Distributed IESO-PD time delay control method for multi-underactuated unmanned ship system

Abstract

The invention belongs to the technical field of unmanned ship control, and particularly discloses a distributed IESO-PD time delay control method of a multi-underactuated unmanned ship system. The distributed IESO-PD time delay control method of the multi-underactuated unmanned ship system comprises the following steps: S1, establishing an all-drive model of the multi-underactuated unmanned ship system; s2, determining a cooperative control target and a network topology structure of the system; s3, designing a low-pass filtering improved extended state observer; s4, constructing a collaborative formation tracking error system; s5, a distributed PD time delay controller is designed, and control parameters of the distributed PD time delay controller are solved based on the distribution theorem of quasi-polynomial roots and pole assignment; cooperative formation tracking control of the system is realized through an output instruction of the distributed PD time delay controller. According to the invention, the problem of comprehensive control of an under-actuated unmanned ship system under severe sea conditions is solved; the related detection information is only the position information of the under-actuated unmanned ship system; and the expected performance index requirements can be met by optimally configuring the control parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned ship control, and particularly relates to a distributed IESO-PD time-delay control method for a multi- underactuated unmanned ship system. Background Art

[0002] With the development of marine resource exploitation and intelligent shipping, the cooperative control research of multi- underactuated (the number of independent control inputs is less than the number of degrees of freedom) unmanned ship systems has extensive application value in the fields of marine exploration, search and rescue, resource exploitation, cargo transportation, cooperative operations, etc.

[0003] However, in complex and harsh marine environments (such as wind, wave and current disturbances, sensor measurement noise, communication time-delay, etc.), for non-linear underactuated unmanned ship systems, how to design appropriate control schemes has always been a huge challenge. In particular, there is less research on cooperative control with communication time-delay, and there are the following problems: Existing control schemes often focus on time-delay analysis, that is, when the time-delay size meets what kind of constraints, the designed control scheme is effective, and the time-delay control problem is not actually solved; existing non-linear time-delay control schemes are extremely complex, not only with very poor practicality, but also with poor control effects; existing results do not further consider the influence of other complex sea conditions on the design of non-linear time-delay control schemes, such as wind, wave and current disturbances and sensor measurement noise, etc., and the relevant research results are still blank; existing control schemes usually require the system to be able to directly detect a lot of information for control services, such as in addition to the pose information of the unmanned ship system, its speed and even acceleration information are also required to be directly detected, which will significantly increase the detection cost and is not practical.

[0004] In summary, there is a need for a distributed IESO-PD time-delay control method for a multi- underactuated unmanned ship system to solve the above problems in the prior art. Summary of the Invention

[0005] The present invention provides a distributed IESO-PD (IESO - improved extended state observer, P - proportional, D - derivative) time-delay control method for a multi- underactuated unmanned ship system, which solves the communication time-delay control problem of the multi- underactuated unmanned ship system.

[0006] To achieve the purpose of solving the above technical problems, the present invention adopts the following technical solutions: A distributed IESO-PD time-delay control method for a multi- underactuated unmanned ship system includes the following steps: Step S1, establish a fully actuated model of the multi- underactuated unmanned ship system; Step S2, determine the cooperative control objective and network topology structure of the multi- underactuated unmanned ship system; Step S3: Design an extended state observer with improved low-pass filtering to achieve filtering of measurement noise and suppression of disturbances; Step S4: Construct a cooperative formation tracking error system; Step S5: Design a distributed PD time-delay controller based on the estimated values output by the extended state observer in Step S3 and the tracking error in Step S4, and solve the control parameters of the distributed PD time-delay controller based on the distribution theorem of quasi-polynomial roots and pole placement; Implement cooperative formation tracking control of the multi-undersea vehicle system through the output commands of the distributed PD time-delay controller.

[0007] In some embodiments of the present invention, Step S1 includes the following steps: Establish the kinematic model and dynamic model of a three-degree-of-freedom multi-undersea vehicle system under external disturbances; Elevate and reduce the dimension of the motion state parameters in the kinematic model to realize the conversion of the kinematic model and dynamic model to obtain a fully actuated model.

[0008] In some embodiments of the present invention, the formula of the fully actuated model is: ; where, p k (t) = [x k (t), y k (t)] T is the position vector, B k is the state transition matrix, τ k (t) = [τ u k (t), τ r k (t)] T is the control input vector, f k (t) = [f x k (t), f y k (t)] T is a known continuous vector function, d k (t) = [f xdis k (t), f ydis k (t)] T is an unknown continuous vector function, k = 1, 2, …, N is the k th undersea vehicle in the multi-undersea vehicle system.

[0009] In some embodiments of the present invention, the equation of the improved extended state observer in step S3 is as follows: ; Where: 、 、 are the estimated values of the position information p k (t), the velocity information q k (t), and the disturbance information d k (t); is the virtual control input; y 1k (t) is the state of the low-pass filter; τ f is the time constant of the low-pass filter; y 0k (t) is the position information detected by the unmanned ship; is the output information of the improved extended state observer; β = [β1, β2, β3] T is the control parameter of the improved extended state observer.

[0010] In some embodiments of the present invention, the cooperative tracking error in step S4 is:

[0011]

[0012] Where: e 1k (t) is the position error of the k th unmanned ship at t time, e 2k (t) is the velocity error of the k th unmanned ship at t time, α kj is the element in the k th row and j th column of the graph adjacency matrix, τ is the communication delay, p k (t - τ) and q k (t - τ) are the actual position and velocity information detected by the k th unmanned ship at t time, p j (t - τ) and q j (t - τ) are the actual position and velocity information detected by the j th unmanned ship at t time, p0(t - τ) and q0(t - τ) are the actual position and velocity information of the expected trajectory received at t time, Δ k and Δ j are the k th unmanned ship and the jThe desired formation information of the bth unmanned ship k is the sth k unmanned ship's pinning gain.

[0013] In some embodiments of the present invention, the control protocol of the distributed PD time-delay controller in the step S5 is:

[0014]

[0015] where k p is the proportional control parameter of the distributed PD time-delay controller, k d is the differential control parameter of the distributed PD time-delay controller, and are respectively the time-delay observation position and time-delay observation speed information of the sth k unmanned ship at t time, and are respectively the time-delay observation position and time-delay observation speed information of the sth j unmanned ship at t time; p0(t-τ) and q0(t-τ) are respectively the actual position and speed information of the desired trajectory received at t time, Δ k and Δ j are respectively the desired formation information of the sth k unmanned ship and the sth j unmanned ship, α kj is the element of the sth k row and the sth j column of the graph adjacency matrix, τ is the communication time-delay; b k is the pinning gain.

[0016] In some embodiments of the present invention, the calculation process of the proportional control parameter k p of the distributed PD time-delay controller and the differential control parameter k d of the distributed PD time-delay controller is as follows: Using the fully actuated model of the multi- underactuated unmanned ship system, the improved extended state observer and the distributed PD time-delay controller, construct the dynamic equation of the overall closed-loop error system; Analyze the characteristic polynomial of the error state based on the frequency domain method; Separate the error state vector into the IESO disturbance compensation error and the PD time-delay control error; Transform the characteristic function corresponding to the PD time-delay control error to obtain the corresponding quasi-polynomial form, and solve the proportional control parameter k p and the differential control parameter k d based on the necessary and sufficient conditions for the distribution of the roots of the quasi-polynomial and the pole placement method.

[0017] In some embodiments of the present invention, a distributed IESO-PD time-delay control system for a multi- underactuated unmanned surface vehicle system is provided to implement the above-mentioned distributed IESO-PD time-delay control method, 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 filtering and suppression module, which is used to implement the filtering of measurement noise and the suppression of disturbances by designing an extended state observer improved by low-pass filtering; A controller design and execution module, which is used to design a distributed PD time-delay controller; is also used to calculate the control parameters of the distributed PD time-delay controller; is also used to output control instructions to achieve cooperative formation tracking control of the multi- underactuated unmanned surface vehicle; A communication module, which is used to communicate with external devices.

[0018] 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 above-mentioned distributed IESO-PD time-delay control method.

[0019] 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 above-mentioned distributed IESO-PD time-delay control method.

[0020] The technical solution of the present invention has the following technical effects compared with the prior art: The present invention uses an improved extended state observer and a distributed PD time-delay controller to solve the comprehensive control problem of the underactuated unmanned surface vehicle system in the presence of wind, wave and current disturbances, measurement noise and communication delay at the same time; the detection information involved in the present invention is only the position information of the unmanned surface vehicle system, and there is no detection requirement for its speed, acceleration and other information; in addition, the control method of the present invention has strong practicability, and can meet the requirements of the desired performance index by optimizing the configuration of control parameters. Description of the Drawings

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0022] Figure 1 It is a flowchart of the control method involved in the present invention.

[0023] Figure 2 It is the network topology structure of the multi-undersactuated unmanned surface vehicle system involved in the present invention.

[0024] Figure 3 It is the cooperative tracking roadmap of the multi-undersactuated unmanned surface vehicle system involved in the present invention when the desired trajectory is circular.

[0025] Figure 4 It is the estimated error of the disturbance in the x-axis direction of the multi-undersactuated unmanned surface vehicle system involved in the present invention when the desired trajectory is circular.

[0026] Figure 5 It is the estimated error of the disturbance in the y-axis direction of the multi-undersactuated unmanned surface vehicle system involved in the present invention when the desired trajectory is circular.

[0027] Figure 6 It is the estimated error of the position in the x-axis direction of the multi-undersactuated unmanned surface vehicle system involved in the present invention when the desired trajectory is circular.

[0028] Figure 7 It is the estimated error of the position in the y-axis direction of the multi-undersactuated unmanned surface vehicle system involved in the present invention when the desired trajectory is circular.

[0029] Figure 8 It is a schematic structural diagram of the control system.

[0030] Figure 9 It is a schematic structural diagram of the electronic device.

[0031] Reference numerals: 100, control system; 110, model conversion module; 120, filtering and suppression module; 130, controller design and execution module; 140, communication module; 200, electronic device; 210, processor; 220, memory; 230, transceiver. Detailed implementation manners

[0032] 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. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0033] In the description of the present invention, it should be noted that unless otherwise clearly specified 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.

[0034] Embodiment 1: Refer to Figure 1 As shown, this embodiment provides a distributed IESO-PD time-delay control method for a multi-underactuated unmanned ship system, including the following steps: Step S1, establish a fully actuated model of the multi-underactuated unmanned ship system; Step S11, the multi-underactuated unmanned ship system involved in this embodiment consists of N identical three-degree-of-freedom underactuated unmanned ships. Among them, the k th ( k = 1,..., N ) underactuated unmanned ship's mathematical model is (for convenience, the explicit expression of some variables with respect to time t will be omitted later; in this embodiment, the formulas are labeled in the format of #(number)):

[0035] where η k = [x k , y k , ψ k T is the pose state variable of the system, and ν k = [u k , v k , r k T is the speed state variable of the system; specifically, x k , y k , ψ k respectively represent the surge displacement, sway displacement, and yaw angle in the earth coordinate system, and u k , v k , r k ​​respectively represent the surge velocity, sway velocity, and yaw angular velocity in the inertial coordinate system; τ k =[τ u k , 0, τ r k T represents the control input; τ k dis =[τ k udis , τ k vdis , τ k rdis T represents the external environmental disturbance. The state transition matrix J(ψ k ), the inertia matrix M k , the Coriolis and centripetal force matrix C k (ν k ), and the damping matrix D k are respectively as follows:

[0036] .

[0037] where d 11 , d 22 , d 23 , d 32 , d 33 represent hydrodynamic damping, m 11 , m 22 , m 23 , m 32 , m 33 represent inertia and added mass, and are all positive; and there exists m 23 =m 32 , c k 13 =m 32 r k -m 22 v k , c k 23 =m 11 u k .

[0038] Step S12: Based on the idea of upgrading and dimension reduction, the first-order underactuated unmanned surface vehicle dynamic model is differentiated. After a series of variable substitutions and arrangements, it is transformed into a second-order fully actuated form, specifically as follows: According to formula (1), we can obtain:

[0039] According to the dynamic equation in formula (1) and m in the actual system​​23 m 32 -m 22 m 33 From the fact that m >> 0, we can obtain:

[0040] Where:

[0041] According to formulas (2) and (3), we can get:

[0042] Where: .

[0043] Define the position state of the nth underactuated unmanned ship k at time t in the inertial coordinate system as p t (t) = [x k (t), y k (t)] k (t)] T . Then the converted fully actuated model is obtained:

[0044] Where τ k (t) = [τ u k (t), τ r k (t)] T is the control input vector, f k (t) = [f x k (t), f y k (t)] T is a known continuous vector function, d k (t) = [f xdis k (t), f ydis k (t)] T is an unknown continuous vector function, and the state transition matrix of the system is

[0045] Obviously, we have: detB k ≠ 0, detB k ≠ ∞, that is, formula (5) represents a second-order fully actuated mathematical model.

[0046] In step S1, based on the idea of ascending order and dimensionality reduction, through a series of variable substitutions, the first-order underactuated unmanned surface vehicle dynamic model is transformed into a second-order fully actuated form, laying a foundation for subsequent transformation of non-linear control into linear control.

[0047] Step S2: Determine the cooperative control objective and network topology of the multi-underactuated unmanned surface vehicle system; Step S21: Determine the cooperative control objective of the multi-underactuated unmanned surface vehicle system: Define p k (t)=[x k (t),y k (t)] T as the position information of the k th unmanned surface vehicle at t time, as the velocity information of the k th unmanned surface vehicle at t time. Given the desired formation position information as Δ=[Δ1 T ,Δ2 T ,…,Δ N T T , the desired tracking trajectory position information is q0(t)=[x0(t),y0(t)] T , and the desired tracking trajectory velocity information is .

[0048] For the k th unmanned surface vehicle, in any initial state, there is

[0049] Step S22: Determine the network topology of the multi-underactuated unmanned surface vehicle system; Refer to Figure 2 as shown. The interaction communication topology formed by N underactuated unmanned surface vehicles contains at least one directed spanning tree, and the root node can directly obtain the desired trajectory information.

[0050] Step S3: Design an extended state observer improved by low-pass filtering to filter measurement noise and suppress disturbances; Step S31: According to the measurement noise problem existing in reality, the fully actuated model formula (5) can be rewritten as:

[0051] where y 0k (t) is the actual output position information of the unmanned surface vehicle system, ω k (t) is the measurement noise, is the virtual control input.​

[0052] Step S32: Design an improved extended state observer (IESO) with a low-pass filter. For the k th unmanned ship, design an improved extended state observer based on the low-pass filter as follows:

[0053] where 、 、 are the estimated values of the position information p k (t), the velocity information q k (t), and the disturbance information d k (t) respectively; y 1k (t) is the state of the low-pass filter; τ f is the time constant of the low-pass filter; y 0k (t) is the position information detected by the unmanned ship, is the output information of the IESO, and β = [β1, β2, β3] T are the control parameters of the IESO; Step S33: To verify the stability of the output of the IESO, based on Formulas (6) and (7), obtain the IESO error dynamics equation as:

[0054] where: is the error state vector of System (7), and , , are the differences between the estimated position and the true position, the estimated velocity and the true velocity, and the estimated total disturbance and the true total disturbance of the IESO respectively.

[0055] is the external disturbance vector of System (8), is a 2×2 matrix with all matrix elements being 0, h k (t) is the derivative of d k (t) and satisfies that for , is an unknown bounded positive number.

[0056] A 0k is the state transition matrix and is a Hurwitz matrix:

[0057] where I is the second-order identity matrix. The measurement noise filtering and complex disturbance suppression are achieved through the IESO.

[0058] In step S3, an improved extended state observer based on low-pass filtering is proposed. While filtering the measurement noise, the non-linear disturbance is regarded as the system state to be estimated and estimated by the designed extended state observer, finally realizing the filtering of the measurement noise and the suppression of the complex disturbance. Compared with the existing disturbance compensation control schemes, the design of IESO only requires directly detecting the position information of the unmanned ship, which will greatly reduce the measurement cost and be more practical.

[0059] Step S4: Construct a cooperative formation tracking error system; Based on the desired formation information and the tracking signal, construct a cooperative formation tracking error system: According to the cooperative control objective, the cooperative tracking error is obtained as:

[0060]

[0061] where: e 1k (t) is the position error of the k th unmanned ship t at time t, e 2k (t) is the velocity error of the k th unmanned ship t at time t, α kj is the element of the k th row and j th column of the graph adjacency matrix, τ is the communication delay, p k (t - τ) and q k (t - τ) are the actual position and velocity information detected by the k th unmanned ship at t time t respectively, p j (t - τ) and q j (t - τ) are the actual position and velocity information detected by the j th unmanned ship at t time t respectively, p0(t - τ) and q0(t - τ) are the actual position and velocity information of the expected trajectory received at t time t respectively, Δ k and Δ j are the desired formation information of the k th unmanned ship and the j th unmanned ship respectively, b k is the pinning gain of the k th unmanned ship.

[0062] Step S5: Design a distributed PD delay controller according to the estimated value output by the extended state observer in step S3 and the tracking error in step S4, and solve the control parameters of the distributed PD delay controller based on the distribution theorem of quasi-polynomial roots and pole placement; The cooperative formation tracking control of a multi-underactuated unmanned surface vehicle (USV) system is realized through the output instructions of a distributed PD time-delay controller.

[0063] Step S51: Design a distributed PD time-delay controller: Define the error system state variables:

[0064] For the k th USV, according to Formulas (7)-(10), design a distributed PD time-delay control protocol as follows:

[0065] where, is the proportional control parameter of the distributed PD time-delay controller, k d is the differential control parameter of the distributed PD time-delay controller, and are respectively the time-delay observed position and time-delay observed velocity information of the k th USV at t time, and are respectively the time-delay observed position and time-delay observed velocity information of the j th USV at t time.

[0066] Specifically, all the input information used by the distributed PD time-delay controller is obtained by IESO estimation. Based on Formulas (7) and (11), it can be known that the design only needs to detect the position information of the USV, which will greatly reduce the detection cost and reduce the introduction of measurement error information.

[0067] Step S52: Calculate the proportional control parameter k p of the distributed PD time-delay controller and the differential control parameter k d of the distributed PD time-delay controller.

[0068] S521: Utilize the fully actuated model of the multi-underactuated USV system, the improved extended state observer, and the distributed PD time-delay controller to construct the dynamic equation of the overall closed-loop error system:

[0069] where, is the error state vector of the overall closed-loop error system, and is the position error state vector, is the velocity error state vector, is the IESO error state vector; is the time-delay error state vector; is the external disturbance input of the overall closed-loop error system; A F , B F , D F are coefficient matrices.

[0070] S522. Analyze the characteristic polynomial of the error state based on the frequency-domain method; Since is a bounded disturbance input, the stability control problem of the overall closed-loop error system can be transformed into the stability control problem of the time-delay system, and the time-delay system satisfies the following formula:

[0071] Based on the frequency-domain method, perform Laplace transform on Equation (13) to obtain:

[0072] where s is the complex frequency-domain variable, e -τs represents the time-delay link. When the characteristic polynomial matrix A F +B F e -τs is Hurwitz stable, the time-delay system is stable.

[0073] S523. Separate the error state vector into the IESO disturbance compensation error and the PD time-delay control error;

[0074] where the matrices E 11 , E 12 , E 22 are not zero matrices, and is only determined by the IESO, and E 11 is only determined by the distributed PD time-delay controller. Due to the special upper diagonal matrix structure of A F +B F e -τs , the system (13) is stable if and only if the matrices E 11 、 E 22 simultaneously satisfy the Hurwitz stability condition. Therefore, the design of the PD time-delay controller and the design of the IESO are separable.

[0075] To facilitate the verification of the stability effect of the PD control time-delay error, is split into two parts, namely and e0(t), where is only related to the design of the PD time-delay controller, and e0(t) is only related to the design of the IESO. Based on the Laplace transform, we can obtain The corresponding characteristic function δ(s) is as follows:

[0076] where μ k is the eigenvalue of the matrix L + B, L is the graph Laplacian matrix, B is a pure diagonal matrix composed of b k .

[0077] S524. Transform the characteristic function corresponding to the PD time-delay control error to obtain the corresponding quasi-polynomial form, and solve the proportional control parameter k p and the differential control parameter k d based on the necessary and sufficient conditions for the distribution of the roots of the quasi-polynomial and the pole-placement method.

[0078] Based on the requirements of the expected performance index, determine the critical position of the pole-placement s = -σ, where σ is a positive number, to ensure that all poles of formula (15) are on the left side of s = -σ.

[0079] Transform formula (15) to obtain the corresponding quasi-polynomial form, and solve the range of k p , k d as follows: Step 1. Eliminate e -τs , that is, δ(s) Í e τs .

[0080] Step 2. Scale and translate the variable s to obtain a new variable λ = s / τ - σ.

[0081] Step 3. Name the quasi-polynomial form obtained in Step 2 as H k (λ). Substitute λ = iz to obtain the real part H r (z) and the imaginary part H i (z), where represents the imaginary unit, satisfying i 2 = -1, and z is a complex variable.

[0082] Step 4. Variable substitution , where is the conjugate of . Obtain the range of k d according to the necessary condition for the distribution of the roots of the quasi-polynomial.

[0083] Step 5. Variable substitution , and obtain the range of k p according to the necessary condition for the distribution of the roots of the quasi-polynomial.

[0084] Step 6. Use the iterative algorithm to obtain the value of k p, k d The effective region of parameters within the necessary and sufficient conditions for the root distribution of the quasi-polynomial satisfied within the range.

[0085] According to the above calculation method, the PD controller parameters can be directly calculated by the pole placement method according to the time delay size, without repeated debugging. In addition, the configured control parameters k p and k d can meet the requirements of the desired performance indicators and achieve the optimal control effect.

[0086] Effect verification: Refer to Figure 2 As shown, consider a multi- underactuated unmanned surface vehicle system composed of five isomorphic underactuated unmanned surface vehicles. The relevant parameters of the k th unmanned surface vehicle are as follows: ,

[0087] External disturbance: , where , , ; Noise: ω k (t) uses white noise with a power of 0.0000002 and a sampling time of 0.001 s, and the noise amplitude is limited to [0.05, 0.05].

[0088] Communication time delay: τ = 0.06 s.

[0089] The communication topology diagram is as Figure 2 shown.

[0090] Only the No. 1 ship can directly receive the information of the desired trajectory. The Laplacian matrix is:

[0091] Control objective: The multi- underactuated unmanned surface vehicle system collaboratively tracks a circular trajectory according to the following formation information. The trajectory has a center at (0, 0), an angular velocity of 0.2 rad / s, and a radius of 50 m. The initial positions, velocities, and formation information of each unmanned surface vehicle are as follows:

[0092]

[0093]

[0094] Controller parameter settings: The parameters of the improved extended state observer are β = [90, 2700, 81000] T , and the time constant τ of the low-pass filter f = 0.01. b1 = 1, b2 = b3 = b4 = b5 = 0. The pole configuration position σ = 0.2. The proportional control parameter k p = 6, and the derivative control parameter k d = 6. The simulation duration is set to 50 s, and the sampling period is set to 0.01 s.

[0095] Refer to Figure 3 As shown, it shows the process of cooperative tracking of a multi- underactuated unmanned surface vehicle system according to the set formation when the desired trajectory is circular. The arrows represent the movement directions during the cooperative tracking process. This figure intuitively reflects through the simulation results that multiple unmanned surface vehicles start from the initial state, gradually adjust their positions, and finally achieve cooperative tracking of the desired trajectory.

[0096] Figure 4 and Figure 5 show the change process of the disturbance observation error of the improved extended state observer. It can be clearly seen from the figure that the estimation error converges smoothly within 5 s in both the x-axis direction and the y-axis direction.

[0097] Figure 6 and Figure 7 show the change process of the position observation error of the improved extended state observer. It can be clearly seen from the figure that the estimation error converges smoothly within 5 s in both the x-axis direction and the y-axis direction.

[0098] The technical solution of the present invention has the following technical effects compared with the prior art: The present invention uses an improved extended state observer and a distributed PD time-delay controller to solve the comprehensive control problem of an underactuated unmanned surface vehicle system in the presence of wind, wave and current disturbances, measurement noise, and communication time delay at the same time; the detection information involved in the present invention is only the position information of the unmanned surface vehicle system, and there is no detection requirement for its speed, acceleration and other information; in addition, the control method of the present invention has strong practicability and can meet the requirements of the desired performance index by optimizing the configuration of control parameters.

[0099] Embodiment 2: This embodiment will describe a distributed IESO-PD time-delay control system 100 and an electronic device 200 of a multi- underactuated unmanned surface vehicle system according to Figure 8 and Figure 9 .

[0100] Among them, refer to Figure 8 As shown, a distributed IESO-PD time-delay control system 100 of a multi- underactuated unmanned surface vehicle system is provided, including: The model conversion module 110 is used to convert the mathematical model of the multi-underactuated unmanned ship system into a fully actuated model; based on the idea of order elevation and dimension reduction, through a series of variable substitutions, the first-order underactuated unmanned ship dynamic model is transformed into a second-order fully actuated form, laying a foundation for the subsequent conversion of non-linear control into linear control.

[0101] The filtering and suppression module 120 is used to filter measurement noise and suppress disturbances by designing an extended state observer improved by low-pass filtering; that is, while filtering measurement noise, the non-linear disturbance is regarded as the system state to be estimated and estimated by the designed extended state observer, and finally the filtering of measurement noise and the suppression of complex disturbances are realized.

[0102] The controller design and execution module 130 is used to design a distributed PD time-delay controller; it is also used to calculate the control parameters of the distributed PD time-delay controller; it is also used to output control instructions to realize the cooperative formation tracking control of the multi-underactuated unmanned ship; the PD controller parameters can be directly calculated by the pole placement method according to the time-delay size without repeated debugging, and the configured control parameters and can meet the requirements of the expected performance indicators and achieve the optimal control effect.

[0103] The communication module 140 is used for communication with external devices.

[0104] It should be understood that the control system 100 here is embodied in the form of functional modules. The term "module" here can 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 embodiment, or, the functions of the electronic device 200 in the above embodiment can be integrated in the control system 100, and the control system 100 can be used to execute the respective processes and / or steps corresponding to the electronic device 200 in the above method embodiment. To avoid repetition, it will not be described in detail here.

[0105] The above control system 100 has the function of implementing the corresponding steps executed by the electronic device 200 in the control method in Embodiment 1; the above functions 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.

[0106] Refer to Figure 9As 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.

[0107] It should be understood that the electronic device 200 can be used to execute the corresponding respective steps and / or processes 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 further include a non-volatile random access memory. For example, the memory 220 may also store information about the device type. The processor 210 may be used to execute the instructions stored in the memory 220, and when the processor 210 executes the instructions, the processor 210 may execute the corresponding respective steps and / or processes in the above method embodiments.

[0108] 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, 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.

[0109] In the implementation process, the respective steps of the above method may be completed by the integrated logic circuit in the hardware of the processor 210 or the instructions in software form. 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 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 a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a 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.

[0110] 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.

[0111] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can 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 can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0112] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0113] In addition, the functional units in each embodiment of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0114] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this 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 to enable a computer device (which can 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 this 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.

[0115] 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.

[0116] The above is only the specific implementation manner 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 distributed IESO-PD time-delay control method for a multi-undersea-driven unmanned ship system, characterized in that, It includes the following steps: Step S1: Establish the full - drive model of the multi - under - actuated unmanned surface vehicle (USV) system; Step S2: Determine the cooperative control objective and network topology structure of the multi - under - actuated USV system; Step S3: Design an extended state observer improved by low - pass filtering to achieve the filtering of measurement noise and the suppression of disturbances; Step S4: Construct a cooperative formation tracking error system; Step S5: Design a distributed PD time - delay controller based on the estimated value output by the extended state observer in Step S3 and the tracking error in Step S4, and solve the control parameters of the distributed PD time - delay controller based on the distribution theorem of quasi - polynomial roots and pole placement; Achieve the cooperative formation tracking control of the multi - under - actuated USV system through the output command of the distributed PD time - delay controller.

2. The distributed IESO-PD delay control method according to claim 1, wherein The said Step S1 includes the following steps: Establish the kinematic model and dynamic model of the three - degree - of - freedom multi - under - actuated USV system under external disturbances; Elevate the order and reduce the dimension of the motion state parameters in the kinematic model to realize the conversion between the kinematic model and the dynamic model to obtain the full - drive model.

3. The distributed IESO-PD delay control method according to claim 2, wherein The formula of the said full - drive model is: ； wherein, is the position vector, is the state transition matrix, is the control input vector, is a known continuous vector function, is an unknown continuous vector function, and k = 1, 2, …, N represents the k-th unmanned surface vehicle in the multi- underactuated unmanned surface vehicle system.

4. The distributed IESO-PD delay control method according to claim 1, characterized in that The equation of the improved extended state observer in Step S3 is as follows: ； wherein and are the estimated values of the position information and disturbance information respectively; is the virtual control input; is the state of the low-pass filter; is the time constant of the low-pass filter; is the position information detected by the unmanned ship; is the output information of the improved extended state observer; is the control parameter of the improved extended state observer.

5. The distributed IESO-PD delay control method according to claim 1, wherein The cooperative tracking error in Step S4 is: ； ； where is the position error of the k-th unmanned ship at time t, is the velocity error of the k-th unmanned ship at time t, is the element of the j-th column in the k-th row of the graph adjacency matrix, is the communication delay, and are the actual position and velocity information detected by the k-th unmanned ship at time t, and are the actual position and velocity information detected by the j-th unmanned ship at time t, and are the actual position and velocity information of the expected trajectory received at time t, and are the expected formation information of the k-th unmanned ship and the j-th unmanned ship, is the pinning gain of the k-th unmanned ship.

6. The distributed IESO-PD delay control method according to claim 1, wherein The control protocol of the distributed PD delay controller in the step S5 is as follows: ； ； Among them, is the proportional control parameter of the distributed PD time-delay controller, is the differential control parameter of the distributed PD time-delay controller, and are the time-delay observation position and time-delay observation speed information of the k-th unmanned ship at time t, respectively, and are the time-delay observation position and time-delay observation speed information of the j-th unmanned ship at time t, respectively; and are the actual position and speed information of the expected trajectory received at time t, respectively, and are the expected formation information of the k-th unmanned ship and the j-th unmanned ship, respectively, is the element in the k-th row and j-th column of the graph adjacency matrix, is the communication time delay; is the pinning gain, is the estimated value of the disturbance information.

7. According to the distributed IESO - PD time - delay control method described in Claim 1, characterized in that The proportional control parameter of the distributed PD delay controller and the differential control parameter of the distributed PD delay controller are calculated as follows: Utilize the full - drive model of the multi - under - actuated USV system, the improved extended state observer and the distributed PD time - delay controller to construct the dynamic equation of the overall closed - loop error system; Analyze the characteristic polynomial of the error state based on the frequency - domain method; Separate the error state vector into the IESO disturbance compensation error and the PD time - delay control error; Transform the characteristic polynomial corresponding to the PD delay control error to obtain the corresponding quasi-polynomial form, and solve the proportional control parameter based on the necessary and sufficient conditions for the root distribution of the quasi-polynomial and the pole placement method and the differential control parameter .

8. A distributed IESO-PD time-delay control system for a multi-underdriven unmanned ship system, characterized in that, To implement the distributed IESO - PD time - delay control method described in any one of Claims 1 - 7, including: A model conversion module, which is used to convert the mathematical model of the multi - under - actuated USV system into a full - drive model; A filtering and suppression module, which realizes the filtering of measurement noise and the suppression of disturbances by designing an extended state observer improved by low - pass filtering; A controller design and execution module, which is used to design a distributed PD time - delay controller; is also used to calculate the control parameters of the distributed PD time - delay controller; is also used to output control commands to achieve the cooperative formation tracking control of the multi - under - actuated USV; A communication module, which is used to communicate with external devices.

9. An electronic device, characterized in that, It includes: A processor, and a memory and a transceiver communicatively connected to the processor; The memory stores computer - executable instructions; the transceiver is used to send and receive data; The processor executes the computer - executable instructions stored in the memory to implement the distributed IESO - PD time - delay control method described in any one of Claims 1 - 7.

10. A computer - readable storage medium, 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 distributed IESO - PD time - delay control method described in any one of Claims 1 - 7.

Images