An event-triggered output control method for unmanned ocean vessels based on fuzzy model

Abstract

The present invention discloses an unmanned ocean ship event trigger output control method based on a fuzzy model, including: establishing an unmanned ocean ship system T-S fuzzy model and its system model parameters; designing a periodic dynamic event trigger controller that meets the state stability and dissipation performance of the unmanned ocean ship system, and obtaining an unmanned ocean ship closed-loop system according to the designed controller; using matrix inequality and other technologies to establish a method for solving the controller gain; and using the designed controller and the obtained controller gain to safely control the unmanned ocean ship system. The present invention establishes a safety control method for ensuring the unmanned ocean ship system, which can effectively resist the adverse effects brought by external disturbances and provide key technical support for the safe and stable operation of the unmanned ocean ship system.

Description

Technical Field

[0001] The present invention relates to the field of unmanned ocean ship state control, and in particular to an unmanned ocean ship event triggering output control method based on a fuzzy model. Background Art

[0002] Unmanned ocean vessels are an important technical means for people to explore and utilize the ocean, and are widely used in military and civilian fields. In the actual execution of tasks, the existence of unknown external disturbances may cause the state of unmanned ocean vessels to fluctuate, thereby causing instability in its trajectory, and ultimately leading to deviations in control effects or even mission failure. Therefore, it is necessary to achieve safe control of unmanned ocean vessels under external interference, which is of great significance for the stable operation of unmanned ocean vessels and ensuring the quality of mission completion.

[0003] The dynamic system of unmanned ocean vessels is highly nonlinear and complex, and it is difficult to obtain an accurate model that can be used for control. Fuzzy logic is needed to approximate the model of unmanned ocean vessels. In addition, unmanned ocean vessels are limited in communication and computing capabilities, and designing controllers based on event trigger mechanisms can reduce communication rates, save computing resources, and improve control efficiency.

[0004] Therefore, the application of event-triggered control technology to unmanned marine ship systems based on fuzzy models is of great significance for their stable mission execution.

[0005] In the process of implementing the present invention, the inventors found that there are at least the following problems in the existing related technologies:

[0006] The existing technology mainly realizes control through the nonlinear model of unmanned marine ships, and rarely uses the control method based on TS fuzzy linear model; in addition, the existing safety control technology for unmanned marine ship systems usually calculates the controller output based on the state value, which requires the whole state information of the system, and there are few technical methods to calculate the controller output based on the output signal of the system;

[0007] The existence of external unknown disturbances will have a huge impact on the control of unmanned marine ship systems. The analysis of dissipative performance can evaluate the stability of the system under external disturbances. However, most of the current results only consider H, which is more special than dissipative performance. ∞ Indicators such as performance have certain limitations;

[0008] Existing event-triggered control technologies applied to unmanned marine ship systems usually do not have the characteristics of periodic triggering. The lack of a lower bound on the minimum event triggering interval leads to the Zeno phenomenon in the control process. In addition, existing technologies rarely use dynamic event triggering, which further consumes network communication resources. Summary of the invention

[0009] The purpose of the embodiment of the present application is to provide a method for safety control of an unmanned ocean vessel based on a fuzzy model, so as to solve the problem of unstable state of the unmanned ocean vessel system under external disturbance existing in the related art.

[0010] The present invention provides an unmanned ocean ship event trigger output control method based on a fuzzy model, comprising the following steps:

[0011] 1) According to the motion state of the unmanned marine ship system, the TS fuzzy model of the unmanned marine ship system is established;

[0012] 2) Design a periodic dynamic event trigger controller based on the output signal of the unmanned marine ship system;

[0013] 3) Combining the TS fuzzy model of the unmanned ocean ship system with a periodic dynamic event trigger controller to obtain an unmanned ocean ship closed-loop control system;

[0014] 4) analyzing the state stability and dissipation performance of the unmanned marine vessel closed-loop control system, thereby solving the gain of the periodic dynamic event triggering controller;

[0015] 5) Based on the gain of the periodic dynamic event trigger controller in step 4), the periodic dynamic event trigger controller is used to perform safety control on the unmanned marine vessel system.

[0016] As a preferred embodiment of the present invention, the unmanned marine vessel closed-loop control system is:

[0017]

[0018] Among them, h i (σ(t)) is the normalized fuzzy weighting function, y(t) is the output signal, C is the observation matrix, x(t) is the state of the unmanned marine ship system, z(t) is the target output, D is the output matrix, τ 1 (t) and τ 2 (t) is the premise variable, and d(t) represents the fluctuation caused by the wave.

[0019] As a preferred solution of the present invention, the step 4) is specifically as follows: in the Matlab environment, the specific parameters of the unmanned ocean ship inertia matrix, damping matrix, mooring force matrix and thruster configuration matrix are respectively set, and the initial state of the unmanned ocean ship system is set; based on the system parameters, the linear matrix inequality is solved to obtain the gain of the periodic dynamic event trigger controller.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] The present invention adopts the TS fuzzy linear model to model the unmanned marine ship system and controls it based on the output signal, which solves the limitation of the prior art that the control signal is calculated only according to the system state of the nonlinear model, and expands the practical value of the relevant technology in actual scenarios;

[0022] The present invention considers the dissipation performance index in the control process, which overcomes the problem that most of the prior art only considers H ∞ Limitations of special indicators such as , and better evaluate the stability of the system under external interference;

[0023] The present invention designs a controller based on periodic dynamic event triggering technology, overcomes the Zeno phenomenon problem in traditional event triggering control, and effectively saves network communication resources.

[0024] The present invention aims at the problem of unstable state of unmanned ocean ship system under external disturbance, takes into account the model of the unmanned ocean ship system and the influence of external disturbance, constructs a periodic dynamic event trigger controller based on the system output signal, performs state stability and dissipation performance analysis on the TS fuzzy model of the unmanned ocean ship system, and solves the gain of the periodic dynamic event trigger controller. In this way, the state stability and dissipation performance of the unmanned ocean ship system are met, thereby improving the stability of the control of the unmanned ocean ship system. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0026] Figure 1 It is a flow chart of a method shown in an embodiment of the present invention.

[0027] Figure 2 It is a schematic diagram showing the state change of the unmanned marine ship system in an open loop situation according to an embodiment of the present invention.

[0028] Figure 3 Schematic diagram of control input of an unmanned marine vessel system according to an embodiment of the present invention.

[0029] Figure 4 It is a schematic diagram showing the state change of the unmanned marine vessel system in a closed loop according to an embodiment of the present invention.

[0030] Figure 5 This is a diagram of event triggering time and event triggering interval according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The present invention is further described and illustrated below in conjunction with specific embodiments. The embodiments are merely exemplary of the present disclosure and do not define the scope of limitation. The technical features of each embodiment of the present invention may be combined accordingly without conflicting with each other.

[0032] Figure 1 is a flow chart of a method for controlling safety of an unmanned marine vessel based on a fuzzy model according to an exemplary embodiment. Figure 1 As shown, the method comprises the following steps:

[0033] S1: Construct the TS fuzzy model of the unmanned marine ship system according to the motion state of the unmanned marine ship system.

[0034] S2: Based on the output signal of the unmanned marine ship system, a periodic dynamic event trigger controller is designed.

[0035] S3: The TS fuzzy model of the unmanned ocean ship system and the periodic dynamic event trigger controller are used to obtain an unmanned ocean ship closed-loop control system.

[0036] S4: Analyze the state stability and dissipation performance of the unmanned ocean vessel closed-loop control system, and solve the gain of the periodic dynamic event triggering controller.

[0037] S5: Using the periodic dynamic event trigger controller and the gain to perform safety control on the unmanned ocean vessel system.

[0038] It can be seen from the above embodiments that the present application aims at the problem of unstable state of unmanned ocean ship system under external disturbance, while taking into account the model of the unmanned ocean ship system and the influence of external disturbance, constructs a periodic dynamic event trigger controller based on the system output signal, performs state stability and dissipation performance analysis on the TS fuzzy model of the unmanned ocean ship system, and solves the gain of the periodic dynamic event trigger controller. In this way, the state stability and dissipation performance of the unmanned ocean ship system are met, thereby improving the stability of the control of the unmanned ocean ship system.

[0039] In the specific implementation of S1: construct the TS fuzzy model of the unmanned marine ship system;

[0040] Specifically, the TS fuzzy model is used to approximate the real model of the unmanned marine ship system, so as to deal with nonlinear characteristics and dynamic uncertainties. The complex nonlinear dynamic process is decomposed into the weighted average of several linear subsystems through the fuzzy logic system, which effectively simplifies the design of the control law and the stability analysis and reduces the difficulty of analysis.

[0041] The TS fuzzy model of the unmanned marine ship system constructed in this example is as follows:

[0042] Fuzzy rule i: If τ 1 (t) is F i1 , and τ 2 (t) is F i2 ,

[0043] but

[0044]

[0045] y(t)=Cx(t)

[0046] z(t)=Dx(t)

[0047] Where, the system state x(t) = [x p (t),y p (t),ψ(t),v 1 (t),v 2 (t),v 3 (t)] T ,(x p (t),y p (t))、ψ(t)、v 1 (t), v 2 (t) and v 3 (t) represent the position coordinates, yaw angle, longitudinal velocity, transverse velocity and yaw velocity of the unmanned ocean vessel respectively; u(t) represents the control input; d(t) represents the disturbance caused by waves; y(t) is the output signal, C is the observation matrix; z(t) is the target output, D is the output matrix; F i1 and F i2 is a fuzzy set, i∈{1,2,3,4}; τ 1 (t) and τ 2 (t) is the premise variable. Other system matrix parameters in (1) are

[0048]

[0049]

[0050] Among them, M, N, G and E represent the inertia matrix, damping matrix, mooring force matrix and thruster configuration matrix of the unmanned marine ship respectively. The TS fuzzy model of the unmanned marine ship system can also be rewritten as:

[0051]

[0052] y(t)=Cx(t)

[0053] z(t)=Dx(t)

[0054] in, τ(t)=[τ1 (t),τ 2 (t)],h i (τ(t)) is the normalized fuzzy weighting function, which satisfies:

[0055]

[0056] In the specific implementation of S2: according to the output signal of the unmanned marine ship system, a periodic dynamic event triggering controller is designed;

[0057] Specifically, designing a controller based on the output signal of the unmanned marine vessel system can more effectively improve the practicality of the controller compared to designing the controller directly based on the state value; in addition, a periodic dynamic event trigger mechanism is introduced to reduce the communication load and computing resource consumption, thereby optimizing resource utilization efficiency and improving the control effect of the system.

[0058] According to the output signal of the unmanned marine ship system, a periodic dynamic event trigger controller is constructed:

[0059] u(t)=Ky(t k ),t∈[t k ,t k+1 )

[0060] Where K is the controller gain to be determined, t k+1 Strategy generation is triggered based on periodic dynamic events:

[0061] t k+1 =min{t>t k |βζ(t)-(y(t)-y(t k )) T O(y(t)-y(t k ))

[0062] +εy T (t)Uy(t)≤0,t∈{s n}}

[0063] Among them, s n =nh(n=0,1,2,...), h is the sampling period; O≥0 and U≥0 are the weight matrices to be determined; ε>0 is a constant; ζ(t) is a dynamic variable, for t∈[s n ,s n+1 ), ζ(t) satisfies the equation

[0064]

[0065] Where L is the pre-designed weight matrix, is an adjustable parameter, and α and β are positive constants. In the specific implementation of 3: according to the TS fuzzy model of the unmanned ocean ship system and the periodic dynamic event triggering controller, an unmanned ocean ship closed-loop control system is obtained.

[0066] Specifically, according to equations (2) and (4), the closed-loop control system of the unmanned marine vessel is obtained:

[0067]

[0068] In the specific implementation of S4: the state stability and dissipation performance of the unmanned ocean vessel closed-loop control system are analyzed, and the gain of the periodic dynamic event triggering controller is solved.

[0069] Specifically, in the Matlab environment, the specific parameters of the unmanned ocean ship inertia matrix, damping matrix, mooring force matrix and thruster configuration matrix are set respectively, and the initial state of the unmanned ocean ship system is set; the linear matrix inequality is solved based on the system parameters to obtain the gain of the periodic dynamic event triggered controller.

[0070] Among them, the main idea of ​​analyzing the state stability and dissipative performance of the closed-loop control system of unmanned marine ships is: through the Lyapunov function V(t) = V 1P (t)+V 2P (t)+V 3P (t), where V 1P (t) = x T (t)Px(t), The function is derived and calculated; when the initial state of the system is not 0 and d(t) is not always 0, the dissipative performance of the system is studied by combining the formula y(t) = Cx(t), that is,

[0071] Set the parameters in the periodic dynamic event trigger strategy C -1 is the pseudo-inverse matrix of the observation matrix C; if there exists a matrix P>0, R=R T >0, S, Θ>0, Φ, J and constants h>0, σ>0, χ>0, g>0, a>0, 0<b<1, α>0, β>0, κ>0, ρ satisfy And the following linear matrix inequality system Φ:

[0072]

[0073] φ 11 =PA i +(PA i )T +[2σ+χ+(g-1)a(1-b)e -2σh ]P+J, i represents the i-th fuzzy rule; The TS fuzzy model of the unmanned marine ship system can achieve stable and dissipative performance under the action of the periodic dynamic event trigger controller, that is, for any t f >0 and dissipation function satisfy:

[0074]

[0075] The controller gain can be obtained by the following formula

[0076] K=X -1 Y.

[0077] Among them, X and Y are the matrices obtained by solving the above linear matrix inequality system Φ, X -1 is the inverse matrix of matrix X.

[0078] In the specific implementation of S5, the periodic dynamic event triggering controller is used to perform safety control on the unmanned ocean vessel system.

[0079] The controller gain obtained by S4 is applied to an unmanned marine vessel closed-loop control system in a specific embodiment of the present invention to verify the effectiveness of the present invention.

[0080] The system parameter values ​​are:

[0081]

[0082] S=0

[0083]

[0084] By solving the inequality in S4, the following control gains are obtained:

[0085]

[0086] In the simulation, the initial state of the system is set to [5483 65 61-36 61] T ; Disturbance

[0087]

[0088] in,

[0089] is the pseudo-inverse matrix of E.

[0090] Figure 2The figure shows the state change of the unmanned marine ship system in the absence of control input. It can be seen that the open-loop system is unstable, which further illustrates the stability of the closed-loop system under the action of the periodic dynamic event triggering controller. Figure 3 For the designed control input, Figure 4 It can be seen that under the control input, the state of the unmanned ocean ship system gradually approaches zero as time increases, which shows that the periodic dynamic event trigger controller can ensure the stability and dissipation performance of the unmanned ocean ship closed-loop system. Figure 5 are the event triggering time and the event triggering interval. It can be seen that the periodic dynamic event triggering controller realizes the periodic dynamic event triggering control, effectively avoids the Zeno phenomenon, and saves network communication resources.

[0091] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. For ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A method for controlling an unmanned marine ship event trigger output based on a fuzzy model, characterized in that: The following steps are involved: 1) According to the motion state of the unmanned marine ship system, the TS fuzzy model of the unmanned marine ship system is established; 2) Design a periodic dynamic event trigger controller based on the output signal of the unmanned marine ship system; 3) Combining the TS fuzzy model of the unmanned ocean ship system with a periodic dynamic event trigger controller to obtain an unmanned ocean ship closed-loop control system; 4) analyzing the state stability and dissipation performance of the unmanned marine vessel closed-loop control system, thereby solving the gain of the periodic dynamic event triggering controller; 5) Based on the gain of the periodic dynamic event trigger controller in step 4), the periodic dynamic event trigger controller is used to perform closed-loop control on the unmanned marine vessel system; The TS fuzzy model of the unmanned marine ship system is: y(t)=Cx(t) z(t)=Dx(t) h i (σ(t)) is the normalized fuzzy weighting function, which satisfies: Where u(t) represents the control input; d(t) represents the disturbance caused by the wave; y(t) is the output signal, C is the observation matrix; z(t) is the target output, D is the output matrix; F i1 and F i2 is a fuzzy set, i∈{1,2,3,4}; τ1(t) and τ2(t) are premise variables, A i is the state matrix, B is the control matrix; According to the output signal of the unmanned marine ship system, a periodic dynamic event trigger controller is constructed, including: Combined with the output signal of the unmanned marine ship system, a periodic dynamic event trigger controller is designed as u(t)=Ky(t k ),t∈[t k ,t k+1 ) Where K is the controller gain to be determined, t k+1 Strategy generation is triggered based on periodic dynamic events: t k+1 =min{t>t k |βζ(t)-(y(t)-y(t k )) T O(y(t)-y(t k ))+εy T (t)Uy(t)≤0,t∈{s n }} Among them, s n =nh(n=0,1,2,...), h is the sampling period for sampling the output signal; O≥0 and U≥0 are the weight matrices to be determined; ε>0 is a set constant; ζ(t) is a dynamic variable, for t∈[s n ,s n+1 ), ζ(t) satisfies the equation: Where L is the pre-designed weight matrix, is an adjustable parameter, α and β are set positive constants; The unmanned marine vessel closed-loop control system is: Among them, h i (σ(t)) is the normalized fuzzy weighted function, y(t) is the output signal, C is the observation matrix, x(t) is the state of the unmanned marine ship system, z(t) is the target output, D is the output matrix, τ1(t) and τ2(t) are the premise variables, and d(t) represents the fluctuation caused by waves.

2. The unmanned marine vessel event trigger output control method according to claim 1, characterized in that: In step 1, the state x(t) of the unmanned marine vessel system is: x(t)=[x p (t),y p (t),ψ(t),v1(t),v2(t),v3(t)] T Among them, (x p (t),y p (t)) is the position coordinate of the unmanned ocean ship, ψ(t) is the yaw angle of the unmanned ocean ship, v1(t) is the longitudinal speed of the unmanned ocean ship, v2(t) is the lateral speed of the unmanned ocean ship, and v3(t) is the yaw speed of the unmanned ocean ship.

3. The unmanned marine vessel event trigger output control method according to claim 1, characterized in that: The step 4) specifically includes: setting specific parameters of the unmanned ocean ship inertia matrix, damping matrix, mooring force matrix and thruster configuration matrix respectively in the Matlab environment, and setting the initial state of the unmanned ocean ship system; The linear matrix inequality is solved based on the unmanned ocean ship system parameters to obtain the gain of the periodic dynamic event triggered controller.

4. The unmanned marine vessel event trigger output control method according to claim 3, characterized in that: The linear matrix inequality is solved based on the system parameters to obtain the gain of the periodic dynamic event triggered controller, which is specifically: Set the parameters in the periodic dynamic event trigger strategy C -1 is the pseudo-inverse matrix of the observation matrix C; if there exists a matrix P>0, R=R T >0, S, Θ>0, Φ, J and constant h>0, σ>0, χ>0, g>0, a>0, 0<b<1, α>0, β>0, κ>0, ρ satisfy And the following linear matrix inequality system Φ: φ 11 =PA i +(PA i ) T +[2σ+χ+(g-1)a(1-b)e -2σh ]P+J, i represents the i-th fuzzy rule; The TS fuzzy model of the unmanned marine ship system can achieve stable and dissipative performance under the action of the periodic dynamic event trigger controller, that is, for any t f >0 and dissipation function satisfy: The controller gain is obtained by K=X -1 AND; Among them, X and Y are the matrices obtained by solving the above linear matrix inequality system Φ, X -1 is the inverse matrix of matrix X.

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