Unmanned surface vehicle self-disturbance rejection control method based on fusion of propeller hydrodynamic

Abstract

The self-disturbance control method of unmanned surface vehicle with propeller power firstly establishes the dynamics model of unmanned surface vehicle, then analyzes the force model of unmanned surface vehicle, estimates the force and torque of wind and wave, current disturbance, real-time feedback of the motion state change of unmanned surface vehicle, and uses the extended state observer to observe the unmodeled part and uncertainty part in real time. Based on the self-disturbance control method, the control law is designed, and the wind and wave disturbance and the change of the center of gravity are added in the propeller control law. When encountering external environmental disturbance and uncertainty disturbance, it can compensate in time to realize stable navigation. Compared with the existing attitude control scheme, the navigation control performance of unmanned surface vehicle can be improved, which is more suitable for actual navigation process.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of unmanned surface vehicle motion control, more particularly to an unmanned surface vehicle self-disturbance rejection control method fusing propeller hydrodynamic force. BACKGROUND

[0002] The unmanned surface vehicle is a kind of water surface robot based on multi-functional and high-performance design for task purposes, which has small volume, low cost and strong maneuverability, so that the unmanned surface vehicle plays a huge role in military and civilian fields. However, due to the high coupling degree, nonlinearity, instability and parameter uncertainty of the motion control of the unmanned surface vehicle, it is often difficult to achieve the expected control target in the actual navigation process.

[0003] In order to meet the navigation task requirements of the unmanned surface vehicle, high-precision attitude control is essential. However, the unmanned surface vehicle will encounter various uncertain external factor disturbances in the actual navigation process, resulting in inaccurate tracking, so that high-precision attitude control of the unmanned surface vehicle cannot be achieved, and even the normal navigation is affected. For example, wind and wave disturbances have a certain influence on the heading angle, roll angle and position of the unmanned surface vehicle, resulting in a deviation between the actual navigation attitude angle and the expected attitude angle. In order to improve the stability performance of the unmanned surface vehicle control, various control schemes have been proposed, including sliding mode control, backstepping, self-disturbance rejection and other control schemes. However, the traditional control scheme is also difficult to achieve the required control performance. Therefore, in the motion control of the unmanned surface vehicle, the disturbance part needs to be estimated and compensated in real time.

[0004] In order to solve the above problems, the prior art is as follows:

[0005] Publication No.: CN113900372A, Application Name: An unmanned surface vehicle course keeping method based on neural network self-disturbance rejection control, the application discloses an unmanned surface vehicle course keeping method based on neural network self-disturbance rejection control, which comprises the following steps: step A: positioning the ship body direction and the ship head direction of the unmanned surface vehicle through the gyro compass to determine the actual course of the unmanned surface vehicle; step B: judging whether there is a course deviation angle according to the preset course and the actual course of the unmanned surface vehicle, if yes, inputting the course deviation angle into the neural network self-disturbance rejection controller; step C: adjusting the speed of the left and right motors of the unmanned surface vehicle through the neural network self-disturbance rejection controller, and adjusting the direction of the propeller through the left and right motors of the unmanned surface vehicle, so as to keep the course of the unmanned surface vehicle. The present application can detect the actual course of the unmanned surface vehicle in real time and compare it with the set course, then adjust the speed of the left and right motors to realize angle control, so as to keep the course of the unmanned surface vehicle from deviating due to the external force of the water surface, thereby avoiding the problem of increasing the travel distance and travel time caused by the re-planning of the route.

[0006] The scheme adopted is that the deviation angle between the preset heading of the unmanned ship and the actual heading is input into the neural network active disturbance rejection controller, the speed of the left and right motors of the unmanned ship is regulated through the neural network active disturbance rejection controller, and the orientation of the propeller is adjusted through the left and right motors of the unmanned ship.

[0007] The application discloses a DC motor propelling unmanned water surface ship speed controller design method, and has the following steps: S1, a DC motor model for propelling an unmanned water surface ship, a propeller model of the unmanned water surface ship and a forward speed model of the unmanned water surface ship are established; S2, a DC motor propelling unmanned water surface ship model is established according to the models in step S1; S3, a neural network-based speed identifier and a speed identifier are used to approximate the uncertain terms of the DC motor propelling unmanned water surface ship model; S4, the uncertain term information is obtained from the speed identifier and the speed identifier, and a dynamic surface control design method is used to design a DC motor propelling unmanned water surface ship speed controller. Compared with existing unmanned water surface ship speed controllers, the application uses a neural network-based identifier to approximate the uncertainty in the DC motor, the propeller and the speed dynamics of the unmanned ship, effectively improving the dynamic response speed of the unmanned water surface ship speed control system.

[0008] The scheme adopted is that according to the uncertain terms of the DC motor propelling unmanned water surface ship model, a neural network-based speed identifier and a speed identifier are used to approximate the uncertain terms, and a dynamic surface control design method is used to design a DC motor propelling unmanned water surface ship speed controller. The scheme adopted by us is to observe the unmodeled part of the unmanned ship and the uncertain disturbance by using the extended state observer ESO, and to compensate to the input end in real time, and to input the deviation, differential deviation and deviation of the center of gravity of the heading angle and the roll angle of the unmanned ship into the active disturbance rejection controller. For the disturbance of wind and current, a propeller hydrodynamic model control law is established to control the thrust output of the left and right propellers and adjust the deviation of the heading angle and the roll angle.

[0009] The water surface unmanned ship often receives the uncertainty of self parameters and the uncertainty of external environment interference during navigation, therefore, in order to improve the control performance of the unmanned ship and the safety coefficient of navigation, the real-time estimation and compensation of the uncertainty of self parameters and the uncertainty of external environment interference of the unmanned ship need to be solved. The application is improved on the basis of the self-disturbance control method, the unmodeled part and the uncertain part are observed in real time by using the extended state observer, the deviation change of the gravity center, the attitude angle and the attitude angle differential is added to the input end of the self-disturbance control law, the heading angle can be adjusted in real time under the flow interference environment, the roll angle can be tracked in real time under the wind and wave interference, the disturbance is compensated in real time, the state model of the thrust size of the control output propeller overcomes the fluid power and the wind and wave interference, and it is ensured that the unmanned ship can work safely and stably on the water surface. SUMMARY

[0010] To solve the above technical problems, the application provides a self-disturbance control method for unmanned ship integrating propeller hydrodynamics, which is improved on the basis of the self-disturbance control method, so that the water surface unmanned ship can maintain the stability of the attitude angle under the interference of external environment wind, wave and flow, the water flow acting force of the unmanned ship is analyzed, the attitude angle deviation is corrected in real time, the thrust size of the control propeller is designed, and the unmanned ship can adapt to the complex water surface environment.

[0011] To achieve the above object, the technical scheme adopted by the application is:

[0012] The application provides a self-disturbance control method for unmanned ship integrating propeller hydrodynamics, and specifically includes the following steps:

[0013] 1) establishing a dynamic model of the water surface unmanned ship;

[0014] The step 1) of establishing the dynamic model of the water surface unmanned ship specifically includes the following process:

[0015] The underactuated unmanned ship includes six degrees of freedom motion, three directions of translation and three directions of rotation, in the actual situation, because the motion of the ship body is carried out on the water surface, the heaving and pitching motion states can be ignored in the kinematic analysis of the water surface unmanned ship, and only the motion states of the four degrees of freedom water surface unmanned ship in surge, sway, roll and yaw are considered, and the dynamic model of the four degrees of freedom underactuated water surface unmanned ship is established as follows:

[0016]

[0017] Wherein, (x, y) is a position vector, u r and v r are the surge speed and sway speed of the unmanned ship relative to the wind, wave and flow, φ is the roll angle, ψ is the heading angle, p is the roll angular velocity, r is the yaw angular velocity, τ u is the longitudinal thrust, τr For the yaw moment, τ w = [τ wu (t) τ wv (t) τ wp (t) τ wr (t)] T For the external environmental disturbance force and moment on the unmanned surface vehicle;

[0018] M is the system inertia matrix, expressed as:

[0019]

[0020] C(y r ) is the Coriolis centripetal force matrix, expressed as:

[0021]

[0022] D(ν r ) is the hydrodynamic damping matrix, expressed as:

[0023]

[0024] 2) Design the attitude tracking active disturbance rejection control law of the unmanned surface vehicle;

[0025] The specific process of designing the attitude tracking active disturbance rejection control law of the unmanned surface vehicle in step 2) is as follows:

[0026] 3.1 Given the desired attitude angle θ d = [φ d ψ d ] T , the attitude angle differential The initial center of gravity position is located at the origin O of the coordinate system, represented as The actual attitude angles φ, ψ of the unmanned surface vehicle satisfy the conditions φ min ≤ φ ≤ φ ma , ψ min ≤ ψ ≤ ψ max , and the attitude angle of the unmanned surface vehicle clockwise around the coordinate axis is positive, and the attitude angle counterclockwise is negative. The actual attitude angle differential is obtained by the extended state observer ESO;

[0027] 3.2 Compare the deviations between the desired values and actual values of the attitude angle, attitude angle differential, and center of gravity coordinates, and the error equation is expressed as:

[0028] e θ = θ d - θ

[0029] e ω = θ ω - θ

[0030]

[0031]

[0032] 3.3k1 is the attitude angle error coefficient, k2 is the attitude angle differential error coefficient, k3 is the centroid horizontal coordinate error coefficient, and k4 is the centroid vertical coordinate error coefficient. The designed active disturbance rejection control law output u is:

[0033] u=k1e θ +k2e ω +k3e x +k4e y

[0034] 3.4 The Extended State Observer (ESO) observes the disturbances of internal uncertainties and external unmodeled parts, denoted as... Real-time compensation is applied to the input for control, thus the final output of the active disturbance rejection control method is... The function satisfies a linear function relationship, k b The coefficients are for the disturbance component;

[0035] 3) Design a propulsion model for the propeller of an unmanned surface vessel under the interference of wind, waves and water flow, and adjust the roll angle and heading angle in real time.

[0036] As a further improvement to the present invention, step 3) involves designing the propulsion model of the unmanned surface vessel's propeller under wind, waves, and current interference, and adjusting the roll and heading angles in real time. The specific process is as follows:

[0037] 4.1 The propeller control mechanism of the unmanned surface vessel (USV) is differential control, meaning that autonomous navigation in any direction can be achieved by outputting the thrust of the two propellers. The propeller thrust is related to the fluid density, propeller diameter and speed, advance velocity, and fluid kinematic viscosity. In still water, the thrust is F = K. F ρn 2 D 4 K F ρ is the propeller thrust coefficient, ρ is the density of water in the surrounding aquatic environment, n is the propeller rotational speed, and D is the propeller diameter.

[0038] 4.2 Under the interference of water flow, the actual heading angle of the unmanned surface vessel deviates from the expected heading angle. If ψ d >ψ indicates that the actual heading angle is less than the reference heading angle, and the thrust of the right propeller needs to be increased to adjust the heading. If ψ d <ψ indicates that the actual heading angle is greater than the reference heading angle, requiring an increase in the thrust of the left propeller to adjust the heading. Therefore, a propeller state model capable of real-time adjustment of the heading angle under conditions of water flow interference is designed:

[0039] F wr = K r ρAv c 2 cos(ψ c -ψ)

[0040] where F wr is the force exerted by the propeller to overcome the disturbance of water flow, K r is the flow pressure coefficient, A is the propeller blade force area, v c is the water flow velocity, ψ c is the water flow direction, and ψ is the actual heading angle of the unmanned ship;

[0041] 4.3 Under the disturbance of wind and wave, the change of the roll angle of the unmanned ship is considered, and the expected roll angle φ d = 0 in actual navigation process, when -φ a ≤ φ ≤ φ a , the influence of the small change of the roll angle on the motion state of the unmanned ship is ignored, φ a is the maximum angle that allows the small change of the roll angle of the unmanned ship, if φ > φ a , it indicates that the actual roll angle is greater than the maximum acceptable roll angle, the unmanned ship is right-tilted, and the thrust size of the right propeller needs to be increased according to the amplitude of the right-tilting of the unmanned ship to reach a balanced state, if φ < -φ a , it indicates that the actual roll angle is less than the minimum acceptable roll angle of the unmanned ship, the unmanned ship is left-tilted, and the thrust size of the left propeller needs to be increased according to the amplitude of the left-tilting of the unmanned ship to reach a balanced state, therefore, a propeller state model that can adjust the roll angle in real time under the disturbance of wind and wave is designed:

[0042] F wp = K p ρge -k / n Sφsgn(φ)

[0043] where F is the force exerted by the propeller to overcome the disturbance of wind and wave, K p is the wind and wave force coefficient, k is the correction coefficient of the exponential function, g is the acceleration of gravity, n is the propeller speed, φ is the actual roll angle of the unmanned ship, S is the submerged surface area of the unmanned ship, and sgn(φ) is the sign function, which has the following values:

[0044]

[0045] 4.4 The attitude angle error, attitude differential error, and gravity center offset are added to the input end of the active disturbance rejection control law, which better evaluates whether the system reaches a steady state, and the output u0 is further input to the control law of the propeller model, which better realizes the control of the motion state of the unmanned ship. The functional relationship between the active disturbance rejection output u0 and the propeller thrust size F0 is established as follows:

[0046]

[0047] Among them, K F Where n is the propeller thrust coefficient, n is the propeller rotational speed, and D is the propeller diameter;

[0048] 4.5 Based on active disturbance rejection control, water flow disturbance and wind and wave disturbance are incorporated into the propeller model control law:

[0049]

[0050] Among them, F L F represents the thrust of the left propeller. R This refers to the size of the right propeller.

[0051] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0052] Changes in the center of gravity of an unmanned surface vessel (USV) affect its motion. Incorporating these changes into the USV's attitude active disturbance rejection law, and observing unmodeled and uncertain disturbances through an extended state observer, allows for a better reflection of the USV's motion. Furthermore, this invention determines the magnitude of the USV's propeller thrust under wind, waves, and current disturbances using a propeller hydrodynamic control model. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the coordinate system for modeling an unmanned surface vessel;

[0054] Figure 2 This is a diagram showing the overall structure of the attitude control method for unmanned surface vessels. Detailed Implementation

[0055] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0056] like Figure 1 As shown, the underactuated unmanned surface vessel (USV) contains six degrees of freedom of motion: translation in three directions and rotation in three directions. In reality, since the hull's motion occurs on the water surface, the pitching and heave motions can be ignored in the kinematic analysis of the USV, and only the pitching, swaying, rolling, and bowing motions of the four-degree-of-freedom USV should be considered. The dynamic model of the four-degree-of-freedom underactuated USV is established as follows:

[0057]

[0058] Where (x, y) is the position vector, u r and v rare the surge and sway velocities of the USV relative to the wave and current, respectively, φ is the roll angle, ψ is the heading angle, p is the roll angular velocity, r is the yaw angular velocity, τ u is the longitudinal thrust, τ r is the yaw moment, τ w = [τ wu (t) τ wv (t) τ wp (t) τ wr (t)] T are the external environmental disturbance forces and moments acting on the USV.

[0059] M is the system inertia matrix, and its expression is:

[0060]

[0061] C(v r ) is the Coriolis centripetal force matrix, and its expression is:

[0062]

[0063] D(v r ) is the hydrodynamic damping matrix, and its expression is:

[0064]

[0065] As Figure 2 shown in the overall structure diagram of the surface USV attitude control method, it includes the active disturbance rejection control law integrated with the attitude angle, attitude angle differential, and gravity center deviation change, and the propeller model control law integrated with the wind wave disturbance, current disturbance, and active disturbance rejection output. The output expression of the active disturbance rejection control law is:

[0066] u = k1e θ + k2e ω + k3e x + k4e y

[0067] wherein k1 is the attitude angle error coefficient, k2 is the attitude angle differential error coefficient, k3 is the gravity center horizontal coordinate error coefficient, k4 is the gravity center longitudinal coordinate error coefficient, e θ is the attitude angle error, e ω is the angular velocity error, e x is the horizontal coordinate error of the gravity center, and e y is the longitudinal coordinate error of the gravity center.

[0068] The extended state observer ESO observes the disturbance of the internal uncertainty and external unmodeled part, denoted as which is compensated to the input end in real time for control, so that the final output of the active disturbance rejection control method is The function satisfies a linear function relationship, kb The disturbance part coefficient is added.

[0069] The attitude angle error, the attitude differential error and the gravity center offset are added to the input end by the active disturbance rejection control law, so that whether the system reaches the steady state can be better evaluated, the output u0 is further input to the control law of the propeller model, so that the control of the unmanned ship motion state can be better realized. On the basis of the active disturbance rejection control, the water flow disturbance and the wind wave interference are added to the control law of the propeller model:

[0070]

[0071] Wherein, F L is the left propeller thrust size, F R is the right propeller size, K r is the flow pressure coefficient, A is the propeller blade force area, v c is the water flow velocity, ψ c is the water flow direction, ψ is the actual heading angle of the unmanned ship, K F is the propeller thrust coefficient, n1 is the left propeller speed, n2 is the right propeller speed, D is the propeller diameter, K p is the wind wave force coefficient, k is the index function correction coefficient, g is the gravity acceleration, φ is the actual roll angle of the unmanned ship, S is the water surface area of the unmanned ship, sgn (φ) is the sign function, and the value is as follows:

[0072]

[0073] The above is only the preferred embodiment of the present application, and does not limit the present application in any other form, and any modification or equivalent change according to the technical essence of the present application still belongs to the scope of the present application.

Claims

1. A method for active disturbance rejection control of unmanned surface vessels integrating propeller hydrodynamics, characterized in that: Specifically, the following steps are included: 1) Establish a dynamic model of the unmanned surface vessel; Step 1) involves establishing the dynamic model of the unmanned surface vessel, and the specific process is as follows: The underactuated unmanned surface vessel (USV) comprises six degrees of freedom of motion: translation in three directions and rotation in three directions. In practice, since the hull's motion occurs on the water surface, the pitch and heave motions can be ignored in the kinematic analysis of the USV, and only the pitch, sway, roll, and bow motions of the four-degree-of-freedom USV should be considered. The dynamic model of the four-degree-of-freedom underactuated USV is established as follows: ； in, For position vectors, and These represent the pitching and swaying velocities of the unmanned surface vessel relative to wind, waves, and currents, respectively. The roll angle, For heading angle, The angular velocity of the roll is... The bow roll angular velocity, For longitudinal thrust, For the turning torque, The forces and moments exerted by external environmental disturbances on the unmanned surface vessel; The system inertia matrix is ​​expressed as: ； The Coriolis centripetal force matrix is ​​expressed as: ； The hydrodynamic damping matrix is ​​expressed as follows: ； 2) Design an active disturbance rejection control law for attitude tracking of unmanned surface vessels; Step 2) describes the design of the active disturbance rejection control law for attitude tracking of the unmanned surface vessel. The specific process is as follows: 2.1 Given the desired attitude angle attitude angle differential The initial centroid is located at the origin of the coordinate system. , represented as Actual attitude angle of unmanned surface vessel , Meet the conditions , Furthermore, the attitude angles of the unmanned surface vessel rotating clockwise around the coordinate axis are positive, and the attitude angles rotating counterclockwise are negative. The differential of the actual attitude angles... This is obtained from the extended state observer ESO; 2.2 Compare the deviations between the expected and actual values ​​of the attitude angle, attitude angle derivative, and centroid coordinates. The error equation is expressed as follows: ； 2.3 This is the attitude angle error coefficient. The differential error coefficient of the attitude angle. The error coefficient for the abscissa of the centroid. Design an active disturbance rejection control law output to represent the error coefficient of the centroid's ordinate. for: ； 2.4 The Extended State Observer (ESO) observes the disturbances of internal uncertainties and external unmodeled parts, denoted as... The real-time compensation is sent to the input for control, so that the final output of the active disturbance rejection control method is... The function satisfies a linear function relationship. The coefficients are for the disturbance component; 3) Design a propulsion model for the propeller of an unmanned surface vessel under the interference of wind, waves and water flow, and adjust the roll angle and heading angle in real time.

2. The method for active disturbance rejection control of unmanned surface vessels integrating propeller hydrodynamics according to claim 1, characterized in that: Step 3) describes the propulsion model of the unmanned surface vessel's propeller under wind, waves, and current interference, and adjusts the roll and heading angles in real time. The specific process is as follows: 3.1 The unmanned surface vessel's (USV) propeller control is differential control, meaning that autonomous navigation in any direction can be achieved by adjusting the thrust of the two propellers. The propeller thrust is related to fluid density, propeller diameter and speed, advance velocity, and fluid kinematic viscosity. In still water, the thrust... , This is the propeller thrust coefficient. The density of water in the surrounding aquatic environment. The rotational speed of the propeller. The diameter of the propeller; 3.2 Under the interference of water flow, the actual heading angle of the unmanned surface vessel deviates from the expected heading angle. If This indicates that the actual heading angle is smaller than the reference heading angle, and the thrust of the right propeller needs to be increased to adjust the heading. This indicates that the actual heading angle is greater than the reference heading angle, requiring an increase in the thrust of the left propeller to adjust the heading. Therefore, a propeller state model capable of real-time adjustment of the heading angle under conditions of water flow interference is designed: ； in, The force applied to the propeller to overcome water flow disturbance, The flow pressure coefficient, The area of ​​the propeller blade under stress. For water flow velocity, For the direction of water flow, This is the actual heading angle of the unmanned surface vessel; 3.3 Under wind and wave disturbances, consider the change in the roll angle of the unmanned surface vessel (USV), while the expected roll angle of the USV during actual navigation is... ,when At that time, the effect of minute changes in the roll angle on the motion state of the unmanned surface vessel is ignored. The maximum angle that allows for a small change in the roll angle of the unmanned surface vessel, if This indicates that the actual roll angle is greater than the maximum acceptable roll angle, causing the unmanned surface vessel (USV) to tilt to the right. The thrust of the right propeller needs to be increased according to the degree of the right tilt to achieve equilibrium. This indicates that the actual roll angle is less than the minimum acceptable roll angle for the unmanned surface vessel (USV), causing it to tilt to the left. To achieve equilibrium, the thrust of the left propeller needs to be increased based on the extent of the left tilt. Therefore, a propeller state model capable of real-time adjustment of the roll angle under wind and wave interference is designed. ； in, The force applied to the propeller to overcome the disturbance of wind and waves, This is the coefficient of wind and wave force. For the correction coefficient of the exponential function It is the acceleration due to gravity. The propeller speed, This is the actual roll angle of the unmanned surface vessel. The surface area of ​​the unmanned surface vessel submerged in water. This is a symbolic function, and its values ​​are as follows: ； 3.4 The active disturbance rejection control law incorporates attitude angle error, attitude differential error, and center of gravity offset into the input to better evaluate whether the system has reached steady state, and outputs... Further input into the control law of the propeller model allows for better control of the unmanned surface vessel's motion state. The active disturbance rejection output is established below. With propeller thrust Functional relationship between them: ； in, This is the propeller thrust coefficient. The rotational speed of the propeller. The diameter of the propeller; 4.5 Based on active disturbance rejection control, water flow disturbance and wind and wave disturbance are incorporated into the propeller model control law: ； in, This refers to the thrust of the left propeller. This refers to the size of the right propeller.

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