Control method of tilting device suitable for stable navigation attitude of small unmanned ship

Abstract

The invention relates to a control method of a tilting device suitable for a stable navigation attitude of a small unmanned ship, and belongs to the technical field of ship control. The method comprises the following steps: identifying discretization model parameters of an execution mechanism and a hull attitude through a preset test; collecting a trim angle, a roll angle, a tipping angle and a rudder angle in real time; predicting a future attitude trend based on the model by using a generalized prediction algorithm and generating a preliminary control quantity; the fine adjustment amount is calculated through a PID controller; superposing the decoupling feedforward quantity to obtain a comprehensive instruction; the final angle control quantity is output after dynamic model compensation of the executing mechanism, the tipping bucket and the steering engine are driven to adjust the angle of the water injection nozzle, and attitude closed-loop stable control is achieved. According to the invention, high-precision decoupling control of trim and roll motion is realized, the response is fast, the method adapts to complex sea conditions, and the stability of a load platform during high-speed navigation of the unmanned ship is obviously improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of unmanned ship navigation attitude control, and particularly relates to a lifting device control method suitable for small unmanned ship navigation stable attitude, which is used for realizing attitude stability in the longitudinal and lateral roll directions in the navigation process to ensure the normal working conditions of the shipborne equipment. BACKGROUND

[0002] As a flexible and low-cost marine operation platform, small unmanned ships have been widely used in environmental monitoring, sea area patrol, load delivery and other tasks. In order to ensure that the special equipment (such as rotor unmanned aircraft transceiver shelter, unmanned aircraft launching device, etc.) carried by the unmanned ship can operate normally and safely, higher requirements are often put forward for the attitude stability of the unmanned ship in navigation. During the take-off, launch or recovery of these equipment, the longitudinal angle (pitch angle) and the roll angle (roll angle) of the carrying platform are usually required to be kept stable within a certain range, otherwise it may cause equipment damage or task failure.

[0003] At present, the common small and fast unmanned ships mostly adopt water jet propulsion scheme, and the engine and propulsion system mainly have two types of designs of external loop and internal loop. Among them, the internal loop design usually realizes water circulation cooling and provides power for navigation through single or double jet pumps. The engine drives the jet pump through a transmission shaft or a hydraulic system, and high-speed water flow is sprayed from the water jet to generate thrust. In order to control the heading and attitude, this kind of system usually is equipped with two sets of actuators: a tipping bucket is used to adjust the pitch angle of the water jet to control the forward, reverse and longitudinal attitude; and a rudder angle mechanism adjusts the left and right deflection angle of the water jet through a connecting rod to affect the steering and roll attitude.

[0004] In this kind of propulsion and attitude control structure, the pitch angle mainly refers to the rotation angle around the transverse axis of the ship body, reflecting the pitch state of the ship body; the roll angle refers to the rotation angle around the longitudinal axis, reflecting the left and right inclination of the ship body. Both of them are directly related to the navigation stability and load safety, and generally require static fluctuation not more than ±5° and dynamic (such as 3~5 sea conditions) not more than ±10°.

[0005] To maintain the above attitude stability, the traditional technical means mainly include speed suppression method, single closed-loop control strategy and local actuator control. The speed suppression method reduces the wave disturbance caused by the rocking of the boat body by reducing the sailing speed. Although this method is simple, it seriously sacrifices the speed and task efficiency of the unmanned surface vehicle. The single closed-loop control strategy is to independently adjust the pitch or roll by using the classic PID control. This method is applicable in calm water or small disturbance, but in complex sea conditions, it often lags in response and has obvious overshoot due to the lack of foresight and anti-coupling ability, and it is difficult to meet the requirements of speed and accuracy at the same time. The local actuator control is to focus on controlling the rudder angle to maintain the heading, and the active adjustment of the flipper angle is insufficient, resulting in single pitch attitude control means and limited adjustment capacity.

[0006] However, these traditional methods have obvious technical defects: it is difficult to balance speed and stability, the speed reduction and attitude stabilization method cannot meet the high-speed operation demand; the control accuracy and response speed are insufficient, the single PID control performance decreases in nonlinear, time-varying and strong disturbance environment; the motion coupling is not systematically processed, there is significant fluid dynamic and inertial coupling between the pitch and roll when the unmanned surface vehicle moves in water, the traditional independent control method cannot effectively decouple, resulting in mutual interference; the model adaptability is poor, most methods do not update the model online or adjust the parameters according to the speed change and actuator dynamic characteristics (such as hydraulic system lag), and the control effect fluctuates greatly under different working conditions.

[0007] Therefore, there is an urgent need for a method that can realize fast and high-precision decoupling control of pitch and roll without sacrificing speed, in order to improve the attitude stability and task adaptability of small unmanned surface vehicles in complex sea conditions. SUMMARY

[0008] To solve the technical problems of the existing small unmanned surface vehicle attitude control method, such as the contradiction between speed and stability, insufficient control accuracy, pitch and roll motion coupling not decoupled, and poor model adaptability, the present application proposes a heave device control method suitable for the stable attitude of small unmanned surface vehicles sailing. This method combines generalized predictive control and PID control without sacrificing speed, and through the coordinated and accurate control of the flipper angle and the rudder angle, the water jet angle is quickly adjusted to realize high-precision and decoupling stable control of the pitch angle and roll angle of the unmanned surface vehicle, and to improve its task adaptability and load platform stability in complex sea conditions.

[0009] The technical scheme of the present application is as follows:

[0010] A heave device control method suitable for the stable attitude of small unmanned surface vehicles sailing, comprising the following steps:

[0011] Step 1: Real-time data acquisition

[0012] The current pitch angle and roll angle of the unmanned ship are acquired in real time by an inertial navigation device; the current actual values of the tipping bucket angle and the rudder angle are acquired in real time by an angle sensor;

[0013] Step 2: Generalized predictive control quantity calculation:

[0014] Based on the current attitude angle, the target attitude angle and the turning angle model, the attitude angle change trend in a future period of time is predicted by using a generalized prediction algorithm, and a preliminary angle control quantity is generated.

[0015] Step 3: PID fine tuning quantity calculation:

[0016] The angle fine tuning control quantity of the attitude angle error is calculated by a PID controller based on the preliminary angle control quantity generated by the generalized prediction algorithm.

[0017] Step 4: Decoupling and comprehensive control quantity calculation:

[0018] The preliminary angle control quantity, the angle fine tuning control quantity and the angle decoupling feedforward quantity for offsetting the coupling effect of the pitch and roll motion are superimposed to obtain a comprehensive control instruction.

[0019] Step 5: Actuator dynamic compensation and final instruction generation:

[0020] The comprehensive control instruction and the current tipping bucket angle and rudder angle actual values are input into a rudder model for dynamic compensation calculation, and the final angle control quantity after compensation is output.

[0021] Step 6: Control execution and closed-loop feedback:

[0022] The PLC control signal is calculated according to the final angle control quantity and is output to the PLC controller, the PLC controller controls the lifting device to drive the tipping bucket and the rudder actuator to move, adjusts the water outlet angle, thereby controlling the ship body attitude; the attitude angle and the actuator angle are detected in real time, and the information is fed back to the control system to form a closed-loop correction and rolling optimization.

[0023] Further preferred, the rudder model adopts a first-order inertia link to describe the dynamic response characteristics of the hydraulic lifting device; the turning angle model adopts a second-order inertia link to describe the dynamic response of the ship body attitude angle to the water outlet angle change.

[0024] Further preferably, the turning angle model and the rudder model obtain model parameters through a pre-designed model parameter identification test: time domain data of the tipping bucket angle, the rudder angle, the pitch angle and the roll angle of the unmanned ship at different speeds are collected respectively; based on the time domain data, the first-order inertia link model parameters describing the dynamic of the unmanned ship actuator and the second-order turning angle model parameters describing the response of the unmanned ship body posture are identified; and the model is discretized into a state space form to obtain system matrices.

[0025] Further preferably, the model parameter identification includes the following steps:

[0026] (1) At different set speeds, continuous excitation tests are respectively performed on the tipping bucket angle actuator and the rudder angle actuator of the unmanned ship, and the control input signal, the actual value of the actuator angle (tipping bucket angle and rudder angle), the pitch angle and the roll angle data of the ship body are synchronously collected;

[0027] (2) Based on the collected data, a first-order inertia link model of the tipping bucket angle and the rudder angle actuator is fitted by using a system identification method, and the rudder model parameters are obtained;

[0028] (3) Based on the collected data, a second-order turning angle model of the pitch angle to the tipping bucket angle and the roll angle to the rudder angle is fitted by using a system identification method, and the turning angle model parameters of the ship body are obtained;

[0029] (4) The rudder model and the turning angle model are discretized into a state space form.

[0030] Further preferably, in the model parameter identification:

[0031] the collected tipping bucket angle control quantity is taken as the input, the collected actual value of the tipping bucket angle is taken as the output, and the system transfer function of the tipping bucket angle corresponding to the lifting device, i.e., the rudder model corresponding to the tipping bucket angle, is identified;

[0032] the collected actual value of the tipping bucket angle is taken as the input, and the collected pitch angle is taken as the output, and the pitch angle body posture angle turning model transfer function, i.e., the turning angle model corresponding to the pitch angle, is identified;

[0033] the collected rudder angle control quantity is taken as the input, the collected actual value of the rudder angle is taken as the output, and the system transfer function of the rudder angle corresponding to the lifting device, i.e., the rudder model corresponding to the rudder angle, is identified;

[0034] the collected actual value of the rudder angle is taken as the input, and the collected roll angle As output, the transfer function of the hull attitude angle rotation model for the roll angle is identified, that is, the rotation model corresponding to the roll angle.

[0035] Beneficial effects

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. This invention combines feedforward optimization of the generalized prediction algorithm with feedback regulation of the PID algorithm, resulting in a rapid system response and high steady-state accuracy, meeting the stability requirements under high-speed navigation.

[0038] 2. By independently modeling and introducing decoupling feedforward, this invention significantly reduces the mutual interference between pitch and roll motions, and achieves independent and precise control of the two-axis motion.

[0039] 3. This invention identifies model parameters based on actual navigation data and distinguishes different speed conditions, enabling the control system to better adapt to complex sea conditions and speed changes.

[0040] 4. The method and steps of this invention are clear, the physical meaning of the model is clear, it is easy to integrate into the existing unmanned surface vessel navigation control system, and it has high reliability.

[0041] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0042] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0043] Figure 1 : Flowchart of the control method of the present invention. Detailed Implementation

[0044] The embodiments of the present invention are described in detail below. These embodiments are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0045] To achieve the stability requirements of fast-moving, small unmanned surface vessels (USVs) carrying equipment during navigation, this embodiment proposes a control method for the tilting device suitable for the stable attitude of small USVs. By combining a generalized predictive algorithm and a PID control method, the tipping bucket and rudder angle control quantities are calculated to control the movement of the actuators and adjust the nozzle angle. Simultaneously, the pitch and roll motions of the USV are decoupled, enabling independent control of both angles. This invention establishes mathematical models for both directions of motion, identifies different transfer functions, and adds a feedforward compensation term to the control system to counteract the coupling effect between pitch and roll.

[0046] The hardware foundation for implementing this embodiment is:

[0047] An inertial navigation device is installed at the turning center of the unmanned surface vessel (USV). By default, the attitude angle and angular velocity information output by the inertial navigation device used by the data user within the USV system has already been converted to baseline.

[0048] The unmanned surface vessel (USV) navigation control system is equipped with embedded computing processing equipment, integrating a generalized predictive algorithm and a PID controller. It receives digital angle values ​​converted from the tipping bucket and rudder angle sensors, and receives the USV's motion attitude angles (pitch angles) output from the inertial navigation system. Roll angle It outputs control signals to the PLC via serial port and outputs I / O signals from the PLC.

[0049] The tilting device is installed inside the tipping bucket and rudder angle equipment, and is driven and pressure-maintaining by a built-in hydraulic cylinder. The control signals for the device are provided by a PLC controller.

[0050] The tipping bucket and rudder angle equipment are equipped with angle sensors. The physical quantities collected by the sensors are converted into digital quantities (actual tipping bucket angle and actual rudder angle) and then sent out via CAN signals.

[0051] Before implementing specific control, it is necessary to conduct a preset model parameter identification test to obtain the servo motor model parameters and the hull's angle model parameters; the specific steps are as follows:

[0052] (1): At different set speeds, continuous excitation tests were conducted on the tipping angle actuator and rudder angle actuator of the unmanned surface vessel, and control input signals, actual values ​​of actuator angles, and data on hull pitch and roll angles were collected simultaneously.

[0053] (2): Based on the collected data, the first-order inertial link models of the tipping angle and rudder angle actuators were fitted using the system identification method to obtain the servo motor model parameters;

[0054] (3): Based on the collected data, the second-order turning angle models of the pitch angle versus the tipping angle and the roll angle versus the rudder angle were fitted using the system identification method to obtain the turning angle model parameters of the hull;

[0055] (4): Discretize the servo model and the turning angle model into a state space form.

[0056] In this embodiment, the unmanned surface vessel's speed is divided into a medium-speed range (8 knots) and a high-speed range (16 knots). The tilt angle is continuously rotated within the range of -35° to 35°, and the rudder angle is continuously rotated within the range of -30° to 30°. Data is collected at different speeds when the tilt angle and rudder angle rotate independently, with the data collection time set to 100 seconds. The recorded data includes the tilt control quantity, the actual tilt angle value, the pitch angle, and the speed corresponding to the collection time; and the rudder angle control quantity, the actual rudder angle value, the roll angle, and the speed corresponding to the collection time. Since speed has a strong correlation with navigation attitude, this invention uses the same model but different parameters for both medium-speed and high-speed navigation.

[0057] Identify the transfer functions of the servo motor model and the hull rotation model within the system based on the recorded input and output data:

[0058] Considering the characteristics of the equipment within the system and the inertia and hysteresis of the hydraulic transmission, the transfer function of the servo motor model within the system adopts a first-order inertial element system identification (in the form of...). This model describes the dynamic response characteristics of a hydraulic lifting device.

[0059] Considering the practical environment and power system design characteristics of unmanned surface vessels, the transfer function of the rotation model within the system is identified using a second-order nomoto model (in the form of...). If converted into a second-order inertial link system, it takes the form of: This model describes the dynamic response of the hull's pitch and roll angles to changes in the nozzle angle. The second-order model, compared to the first-order model, more accurately describes the ship's dynamic characteristics and incorporates the ship's inertia and damping effects during motion.

[0060] The specific identification process is as follows:

[0061] The collected tipping angle control value As input, the actual value of the tipping angle will be collected. As output, identify the system transfer function of the tilting device corresponding to the tilting angle, that is, the servo motor model corresponding to the tilting angle;

[0062] The actual value of the collected tipping angle As input, the collected pitch angle As output, identify the transfer function of the hull attitude angle rotation model for the pitch angle, that is, the rotation model corresponding to the pitch angle;

[0063] The collected rudder angle control values As input, the actual value of the rudder angle collected will be used. As output, identify the system transfer function of the lifting device corresponding to the rudder angle, that is, the servo model corresponding to the rudder angle;

[0064] The actual value of the rudder angle collected As input, the collected roll angle As output, the transfer function of the hull attitude angle rotation model for the roll angle is identified, that is, the rotation model corresponding to the roll angle.

[0065] The servo model and the steering angle model have the same state-space model form, the difference lies in the parameters of the discretized transfer function. The general form of the state-space model is shown below:

[0066]

[0067] In the formula, yes The state vector at a given time represents the internal state of the system at that time, which is the actual value of the pitch angle or roll angle. yes The input vector at any given time represents the external control input to the system, which is the control quantity of the tilting angle or rudder angle. yes The output vector at time t represents the measurable output of the system at that time, which is the predicted pitch angle or the predicted roll angle. It is the state transition matrix, which describes how the system state changes over time; It is the input matrix, which describes the effect of control input on the system state; It is the output matrix, which describes the relationship between the system state and the system output; It is a direct transfer matrix, describing the direct impact of control inputs on system outputs. This invention assumes... This means that the control input is considered to have no direct impact on the system output. , , The parameters are calculated based on the transfer function of the hull attitude angle rotation model. For example, the reference transfer function.

[0068] ,but A = [ 0 1 − c 0 c 2 − c 1 c 2 ] , B = [ 0 1 c 2 ] , C = [ d 0 0 ] .

[0069] Based on the obtained servo motor model and hull angle model, the method for controlling the tilting device suitable for stabilizing the navigation attitude of small unmanned surface vessels includes the following steps:

[0070] Step 1: Real-time acquisition of the current pitch angle, roll angle, tipping angle, and rudder angle of the unmanned surface vessel (USV); real-time acquisition of the current pitch angle and roll angle of the USV through inertial navigation equipment; real-time acquisition of the current actual values ​​of tipping angle and rudder angle through angle sensors.

[0071] Step 2: Based on the current attitude angle, the target attitude angle, and the aforementioned rotation model, use a generalized prediction algorithm to predict the attitude angle change trend over a future period of time and generate preliminary angle control quantities.

[0072] The generalized prediction algorithm constructs an objective function using an output error term and a control input variation term. The output error term ensures that the predicted output of the system is as close as possible to the desired output, guaranteeing control accuracy. The control input variation term limits the magnitude of changes in the control input, preventing excessively drastic changes and ensuring system stability and smoothness. The objective function is shown below:

[0073] J = ∑ i = 1 P [ y ^ ( k + i | k ) − w ( k + i ) ] 2 + ∑ j = 1 M Lambda j Delta u ( k + j − 1 ) 2

[0074] In the formula Indicates at time Predicted future moments The system output; Indicates a future moment The expected output is the expected pitch angle or the expected roll angle; Indicates a future moment The amount of change in the control input; The weighting coefficient represents the amount of change in the control input, and is used to adjust the penalty for changes in the control input. This indicates the prediction time domain, representing the number of future time points in the prediction output. This represents the control time domain, indicating how many future time intervals the control input changes will be optimized.

[0075] The generalized prediction algorithm estimates and predicts the future system output based on the current system state and future control inputs. The formula describing the calculation of this predicted output is as follows:

[0076]

[0077] In the formula Indicates future time The free response, that is, the system output when future control inputs are not considered and only the current state and historical control inputs are considered; Represents a dynamic matrix The elements describe the impact of future control inputs on the system output; Indicates future time The amount of change in the control input.

[0078] Generalized prediction algorithms minimize the objective function Obtain the future change in control input To achieve the goal of making the output of the generalized prediction algorithm and the output of the driving system as close as possible to the desired value, the optimal control input calculation formula is as follows:

[0079]

[0080] In the formula This represents a dynamic matrix that describes the impact of future control inputs on the system output. This represents the control weighting matrix, which is a diagonal matrix in this method, with elements of... ; The desired output vector contains the future. Expected output at each moment; For the free response vector, which includes the future... Free response at any moment.

[0081] The optimal control input described above is specifically solved by solving the Diophantine equation, calculating the free response, constructing a matrix summation, and performing rolling optimization.

[0082] Step 2.1: Initialize the input parameters of the generalized prediction algorithm. This specifically includes the prediction time domain. Control time domain Total number of loop steps softening factor Control the weighting coefficients Initial values ​​of the state vector for the angle rotation model (pitch angle rotation model or roll angle rotation model) and the initial values ​​of the state vector of the hydraulic rotation model (the servo model corresponding to the tipping angle or the servo model corresponding to the rudder angle). Control input history State transition matrix Discretized state-space parameters Control input matrix Discretized state-space parameters Output matrix Discretized state-space parameters and expected angle value Enter the upper and lower limit values. Output limit value Feedforward value of the tipping angle rotation model Feedforward value of rudder angle rotation model ;

[0083] Step 2.2: Based on the matrix Time domain Number of loop steps Solve for the Diophantine matrix and obtain the calculation results. and This result is used to describe the dynamic characteristics of the system.

[0084] Step 2.3: Based on the initial values ​​of the state vector , and Calculate the free response term Predicting the future The system output at each moment;

[0085] Step 2.4: Based on the time domain Time domain Diophantine matrix calculation results ,matrix , , Calculate matrix This describes the effect of control inputs on system outputs. The matrix elements... The calculation is as follows:

[0086] { G n , j = ∑ k = 0 Length ( E n − 1 ) − 1 E n − 1 [ k ] × ( CA k + d − 1 B ) 0 , 0 j ≤ n + 1 G n , j = 0 j > n + 1

[0087] In the formula The delay step is tentatively set to 1 in this embodiment;

[0088] Step 2.5: Based on the control weighting coefficient Construct a diagonal matrix Set the control weighting coefficient and adjust the change in control input;

[0089] Step 2.6: Based on the softening factor and expectations Calculate the expected output The specific calculations are as follows:

[0090] ;

[0091] Step 2.7: Rolling optimization, solving for the future The optimal control input change at each time step That is, minimizing the objective function to obtain the optimal change in control input;

[0092] Step 2.8: [The text appears to be incomplete and contains several grammatical errors. A more accurate translation would require Iteratively add to the current control input, update the control input to obtain the initial angle control quantity. .

[0093] Step 3: Based on the initial angle control quantity, the angle fine-tuning control quantity is calculated by the PID controller;

[0094] Specifically, the state vector and output matrix As input, with the current Expectations at all times The difference is then used as the PID error term. :

[0095]

[0096] Based on the PID proportional term coefficient Integral term coefficient Differential coefficients The angle fine-tuning control quantity is calculated using a PID controller. The specific calculations are as follows:

[0097]

[0098] Step 4: Superimpose the initial angle control amount, the angle fine-tuning control amount, and the angle decoupling feedforward amount used to counteract the coupling effect of pitch and roll motion to obtain the comprehensive control command;

[0099] Specifically, the generalized prediction angle control quantity With PID angle fine-tuning control quantity and angle decoupling feedforward quantity (Tilting Angle Feedforward Value) or rudder angle feedforward value The superimposed commands are used as a comprehensive control instruction, and the specific calculation is as follows:

[0100]

[0101] Step 5: Combine the integrated control command with the current actuator feedback value and calculate the final angle control value through the corresponding servo model; specifically, input the integrated control command and the current actual values ​​of the tilting angle and rudder angle into the corresponding servo model for dynamic compensation calculation, and output the compensated final angle control value.

[0102] The function is transferred through the hydraulic rotation system, and controlled by the integrated control commands. Rudder angle or tipping angle collected values ( or Calculate the target value Reference transfer function Similar to the state-space model of the angular rotation model, the transfer function parameters of the hydraulic rotation system are identified. , , , The formula for calculating the target output value of the servo model is as follows:

[0103]

[0104] Output target value for servo model As the final angle control quantity Update the system to proceed to the next calculation cycle.

[0105] Step 6: Use the final angle control quantity to control the tilting device to drive the tipping bucket and the servo actuator to move, adjust the spray nozzle angle, and perform closed-loop correction based on feedback information.

[0106] Specifically, based on the final angle control amount The PLC control signal is calculated and output to the PLC controller via serial port. The PLC controller converts it into I / O signals and outputs them to the tilting device. The tilting device drives the tilting bucket and the servo actuator to move, adjusting the spray nozzle angle and thus controlling the hull attitude. The attitude angle and actuator angle are detected in real time and the information is fed back to the control system to form a closed-loop correction and rolling optimization.

[0107] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method for controlling a tilting device to stabilize the attitude of a small unmanned surface vessel, characterized in that: Includes the following steps: Step 1: Real-time acquisition of the current pitch angle, roll angle, tipping angle, and rudder angle of the unmanned surface vessel; Step 2: Based on the current attitude angle, target attitude angle, and rotation angle model, use a generalized prediction algorithm to predict the attitude angle change trend over a future period of time and generate preliminary angle control quantities; the rotation angle model represents the dynamic response of the hull's pitch angle and roll angle to changes in the nozzle angle. Step 3: Based on the initial angle control quantity, the angle fine-tuning control quantity is calculated by the PID controller; Step 4: Superimpose the initial angle control amount, the angle fine-tuning control amount, and the angle decoupling feedforward amount used to counteract the coupling effect of pitch and roll motion to obtain the comprehensive control command; Step 5: Combine the integrated control command with the actual values ​​of the current tilting angle and rudder angle, perform dynamic compensation calculation through the corresponding servo model, and output the final angle control quantity after compensation; the servo model represents the dynamic response characteristics of the tilting device; Step 6: Use the final angle control quantity to control the tilting device to drive the tipping bucket and the servo actuator to move, adjust the spray nozzle angle, and perform closed-loop correction based on feedback information.

2. The method for controlling the tilting device for stabilizing the navigation attitude of a small unmanned surface vessel according to claim 1, characterized in that: The servo motor model uses a first-order inertial element to describe the dynamic response characteristics of the hydraulic tilting device; the turning angle model uses a second-order inertial element to describe the dynamic response of the hull attitude angle to changes in the nozzle angle.

3. The method for controlling the tilting device for stabilizing the navigation attitude of a small unmanned surface vessel according to claim 1 or 2, characterized in that: The turning angle model and the servo motor model obtain model parameters through a pre-designed model parameter identification experiment: time-domain data of the tipping angle, rudder angle, pitch angle, and roll angle are collected at different speeds of the unmanned surface vessel (USV); based on the time-domain data, the first-order inertial link servo motor model parameters describing the dynamics of the USV's actuators and the second-order turning angle model parameters describing the USV's attitude response are identified; and the models are discretized into a state-space form to obtain the system matrix.

4. The method for controlling the tilting device for stabilizing the navigation attitude of a small unmanned surface vessel according to claim 3, characterized in that: Model parameter identification includes the following steps: (1) At different set speeds, continuous excitation tests were conducted on the tipping angle actuator and rudder angle actuator of the unmanned surface vessel, and control input signals, actual values ​​of actuator angles, and data on hull pitch and roll angles were collected simultaneously. (2) Based on the collected data, the first-order inertial link models of the tipping angle and rudder angle actuators are fitted respectively using the system identification method to obtain the servo motor model parameters; (3) Based on the collected data, the second-order turning angle models of the pitch angle versus the tipping angle and the roll angle versus the rudder angle are fitted respectively using the system identification method to obtain the turning angle model parameters of the hull; (4) Discretize the servo model and the turning angle model into a state space form.

5. The method for controlling the tilting device for stabilizing the navigation attitude of a small unmanned surface vessel according to claim 3, characterized in that: Model parameter identification in progress: The collected tipping angle control value As input, the actual value of the tipping angle will be collected. As output, the system transfer function of the tilting device corresponding to the tilting angle is identified, and the servo motor model parameters corresponding to the tilting angle are obtained. The actual value of the collected tipping angle As input, the collected pitch angle As output, the transfer function of the hull attitude angle rotation model is identified to obtain the rotation model parameters corresponding to the pitch angle. The collected rudder angle control values As input, the actual value of the rudder angle collected will be used. As output, the system transfer function of the lifting device corresponding to the rudder angle is identified, and the servo motor model parameters corresponding to the rudder angle are obtained. The actual value of the rudder angle collected As input, the collected roll angle As output, the transfer function of the hull attitude angle rotation model is identified to obtain the rotation model parameters corresponding to the roll angle.

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