mode band, and realize the cooperative tracking control of the multi- underactuated unmanned surface vehicle system through the output command of the controller.

[0091] Step S61: Design a distributed event-triggering controller based on the controller u i * :

[0092] Among them: u * i,m (t i,m k ) represents the value of the m-th control input of the i-th unmanned surface vehicle at the previous triggering moment, τ ci,m represents the current output value of the m-th control input of the i-th unmanned surface vehicle at time t, where t i,m k represents the k-th event triggering moment of the m-th control input of the i-th unmanned surface vehicle, t i,m k+1 represents the (k + 1)-th event triggering moment of the m-th control input of the i-th unmanned surface vehicle, m = 1, 2.

[0093] Step S62: Design the fixed-threshold event-triggering mechanism as:

[0094] Among them, σ im is a positive constant. At the moment of t the i th unmanned surface vehicle mAn event that controls the input triggers the error function e im = u * i,m - τ ci,m , when the absolute value of e im is greater than σ im , the controller is triggered to update; otherwise, it does not update, avoiding frequent communication and saving communication resources.

[0095] Effect verification: Refer to Figure 2 As shown, consider a multi-underactuated unmanned surface vehicle system composed of five underactuated unmanned surface vehicles. The relevant parameters of the i th unmanned surface vehicle are as follows:

[0096] External disturbance: τ ei = [τ ei u , τ ei v , τ ei r T , where τ ei u = -0.15cos(0.01t)cos(0.015t), τ ei v = 0.15sin(0.21t)cos(0.2t), τ ei r = -0.15sin(0.2t)cos(0.23t);

[0097] The control input saturation constraint for each unmanned surface vehicle is: τ max = 50, τ min = -50.

[0098] Only the first vehicle can directly receive the information of the desired trajectory. The Laplacian matrix is: .

[0099] Control objective: The multi-underactuated unmanned surface vehicle system collaboratively tracks a circular trajectory q0 = [3cos(0.09t), 3cos(0.09t)] T . The initial position information, initial velocity information, and desired formation information of each unmanned surface vehicle are as follows:

[0100] Refer to Figure 3 ​As shown, it demonstrates that when the desired trajectory is circular, the multi-undersea vehicle system realizes fixed-time cooperative tracking control under the distributed event-triggered terminal sliding mode control method proposed in the present invention.

[0101] Figure 4 and Figure 5 It shows the change process of the observation error of the fixed-time disturbance observer. It can be clearly seen from the figure that the estimation error of the disturbance observer converges smoothly within the specified convergence time in both the x-axis direction and the y-axis direction and stabilizes within a small error range.

[0102] Figure 6 and Figure 7 It shows the change curve of the estimation error of the fixed-time RBF neural network observer. It can be observed from the figure that the estimation error of the fixed-time RBF neural network observer converges rapidly within the specified time in both the x-axis direction and the y-axis direction and stabilizes within a small error range.

[0103] Figure 8 and Figure 9 It shows the control input τ of the multi-undersea vehicle system u , τ r The image of the event trigger moment. It can be seen from the figure that the average event trigger interval of the system controller is significantly greater than the given simulation sampling period of 0.01 s, so there is no Zeno phenomenon in the system.

[0104] The technical solution of the present invention has the following technical effects compared with the prior art: The present invention constructs an equivalent fully actuated model of the underactuated undersea vehicle system based on the idea of upgrading and dimension reduction, laying an important foundation for subsequent simplified controller design; adopts a fixed-time terminal sliding mode surface to ensure that the cooperative tracking error of multiple undersea vehicles converges within a fixed time, designs a fixed-threshold event trigger mechanism, introduces the idea of a sliding mode band, solves the fusion problem of event-triggered control and sliding mode control, and simultaneously achieves the two indicators of "fast cooperative control" and "saving communication resources"; innovatively introduces a fixed-time adaptive RBF neural network to achieve input saturation compensation control, improving the robustness of the system to changes in the parameters of the distributed event-triggered controller while reducing the computational burden, making the cooperative control method of the designed multi-undersea vehicle system more practical.

[0105] Embodiment 2: This embodiment will describe a control system 100 and an electronic device 200 of a multi-undersea vehicle system under input saturation constraints according to Figure 10 and Figure 11

[0106] Among them, referring to Figure 10As shown in the figure, a control system 100 for a multi-undersea vehicle system under input saturation constraint is provided, including: A model conversion module 110, which is used to convert the mathematical model of the multi-undersea vehicle system into an equivalent fully actuated model; avoiding the complex non-linear expressions caused by traditional mathematical reconstruction, reducing the state space dimension, significantly simplifying the controller design complexity, and improving the calculation efficiency and control intuitiveness.

[0107] A disturbance observation module 120, which estimates the environmental disturbance through a designed fixed-time disturbance observer; traditional sliding mode control generates discontinuous control signals through a sign function to suppress the disturbance, which will cause chattering phenomenon. Traditional disturbance observers require the upper bound information of known uncertainties and disturbance derivatives, and can only guarantee asymptotic stability, and cannot complete the disturbance estimation within a fixed time. In this embodiment, a fixed-time disturbance observer is designed to achieve fast disturbance estimation, and the upper bound of the convergence time is independent of the initial state, weakening the chattering of the control input.

[0108] An input saturation estimation module 130, which uses a fixed-time adaptive RBF neural network observer to estimate the input saturation term of the multi-undersea vehicle system; most existing achievements construct an auxiliary system to achieve the compensation control of input saturation, but the corresponding methods have the defects of complex parameter tuning and large calculation burden, and it is difficult to meet the real-time requirements of multi-ship cooperation. In this embodiment, an RBF neural network is innovatively introduced to estimate and compensate the input saturation, and the network weights are adjusted online adaptively. This method does not depend on the model parameters of the undersea vehicle and has stronger generalization ability.

[0109] A controller design and execution module 140, which is used to design a fixed-time sliding mode surface and a fixed-threshold triggering mechanism to obtain a controller, and is also used to output control instructions to achieve the cooperative tracking control of the multi-undersea vehicle; a fixed-time terminal sliding mode surface is designed based on the fixed-time adaptive RBF neural network to ensure that the cooperative tracking error of the multi-undersea vehicle converges within a fixed time. A fixed-threshold event triggering mechanism is designed, and the idea of a sliding mode band is introduced to solve the fusion problem of event-triggered control and sliding mode control, that is, the two indicators of "fast cooperative control" and "saving communication resources" are achieved at the same time.

[0110] A communication module 150, which is used to communicate with external devices.

[0111] It should be understood that the control system 100 here is embodied in the form of functional modules. The term "module" here may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a proprietary processor or a group of processors, etc.) for executing one or more software or firmware programs, and a memory, a combined logic circuit and / or other suitable components that support the described functions. In an alternative example, those skilled in the art can understand that the control system 100 can specifically be the electronic device 200 in the above embodiments, or, the functions of the electronic device 200 in the above embodiments can be integrated in the control system 100, and the control system 100 can be used to execute each process and / or step corresponding to the electronic device 200 in the above method embodiments. To avoid repetition, details are not described herein again.

[0112] The above control system 100 has the function of implementing the corresponding steps executed by the electronic device 200 in Embodiment 1; the above function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. For example, the above acquisition module can be a communication interface, such as a transceiver interface.

[0113] Refer to Figure 11 As shown, in this embodiment, an electronic device 200 is provided, including: a processor 210, and a memory 220 and a transceiver 230 communicatively connected to the processor; the memory 220 stores computer-executable instructions; the transceiver 230 is used for receiving and transmitting data; the processor 210 executes the computer-executable instructions stored in the memory 220 to implement the control method in Embodiment 1.

[0114] It should be understood that the electronic device 200 can be used to execute each corresponding step and / or process in the above method embodiments. Optionally, the memory 220 may include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory 220 may also include a non-volatile random access memory. For example, the memory 220 may also store information about the device type. The processor 210 can be used to execute the instructions stored in the memory 220, and when the processor 210 executes the instructions, the processor 210 can execute each corresponding step and / or process in the above method embodiments.

[0115] It should be understood that in the embodiments of the present application, the processor 210 may be a central processing unit (CPU), and the processor 210 may also be other general-purpose processors, DSP digital signal processors 210, ASIC application-specific integrated circuits, FPGA field-programmable gate arrays, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0116] In the implementation process, each step of the above method may be completed by the integrated logic circuit of the hardware in the processor 210 or the instructions in the form of software. The steps of the method disclosed in combination with the embodiments of the present application may be directly embodied as being executed and completed by the hardware processor, or may be executed and completed by a combination of the hardware and software modules in the processor 210. The software module may be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory, and the processor executes the instructions in the memory and combines its hardware to complete the steps of the above method. To avoid repetition, it will not be described in detail here.

[0117] Embodiment 3: In this embodiment, a computer-readable storage medium is provided. Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the control method in Embodiment 1.

[0118] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, and the indirect coupling or communication connection of the device or unit may be in an electrical, mechanical, or other form.

[0119] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0120] In addition, in each embodiment of the present application, each functional unit may be integrated into one processing unit, may exist physically alone for each unit, or two or more units may be integrated into one unit.

[0121] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0122] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any one or more embodiments or examples in a suitable manner.

[0123] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A cooperative control method for a multi- underactuated unmanned surface vehicle system under input saturation constraints, characterized in that, Including the following steps: Step S1: Establish a fully actuated model of the multi-underactuated unmanned surface vehicle system; Step S2: Design a fixed-time disturbance observer for the fully actuated model to achieve fixed-time estimation of disturbances; Step S3: Design a fixed-time adaptive RBF neural network observer to estimate the input saturation term of the multi-underactuated unmanned surface vehicle system; Step S4: Establish a cooperative tracking error system according to the cooperative control objective and network topology; Step S5: Establish a fixed-time terminal sliding surface and take its derivative to obtain an equivalent distributed terminal sliding mode control law; Step S6: Construct a fixed-threshold event-triggering mechanism, design a distributed event-triggering - terminal sliding mode controller in combination with the sliding mode band idea, and achieve cooperative tracking control of the multi-underactuated unmanned surface vehicle system through the output instructions of the controller.

2. The collaborative control method according to claim 1, wherein, The said Step S1 includes the following steps: Establish a dynamic mathematical model of the three-degree-of-freedom multi-underactuated unmanned surface vehicle system under input saturation constraints; Elevate and reduce the order of the motion state parameters in the dynamic mathematical model to construct a fully actuated model of the multi-underactuated unmanned surface vehicle system; Introduce saturation input constraints into the formula of the fully actuated model.

3. The collaborative control method according to claim 2, wherein The formula of the fully actuated model is: ； Among them, is the transfer matrix, is the position information in the inertial coordinate system, is the control input information of the multi-undersea-actuated unmanned surface vehicle system without saturation constraints; is the difference caused by the saturated input; is the external disturbance information; is the non-linear term information.

4. The collaborative control method according to claim 3, wherein The difference caused by the saturated input The calculation formula is as follows: ； wherein, is the control input of the all-drive system, τ u i is the control input generated by the thruster under saturation constraints, τ r i is the control input generated by the rudder under saturation constraints; is the control input of the unmanned ship under saturation constraints, τ ci,1 is the control input generated by the thruster without saturation constraints, τ ci,2 is the control input generated by the rudder without saturation constraints, Δτ u i is the control input τ u i under saturation constraints and the control input τ ci,1 without saturation constraints, the difference, Δτ r i is the control input τ r i under saturation constraints and the control input τ ci,2 without saturation constraints; and has an input saturation constraint and satisfies the following formula: ； ； Among them, is the saturation upper limit of the system input, is the saturation lower limit of the system input.

5. The collaborative control method according to claim 1, wherein The design of the fixed-threshold event-triggering mechanism is as follows: ； Among them, represents the th event triggering moment of the th control input of the th unmanned ship; represents the th event triggering moment of the th control input of the th unmanned ship, ; at time t, the event triggering error function of the th control input of the th unmanned ship is , where is the fixed-time terminal sliding mode control law at time t, is a positive constant. When the absolute value of is greater than , the controller is triggered to update, otherwise it does not update.

6. The collaborative control method according to claim 1, wherein The formula of the fixed-time adaptive RBF neural network observer in Step S3 is as follows: ； Among them, is the estimated value of the velocity vector , is the transfer matrix, is the control input information of the multi-undersea-actuated unmanned surface vehicle system without saturation constraints; is the information of the non-linear term; is the estimated value of the disturbance information d i ; m = 1, 2; , is the positive diagonal gain matrix, which is used to adjust the convergence speed of the observer; the power , , is the estimated value of the optimal weight of the adaptive RBF neural network ; is the bounded neuron radial basis function vector, satisfying , is a positive constant.

7. The collaborative control method according to claim 6, characterized in that Estimated value The adaptive update rule for is as follows: ； where the observation error , is the velocity observation error of the i-th unmanned ship in the x-axis direction, is the velocity observation error of the i-th unmanned ship in the y-axis direction, and are positive constants, representing the learning rate and damping coefficient of weight update respectively.

8. A control system for a multi-underactuated unmanned surface vehicle system under input saturation constraints, characterized in that, To implement the cooperative control method as described in any one of claims 1-7, including: A model conversion module, which is used to convert the mathematical model of the multi-underactuated unmanned surface vehicle system into a fully actuated model; A disturbance observation module, which estimates environmental disturbances through the designed fixed-time disturbance observer; An input saturation estimation module, which estimates the input saturation term of the multi-underactuated unmanned surface vehicle system by using the fixed-time adaptive RBF neural network observer; A controller design execution module, which is used to design a fixed-time sliding surface and a fixed-threshold event-triggering mechanism to obtain a controller, and is also used to output control instructions to achieve cooperative tracking control of the multi-underactuated unmanned surface vehicle; A communication module, which is used to communicate with external devices.

9. An electronic device, characterized in that, Including: A processor, and a memory and a transceiver communicatively connected to the processor; The memory stores computer execution instructions; the transceiver is used for sending and receiving data; The processor executes the computer execution instructions stored in the memory to implement the cooperative control method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the cooperative control method as described in any one of claims 1-7.

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