Unmanned ship quantitative sliding mode fault-tolerant control method with propeller saturation

Abstract

The application discloses a kind of unmanned ship quantization sliding mode fault-tolerant control methods with propeller saturation, comprising: S1: based on traditional unmanned ship dynamics equation and kinematics equation, in combination with propeller failure, saturation model, establish the unmanned ship system model under actuator failure saturation;S2: establish the unmanned ship system quantization model;S3: by introducing unknown positive definite matrix X, establish the sliding mode surface that can make the system sliding mode asymptotically stable;S4: based on adaptive update law, select the positive definite Lyapunov function, control unmanned ship system error enters into banded region;S5: based on sliding mode fault-tolerant controller, by Lyapunov second method establishes the attraction domain that makes error converge to zero;S6: based on the dynamic adjustment of quantization parameter, the error of unmanned ship system evolves to spherical domain in banded region, and finally asymptotically reaches equilibrium point;S7: simulation experiment is carried out to floating production ship, thereby verifying the effectiveness of unmanned ship quantization sliding mode fault-tolerant control method.

Description

Technical Field

[0001] This invention relates to the field of unmanned vessel control, and more particularly to a quantized sliding mode fault-tolerant control method for unmanned vessels with thruster saturation. Background Technology

[0002] In ship DP feedback control systems, thrusters inevitably malfunction during prolonged operation in complex marine environments. Secondly, in practice, the thruster execution of unmanned surface vessels (USVs) is typically quite limited, exhibiting saturation. Therefore, excessively large control commands cannot be effectively executed. Since the thruster is controlled by a land-based control station, the signals from the input and output controllers are quantized. The quantization phenomenon of digital signals exists in the connection channel between the controlled object and the controller in the feedback control system, a point worthy of in-depth study. For the quantization error control problem of USVs, it is essential to address the interaction between thruster saturation and quantization effects, and to design a quantization sliding mode controller that can tolerate thruster failure. Summary of the Invention

[0003] To address the problems existing in the prior art, this invention discloses a quantitative sliding mode fault-tolerant control method for unmanned surface vessels with thruster saturation, specifically including the following steps:

[0004] S1: Based on the traditional unmanned vessel dynamics equations and kinematic equations, and combined with the propeller failure and saturation model, establish an unmanned vessel system model under actuator failure saturation;

[0005] S2: Establish a quantitative model for the unmanned vessel system based on the principle that system errors are quantified after entering the network channel;

[0006] S3: Based on the quantitative model of the unmanned vessel system, a sliding surface that can make the sliding mode of the system asymptotically stable is established by introducing a constant matrix X;

[0007] S4: Based on the sliding surface, design a sliding mode fault-tolerant controller and an adaptive update law, select a positive definite Lyapunov function, and control the unmanned vessel system error to enter the strip region;

[0008] S5: Based on the sliding mode fault-tolerant controller, an attraction domain that converges the error to zero is established using Lyapunov's second method;

[0009] S6: Based on the dynamic adjustment of quantization parameters, the error of the unmanned ship system is evolved from the strip region to the spherical region and finally asymptotically reaches the equilibrium point;

[0010] S7: Conduct simulation experiments on floating production vessels to verify the effectiveness of the quantitative sliding mode fault-tolerant control method for unmanned vessels.

[0011] S3 specifically adopts the following method:

[0012] S31: Perform full-rank decomposition on the input matrix B of the unmanned surface vessel system quantization model: in, N=ιN * ι>0 is an introduced parameter;

[0013] S32: Design as a sliding mold surface: Where X is the constant matrix to be designed;

[0014] S33: Solve for the following LMIs, design the constant matrix X, construct the reduced-order sliding surface through the full-rank decomposition of the input matrix B, design the upper bound of the unknown fault parameters and the unknown jamming fault, and design the sliding mode control law to control the unmanned vessel system to reach the sliding surface.

[0015]

[0016]

[0017] S4 specifically adopts the following method:

[0018] S41: Design the nonlinear control law, as follows:

[0019] in, and They are σ and The estimated value; yes The estimated value ∈ is an arbitrarily small positive scalar;

[0020] S42: Prove that the unmanned vessel system state will enter a banded region under the action of the control law, and prove that the system state will enter a spherical region under the dynamic adjustment of the quantization parameters. First, construct a Lyapunov function, specifically:

[0021] V = V1 + V2, V1 = α T (e)(SB v ) -1 α(e)

[0022]

[0023] Taking the derivative of V1, we get

[0024]

[0025] S43: Based on the fault-tolerant control law, design the following adaptive law:

[0026]

[0027] Where, γ1i ,γ 2i ,γ 3i It is the adaptive gain constant.

[0028] S44: Apply the control law and the adaptive law to the Lyapunov function in S42 above, and derive...

[0029]

[0030] Therefore, by processing the above formula again, we obtain...

[0031]

[0032] This indicates that H represents the unmanned ship system. ∞ The performance index is no greater than γ, and the unmanned vessel system's state trajectory will enter a strip-shaped region.

[0033] S5 adopts the following method:

[0034] S51: By solving the LMIs in S33, the attraction domain parameter k is optimized.

[0035] S52. Under the action of a nonlinear control law, the attraction region is obtained through Lyapunov function analysis.

[0036] The specific process of step S6 is as follows:

[0037] S61: Propose an algorithm for dynamically quantizing parameter h2: in M is a calculated constant value.

[0038] S62: Adjust the state evolution of the unmanned vessel system quantization model within the strip region, control the sliding surface to approach 0, and the error state asymptotically reaches the equilibrium point.

[0039] By adopting the above technical solution, this invention provides a quantized sliding mode fault-tolerant control method for unmanned surface vessels with thruster saturation. This method reveals the relationship between quantization parameters, fault information, and saturation parameters of the unmanned surface vessel, and provides a larger range for adjusting the quantization parameters. This range depends on the desired position and velocity, the lower limit of the fault information, and the lower limit of the saturation parameters. Therefore, this method designs a new fault-tolerant controller that can ensure the asymptotic stability of the system and compensate for the effects of quantization, thruster failure, and saturation. As a result, this method has been widely promoted and applied in fields such as ship dynamic positioning control. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 A flowchart of the sliding mode quantization fault-tolerant control design for a ship DP system provided in an embodiment of the present invention.

[0042] Figure 2 The response curve of the speed error of the ship DP system provided in the embodiment of the present invention.

[0043] Figure 3 The response curve of the position error of the ship DP system provided in the embodiment of the present invention.

[0044] Figure 4 The response curve of the yaw rate of the ship DP system provided in the embodiment of the present invention.

[0045] Figure 5 The response curve of the sliding surface of the DP control system provided in the embodiment of the present invention.

[0046] Figure 6 The response curve of the thruster command of the DP control system provided in the embodiment of the present invention.

[0047] Figure 7 The response curve of the quantization parameter h2 of the DP control system provided in the embodiment of the present invention.

[0048] Figure 8 This is an estimated region diagram of the attraction domain of the DP control system provided in an embodiment of the present invention. Detailed Implementation

[0049] To make the technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention:

[0050] like Figure 1 The method for quantized sliding mode fault-tolerant control of an unmanned surface vessel with thruster saturation, as shown, specifically includes the following steps:

[0051] S1: Based on the traditional dynamic and kinematic equations of unmanned vessels, and combined with propeller failure and saturation models, establish an unmanned vessel system model under actuator failure saturation:

[0052] S11. The kinematic and dynamic equations of the unmanned vessel system are defined as follows:

[0053]

[0054] Where η(t) = [x p (t),y p (t),ψ(t)] T These represent the ship's position and yaw angle, respectively. v(t) = [ζ(t), ν(t), r(t)] T Let represent the surge speed, roll speed, and yaw speed of the ship, respectively. M, N, and E represent the inertia matrix, damping matrix, and mooring force matrix, respectively. u(t) is the thrust vector, and Γ is the configuration matrix.

[0055] S12. Based on the thruster failure model, establish an unmanned surface vessel model under thruster failure; the actuator failure model is specifically as follows:

[0056]

[0057] Where i = 1, ..., m, j = 1, ..., l, and l is the total number of failure modes. For the i-th thruster under the j-th failure mode, These represent the actual thrust of the thruster, the thruster command, and the thruster's unknown time-varying bounded deadlock fault, respectively. Let these be the thruster efficiency coefficient and the card failure coefficient. Then, the following matrix is ​​introduced:

[0058]

[0059] in, The thruster failure model is u F (t)=ρu(t)+σu s (t).

[0060] S13. To compensate for saturation, the proposed saturation model is introduced. The thruster failure and saturation model is then:

[0061] u S (t)=sat(ρu(t)+σu s (t))=ρχu(t)+σu s (t)

[0062] Where χ∈(0,1] is the saturation coefficient.

[0063] S14. Define the error vector Where η ref It is the desired position vector, v ref It is the desired velocity vector, and the system state x = [η] T (t)v T (t)] T Desired position and velocity, state error After state error matrix transformation, the unmanned vessel DP control error system is as follows:

[0064]

[0065] Where D=B1ω+Ae d z represents the control output.

[0066] S2: A quantitative model of the unmanned surface vessel system is established based on the principle that system errors are quantized after entering the network channel.

[0067] S21. Since the thruster is controlled by a land-based control station, the signals from the input and output controllers are quantized. This step uses the following quantization method to design the controller:

[0068]

[0069] S22, Definition but

[0070]

[0071] in It is a static quantizer. It is a dynamic quantizer.

[0072] S3: Based on the quantization model of the unmanned vessel error system, a sliding surface that can asymptotically stabilize the sliding mode of the system is established by introducing a constant matrix X:

[0073] S31. Perform full-rank decomposition on the input matrix: in, N=ιN * ι>0 is an introduced parameter.

[0074] S32. Design the sliding surface, as follows: Where X is the constant matrix to be designed.

[0075] S33. Design the constant matrix X. Solve for the following LMIs:

[0076]

[0077]

[0078] S4: Based on the sliding mode surface, a sliding mode fault-tolerant controller and an adaptive update law are designed, and a positive definite Lyapunov function is selected to control the unmanned ship system error to enter the banded region. The specific process is as follows: First, the quantization parameters are fixed. At this time, it is proved that the unmanned ship system state will enter the banded region under the action of the control law. Second, it is proved that the system state will enter a spherical region under the dynamic adjustment of the quantization parameters.

[0079] S41: Design the nonlinear control law, as follows:

[0080] in, and They are σ and The estimated value; yes The estimated value ∈ is an arbitrarily small positive scalar;

[0081] S42: Prove that the unmanned vessel system state will enter a banded region under the action of the control law, and prove that the system state will enter a spherical region under the dynamic adjustment of the quantization parameters. First, construct a Lyapunov function, specifically:

[0082] V = V1 + V2, V1 = α T (e)(SB v ) -1 α(e)

[0083]

[0084] Taking the derivative of V1, we get

[0085]

[0086] S43: Based on the fault-tolerant control law, design the following adaptive law:

[0087]

[0088] Where, γ 1i ,γ 2i ,γ 3i It is the adaptive gain constant.

[0089] S44: Apply the control law and the adaptive law to the Lyapunov function in S42 above, and derive...

[0090]

[0091] Therefore, by processing the above formula again, we obtain...

[0092]

[0093] This indicates that H represents the unmanned ship system. ∞ The performance index is no greater than γ, and the unmanned vessel system's state trajectory will enter a strip-shaped region.

[0094] S5: Based on the sliding mode fault-tolerant controller, an attraction region is established using Lyapunov's second method to converge the error to zero: The attraction region of an asymptotically stable equilibrium point of a dynamic system is a part of the state space, generated by the trajectory converging to that equilibrium point. The formation of the band is due to the influence of quantization; therefore, the sliding mode control law cannot guarantee that the system state reaches and remains on the sliding surface, but rather reaches the band near the sliding surface. Through the LMIs in step 3, the k required for the attraction region will be optimized.

[0095] S51. Under the action of the control law, the attraction field is obtained by Lyapunov function analysis and by solving k through LMIs.

[0096] S6: After the state in the attraction domain enters the zone described in S4, the quantization parameters begin to adjust. Based on their dynamic adjustment, the error of the unmanned ship system evolves from the zone to the spherical domain and eventually asymptotically reaches the equilibrium point.

[0097] S61. In this invention, in the uplink channel, we use a static quantizer 1 to quantize the control input signal, and in the downlink channel, we use a dynamic quantizer with a statically adjustable quantization parameter h2 to quantize the error state signal. Since the static quantizer has a simple structure and is easy to implement in practical engineering applications, quantizer 1 uses a static quantizer. If quantizer 2 also uses a static quantizer, then the traditional sliding mode control law cannot guarantee that the system state reaches and remains on the sliding surface, but rather reaches the sliding band near the sliding surface. Therefore, quantizer 2 uses a dynamic quantizer. Thus, an algorithm for the dynamic quantization parameter h2 is proposed: in M is a calculated constant value.

[0098] S62. The state of the unmanned vessel system evolves within the strip region. Due to the quantization parameter adjustment strategy, the sliding surface will tend to 0, and the error state will also asymptotically reach the equilibrium point.

[0099] S7: Simulation experiments were conducted on a floating production vessel to verify the effectiveness of the quantized sliding mode fault-tolerant control method for unmanned vessels. To verify the effectiveness of the quantized feedback control method for unmanned vessels based on sliding mode strategy with propeller failure, saturation, and ocean disturbances provided in this invention, simulation experiments were conducted using MATLAB, and detailed explanations are provided.

[0100] The system matrix of a typical floating production vessel is scaled down proportionally, and the initial error state of the unmanned vessel system is selected as follows. Furthermore, other initial parameters are selected as follows.

[0101]

[0102]

[0103] r 1i =r 2i =r 3i =0.1

[0104] x pd =y pd =ψ d =ζ d =ν d =0

[0105] The yaw angle is selected in the following form:

[0106]

[0107] To simulate the dynamic positioning of an unmanned surface vessel (USV) in practical applications, the fault modes are set as follows: when t ≤ 70s, all thrusters function normally; when t > 70s, 50% of the port main propeller fails, 70% of the starboard main propeller fails, all thrusters in the stern tunnel 1 fail, and the remaining thrusters function normally. Ocean disturbance w(t) = [w1(t), w2(t), w3(t)] T Occurs from 0-20 seconds, set as

[0108] w1(t) = 0.1*sin(t)

[0109] w2(t)=0.1

[0110] w3(t) = -0.1*sin(t)

[0111] Based on the above parameters, the proposed quantized feedback control method for unmanned surface vessels with thruster failure, saturation, and ocean disturbances based on sliding mode strategy is simulated and verified. Figure 2-8 As shown. Among them, Figure 2 The system speed error response curve is displayed, and it eventually converges to near 0; Figure 3 The system displays the response curve of the position error and gradually converges to the desired position; Figure 4 The system displays the response curve of the yaw rate, and through the action of the control law, it satisfies the real-time change of the set yaw rate. Figure 5 , Figure 6 The system's sliding surface curve and thruster command curve gradually approached 0, and finally the chattering almost completely disappeared. Figure 7 The response curve of the display control system's quantization parameter h2 tends to 0 after the adjustment effect ends; ultimately, Figure 8 This is a region diagram for estimating the attraction domain under different fault parameters of the DP control system provided in this embodiment of the invention; this completes the digital simulation of the algorithm of the present invention and verifies its effectiveness.

[0112] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A quantitative sliding mode fault-tolerant control method for unmanned surface vessels with thruster saturation, characterized in that... include: S1: Based on the traditional unmanned vessel dynamics equations and kinematic equations, and combined with the propeller failure and saturation model, establish an unmanned vessel system model under actuator failure saturation; S2: Establish a quantitative model for the unmanned vessel system based on the principle that system errors are quantified after entering the network channel; S3: Based on the quantization model of unmanned surface vessel systems, by introducing a constant matrix. Establish a sliding surface that enables the system to achieve asymptotic stability in its sliding modes; S4: Based on the sliding surface, design a sliding mode fault-tolerant controller and an adaptive update law, select a positive definite Lyapunov function, and control the unmanned vessel system error to enter the strip region; S5: Based on the sliding mode fault-tolerant controller, an attraction domain that converges the error to zero is established using Lyapunov's second method; S6: Based on the dynamic adjustment of quantization parameters, the error of the unmanned ship system is evolved from the strip region to the spherical region and finally asymptotically reaches the equilibrium point; S7: Conduct simulation experiments on floating production vessels to verify the effectiveness of the quantitative sliding mode fault-tolerant control method for unmanned vessels; S4 specifically adopts the following method: S41: Design the nonlinear control law, as follows: in, , and They are and The estimated value; yes The estimated value ( ); It is an arbitrarily small positive scalar; S42: Prove that the unmanned vessel system state will enter a banded region under the action of a nonlinear control law, and prove that the system state will enter a spherical domain under the dynamic adjustment of quantization parameters. First, construct a Lyapunov function, specifically: Among them Taking the derivative, we get S43: Design the following adaptive law based on the nonlinear control law: in, , , It is the adaptive gain constant; S44: Apply the nonlinear control law and the adaptive law to the Lyapunov function in S42 above, and derive... Therefore, by processing the above formula again, we obtain... This indicates an unmanned ship system. Performance indicators not greater than Furthermore, the unmanned vessel system's status trajectory will enter a strip-shaped area.

2. The quantized sliding mode fault-tolerant control method for unmanned surface vessels with thruster saturation according to claim 1, characterized in that: S3 specifically adopts the following method: S31: Input matrix for the quantization model of the unmanned surface vessel system Perform full-rank decomposition: ,in, , , For the introduced parameters; S32: Design as a sliding mold surface: ,in It is the constant matrix to be designed; S33: Solve for the following LMIs and design the constant matrix. By input matrix The full-rank decomposition is used to construct a reduced-order sliding surface, and the upper bound values ​​of unknown fault parameters and unknown jamming faults are designed and estimated. The sliding control law is designed to control the unmanned ship system to reach the sliding surface. 。 3. The quantized sliding mode fault-tolerant control method for unmanned surface vessels with thruster saturation according to claim 2, characterized in that: S5 adopts the following method: S51: By solving for the LMIs in S33, the attraction field parameters are optimized. , S52. Under the action of a nonlinear control law, the attraction region is obtained through Lyapunov function analysis. .

4. The quantized sliding mode fault-tolerant control method for unmanned surface vessels with thruster saturation according to claim 1, characterized in that: The specific process of step S6 is as follows: S61: Propose dynamic quantization parameters Algorithm: ,in , The calculated constant value; S62: Adjust the state evolution of the unmanned vessel system quantization model within the strip region, control the sliding surface to approach 0, and the error state asymptotically reaches the equilibrium point.

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