A method for controlling the motion of a near-surface vehicle in high sea states

Abstract

A high sea state near-surface vehicle motion control calculation method, according to the application scene of near-surface vehicle, through the association of hydrodynamic force and navigation depth, the motion model under the condition of parameter perturbation is established; in order to improve the response speed and robustness of the actuator, the expert control-improved S surface algorithm is proposed, so as to accurately describe the motion model of this kind of vehicle, improve the motion prediction accuracy of this kind of vehicle and reduce the motion amplitude.

Description

Technical Field

[0001] This invention relates to the field of motion control for near-surface vehicles, and particularly to a calculation method for motion control of near-surface vehicles under high sea states. Background Technology

[0002] Near-surface vehicles (NSVs) operate at depths between surface vehicles (such as ships) and submersibles (such as AUVs). They use fin-rudder control to change their depth, mitigating wave impact, and maintain real-time communication with shore-based facilities and the mother ship via their above-water masts. The structural characteristics and application scenarios of NSVs dictate significant draft changes during submersion and surfacing transitions. These substantial draft variations alter hydrodynamic performance and rudder effectiveness, limiting the application of motion models for both surface and submersible vehicles. Furthermore, NSVs are still affected by waves in high sea states, experiencing heave and pitch, impacting navigation safety. Currently, surface vehicles, with sufficient reserve buoyancy, do not require vertical plane control mechanisms; their motion control focuses on horizontal heading or track tracking. Submersibles, operating at greater depths, are less affected by surface waves and do not experience draft changes. Therefore, there is a pressing need to develop a computational method for motion models and navigation stability control of NSVs in high sea states, improving motion prediction accuracy and reducing motion amplitude.

[0003] The mathematical models used to describe near-surface motion of the papers "Research on Hydrodynamic Characteristics of Twin-Tail Semi-Submersible Unmanned Surface Vessels," "Research on Near-Free Surface Maneuverability of Twin-Tail Semi-Submersible Unmanned Surface Vessels," and "Research on Motion Characteristics of Semi-Submersible Vehicles" do not consider the perturbation of vehicle parameters and wave effects under the influence of the free surface. The paper "Free-running tests on a self-propelled submersible multi-state vehicle model" proposes that the free surface affects the rudder effectiveness of near-surface vehicles but does not establish a corresponding mathematical model to describe this. The paper "Analysis of the Influence of Diving Depth on the Added Mass of Semi-Submersible Vehicles" discusses the influence of diving depth on the added mass of near-surface vehicles but does not establish a motion model under wave interference.

[0004] The control algorithms used in the papers "Wave Resistance Analysis of Scaled-Down Model of Semi-Submersible Vehicle Based on PID Control" and "Application of Sliding Mode Variable Structure Control in Underwater Vehicle Steering Gear Control" regarding the solution to the motion control problem of near-surface vehicles do not consider the effects of free surface and waves. Summary of the Invention

[0005] This disclosure provides a motion control calculation method applicable to near-surface vehicles in high sea states, which can accurately establish the motion model of near-surface vehicles and effectively control navigation stability.

[0006] The motion control calculation method for near-surface vehicles in high sea states provided in this disclosure includes the following steps: Step S1: Define the coordinate system with the vehicle's center of mass as the origin. Let the pitch angle be the motion model of the near-surface vehicle.

[0007] In the formula, , , , , , , These are, respectively, the mass attribute matrix, the hydrodynamic coefficient matrix, the front rudder angle coefficient matrix, the rear rudder angle coefficient matrix, the static matrix, the propulsion force matrix, and the wave disturbance force matrix. , For the actuating structures of an aircraft, namely the front and rear rudders, variables , , , , , θ These represent longitudinal velocity, vertical velocity, pitch rate, longitudinal displacement, depth of travel, and pitch angle, respectively. , , , , , These represent longitudinal acceleration, vertical acceleration, pitch acceleration, derivative of longitudinal displacement with respect to time, derivative of depth of travel with respect to time, and pitch velocity, respectively. The coefficient elements in the hydrodynamic coefficient matrix are functions of depth of travel and pitch angle. Step S2: Based on this motion model, the rudder, acting as the actuator, is controlled using an improved S-surface algorithm. The actuator output is:

[0008] in, δ As the rudder angle, k 1. k 2. a Parameters for controlling response speed, k 1, k 2. Adjust according to the actual motion response, with a value range of 1 < k 1<5, 1< k 2<5, 1< a <2, x E For deviation, dx E / dt The rate of change of deviation This is the offset correction amount.

[0009] Furthermore, the hydrodynamic coefficient matrix Calculate according to the following formula:

[0010] In the formula, m is the mass of the spacecraft, and g is the acceleration due to gravity. It has high initial stability. , , Here are the coefficients of the longitudinal fluid force with respect to the longitudinal direction, vertical direction, and vertical rotation. , Let be the coefficient of the vertical fluid force with respect to the vertical direction and vertical rotation. , This is the coefficient of the lateral rotating fluid torque with respect to the vertical direction and vertical rotation.

[0011] Furthermore, the offset correction amount Determined according to the following formula:

[0012] T For time intervals, s This represents the number of iterations required to achieve a stable deviation. e The error between the target quantity and the current state. b The iteration termination time, α This is the gain factor, with a value range of 1 < α <2.

[0013] Furthermore, in step S2, an expert control algorithm combined with an improved S-plane algorithm is used to control the rudder, which serves as the actuator, including: S21: When | x E ( k )|> M At time 1, the feedback results of motion information are transmitted to the actuator for closed-loop control, and the gain coefficient is set. kh,kh ( k ) =kh ( k- 1) + 2 * ( kh ( k- 1)-1) ， coefficients in the improved S-surface control algorithm k 1( k ) =kh ( k ) *k 1(k- 1), k 2 ( k ) =kh ( k ) *k 2( k- 1) The output of the actuator is: in, k、k- 1 represents the current time and the previous time. x E ( k )express k Time deviation, x E ( k- 1) indicates k -1 time deviation express k Rate of change of time deviation A Maximum rudder angle, M 1 represents the specified tolerance level for deviation; S22: When x E ( k ) Δ x E ( k When )>0: (1) | x E ( k )|≥ M 2. Parameters of the actuator k 1( k ), k 2( k Take them as respectively kh ( k )* k 1( k -1), kh ( k )* k 2( k -1), the actuator output is: ; (2) | x E ( k )|< M 2. The output expression of the actuator remains unchanged, that is: ; Where, Δ x E ( k ) = x E ( k ) - xE ( k- 1), M 2 represents the specified tolerance level for deviation. M 2< M 1; S23: Δ x E ( k )=0 x E ( k ) =x E ( k- 1) The executing agency outputs according to strategy (1) in S22; S24: x E ( k )Δ x E ( k )<0, Δ x E ( k ) Δ x E ( k -1)>0 or x E ( k If ) = 0, the output expression of the actuator remains unchanged, that is: ; S25: x E ( k )Δ x E ( k )<0, Δ x E ( k )Δ x E ( k -1)<0: (1) | x E ( k )|≥ M 2, k 1( k )= kh ( k )* k 1( k- 1), k 2= kh ( k )* k 2( k- 1) The output of the actuator is: ; (2) |x E ( k )|< M 2. Set the suppression coefficient kd , k 1( k )= kd * k 1( k- 1), k 2( k )= kd * k 2( k- 1) The output of the actuator is: ; S26:| x E ( k )|≤ e, e To improve the accuracy of the deviation, an integral term is added to reduce the steady-state deviation. ki The integral term parameter needs to be adjusted based on the feedback results. The actuator output is: .

[0014] Furthermore, the gain coefficient ranges from 1 to 2, and the suppression coefficient ranges from 0 to 1.

[0015] The motion control calculation method for near-surface vehicles disclosed herein establishes a more comprehensive motion model by fitting the relationship between hydrodynamic coefficients and navigation depth and attitude, and incorporates expert decision-making into the generation of control strategies, thus obtaining a motion control method for near-surface vehicles applicable to high sea clarity conditions.

[0016] Compared with the prior art, the beneficial effects of this disclosure are: (1) It fully considers the parameter perturbation in the attitude change process of near-surface vehicles, which is more in line with the motion of such vehicles in actual sea conditions, and can be used as a motion simulation calculation method for near-surface vehicles; (2) The expert control-improved S-surface algorithm proposed based on this motion model can improve the wave resistance and steering efficiency of near-surface vehicles, effectively solve the motion prediction of near-surface vehicles and improve the navigation control accuracy; (3) Expert control - The basic expression of the improved S-surface algorithm is simple. It can complete motion control based on the feedback information of the monitoring equipment on the vehicle, and has good practicality and versatility. Attached Figure Description

[0017] The above and other objects, features and advantages of this disclosure will become more apparent from the more detailed description of exemplary embodiments of this disclosure taken in conjunction with the accompanying drawings, in which the same reference numerals generally represent the same components.

[0018] Figure 1 This is a basic structural diagram of a near-surface vehicle. Figure 2 This is a schematic diagram of the control process according to this disclosure; Figure 3 This is a comparison chart of several algorithms. Detailed Implementation

[0019] Preferred embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art.

[0020] This disclosure provides a motion control calculation method for near-surface vehicles under high sea states. Based on the application scenario of near-surface vehicles, a motion model under parameter perturbation is established by associating hydrodynamics with navigation depth. In order to improve the response speed and robustness of the actuators, an expert control-improved S-surface algorithm is proposed, thereby accurately describing the motion model of this type of vehicle, improving the motion prediction accuracy of this type of vehicle, and reducing the motion amplitude.

[0021] An exemplary embodiment includes the following steps: Step 1: As attached Figure 1 As shown, a motion coordinate system G-x1y1z1 is established with the vehicle's center of mass as the origin, and o-x2y2z2 is the geodetic coordinate system. The following definitions are provided. For the pitch angle, the motion model of the near-surface vehicle includes wave interference, and the expression is as follows:

[0022] variable , , , , , These represent longitudinal velocity, vertical velocity, pitch rate, longitudinal displacement, depth of travel, and pitch angle, respectively. , , , , , These represent longitudinal acceleration, vertical acceleration, pitch acceleration, the derivative of longitudinal displacement with respect to time, the derivative of depth with respect to time, and pitch velocity, respectively. , , , , , , These are, respectively, the mass attribute matrix, the hydrodynamic coefficient matrix, the forward rudder angle coefficient matrix, the rear rudder angle coefficient matrix, the static matrix, the propulsion force matrix, and the wave disturbance force matrix. , The actuators of a spacecraft are the front and rear rudders.

[0023] The expressions for each matrix are as follows:

[0024]

[0025]

[0026]

[0027] In the formula, m is the mass of the spacecraft, and g is the acceleration due to gravity. It has high initial stability. For lateral moment of inertia, , , Here are the coefficients of the longitudinal fluid force with respect to the longitudinal direction, vertical direction, and vertical rotation. , Let be the coefficient of the vertical fluid force with respect to the vertical direction and vertical rotation. s are the coefficients of the lateral rotational fluid torque with respect to the vertical direction and vertical rotation. , , , , For each corresponding fluid force acceleration coefficient, , , , , , The coefficients of longitudinal, vertical, and pitching moments generated by the front and rear rudders. , These are the initial vertical force coefficient and the initial pitch coefficient. , , , The parameters are: weight difference, buoyancy, longitudinal position of the center of buoyancy, and vertical position of the center of buoyancy. For thruster thrust, The vertical position of the thruster relative to the center of mass. For fluid density, For the displacement volume of the aircraft, For the frequency of encounters, It is the angular frequency. For wave height, For wave number, For wave angle, Cross-sectional area of ​​the aircraft For the effective wave tilt coefficient, For speed. All the matrices mentioned above, except for the hydrodynamic coefficient matrix, were calculated using existing formulas. The hydrodynamic coefficient is related to the navigation depth. The function, at different sailing depths The hydrodynamic coefficients are expressed in the form of... The expression shows that static force is the depth of navigation. and pitch angle The function, through the form of The expression demonstrates that the hydrodynamic coefficients can be adjusted according to depth during the iterative calculation process. and pitch angle Updated in real time. The coefficient elements in the hydrodynamic coefficient matrix are related to the navigation depth. and pitch angle The relationship can be established by considering different sailing depths. Pitch angle The data was obtained by fitting the test data of the aircraft.

[0028] Step 2: Preferably, the expert control-improved S-surface algorithm proposed in this disclosure is used to control the rudder, which serves as the actuator. This algorithm combines the expert control algorithm with the improved S-surface algorithm, incorporating deviation and deviation change rate into the improved S-surface algorithm, and using expert rules to further optimize the improved S-surface algorithm.

[0029] The basic expression of the improved S-surface algorithm is as follows: k 1. k 2. a The parameter used to control the response speed, 1 < a <2, x E For deviation, dx E / dt The rate of change of deviation The offset correction amount is expressed as follows:

[0030] t The total iteration time. T For time intervals, s This represents the number of iterations required to achieve a stable deviation. eLet b be the error between the target value and the current state, and b be the iteration termination time. α This is the gain factor, with a value range of 1 < α <2.

[0031] The improved S-surface algorithm, incorporating expert control, specifically includes the following: 1) | x E ( k )|> M 1. At this point, the vehicle's deviation from the designated target is significant, requiring an increase in control input to quickly adjust the deviation. To avoid excessive overshoot and an overly rapid system response, the motion feedback information still needs to be transmitted to the actuator in this situation, achieving closed-loop control based on traditional open-loop control. Gain coefficient kh Take as kh ( k ) = kh ( k- 1) + 2 * ( kh ( k- 1)-1), Improved coefficients in the S-surface control algorithm k 1 (k)=kh(k)*k 1 (k- 1 ) , k 2 (k)=kh(k)* k 2 (k- 1 ) The output of the actuator is as follows:

[0032] x E ( k )express k Time deviation, x E ( k- 1) indicates k -1 time deviation Indicates the rate of change of deviation. A Maximum rudder angle, M 1 represents the specified tolerance level for deviation. t The total iteration time. T For time intervals, s This represents the number of iterations required to reach a stable error.

[0033] 2) x E ( k )Δ x E (k If )>0, it means that the error and the amount of error growth have the same trend, indicating that the error is developing in the direction of increasing absolute value; (1) | x E ( k )|≥ M 2 indicates a large error, requiring increased control strength and adjustment of the gain coefficient. kh Parameters of the actuator k 1 (k) , k 2 (k) Represented as kh(k) * k 1( k -1), kh(k) * k 2( k -1), the actuator output is:

[0034] (2) | x E ( k )|< M 2. This indicates that the error is not significant, and the current control and actuator parameters can be maintained. k 1, k 2. Maintain k 1, k 2. The output expression of the actuator remains unchanged:

[0035] M 2 represents the specified tolerance level for deviation. M 2< M 1, Δ x E ( k ) =x E ( k ) -x E ( k- 1).

[0036] 3) Δ x E ( k )=0 x E ( k ) =x E ( k- 1) indicates that the error remains unchanged and the control strength needs to be increased. The actuator outputs according to strategy (1) in 2).

[0037] 4) xE ( k )Δ x E ( k )<0, Δ x E ( k ) Δ x E ( k -1)>0 or x E ( k If )=0, it indicates that the absolute value of the error is decreasing or has reached equilibrium, and the actuator output expression remains unchanged.

[0038] 5) x E ( k )Δ x E ( k )<0, Δ x E ( k )Δ x E ( k -1)<0 indicates that the error curve has an inflection point.

[0039] (1) | x E ( k )|≥ M 2. This indicates a large absolute value of error, necessitating increased control intensity. k 1( k )= kh ( k )* k 1( k- 1), k 2( k )= kh ( k )* k 2( k- 1) The output of the actuator is:

[0040] (2) | x E ( k )|< M 2. This indicates that the absolute value of the deviation is small, so the control intensity should be reduced and a suppression coefficient should be set. kd , k 1( k )= kd * k 1( k- 1),k 2( k )= kd * k 2( k- 1) The output of the actuator is:

[0041] 6) | x E ( k If | ≤ e (where e is the error precision), it indicates that the error is already small, and an integral term should be added to reduce the steady-state error. ki The integral term parameter needs to be adjusted based on the feedback results. The actuator output is: As attached Figure 2 The diagram shown illustrates the control process in a specific embodiment. After processing the information obtained from the sensors, the corresponding improved S-plane algorithm is selected to control the actuators according to the established expert control rules, resulting in a new vehicle state. This state is compared with the target value to obtain the deviation. The corresponding improved S-plane algorithm is then selected again to control the actuators according to the expert control rules, and this iterative cycle continues until the control target is achieved.

[0042] like Figure 3 The diagram shows a comparison of the motion control effects of a specific embodiment of the aircraft: a speed of 8 knots, a wave height of 2.5 m, a wave period of 8.8 s, a target navigation depth of 3 m, and a target pitch angle of 0°. It compares the control effects and rudder angle variation amplitudes of the expert control-improved S-plane algorithm and the S-plane algorithm under sea state 4. The meaningful values ​​of the single amplitude of heave are 3.86 m and 3.38 m, respectively, and the meaningful values ​​of the single amplitude of pitch angle are 6.24° and 2.44°, respectively. Under the control algorithm proposed in this disclosure, the amplitudes of heave, pitch angle, and rudder angle variation are smaller, which is more beneficial for reducing the load on the aircraft's servo motors.

[0043] The above technical solutions are merely exemplary embodiments of the present invention. For those skilled in the art, based on the application methods and principles disclosed in the present invention, it is easy to make various types of improvements or modifications, and not limited to the methods described in the specific embodiments of the present invention. Therefore, the methods described above are merely preferred and not restrictive.

Claims

1. A method for controlling the motion of a near-surface vehicle in high sea states, comprising the following steps: Step S1: Define the coordinate system with the vehicle's center of mass as the origin. Let the pitch angle be the motion model of the near-surface vehicle. In the formula, , , , , , , These are, respectively, the mass attribute matrix, the hydrodynamic coefficient matrix, the front rudder angle coefficient matrix, the rear rudder angle coefficient matrix, the static matrix, the propulsion force matrix, and the wave disturbance force matrix. , For the actuating structures of an aircraft, namely the front and rear rudders, variables , , , , , θ These represent longitudinal velocity, vertical velocity, pitch rate, longitudinal displacement, depth of travel, and pitch angle, respectively. , , , , , These represent longitudinal acceleration, vertical acceleration, pitch acceleration, derivative of longitudinal displacement with respect to time, derivative of depth of travel with respect to time, and pitch velocity, respectively. The coefficient elements in the hydrodynamic coefficient matrix are functions of depth of travel and pitch angle. Step S2: Based on this motion model, the rudder, acting as the actuator, is controlled using an improved S-surface algorithm. The actuator output is: in, δ As the rudder angle, k 1. k 2. a Parameters for controlling response speed, k 1, k 2. Adjust according to the actual motion response, with a value range of 1 < k 1<5, 1< k 2<5, 1< a <2, x E For deviation, dx E / dt The rate of change of deviation This is the offset correction amount.

2. The control method as described in claim 1, characterized in that, The fluid dynamic coefficient matrix Calculate according to the following formula: In the formula, m is the mass of the spacecraft, and g is the acceleration due to gravity. It has high initial stability. , , Here are the coefficients of the longitudinal fluid force with respect to the longitudinal direction, vertical direction, and vertical rotation. , Let be the coefficient of the vertical fluid force with respect to the vertical direction and vertical rotation. , This is the coefficient of the lateral rotating fluid torque with respect to the vertical direction and vertical rotation.

3. The control method as described in claim 2, characterized in that, The offset correction amount Determined according to the following formula: T For time intervals, s This represents the number of iterations required to achieve a stable deviation. e ( j The error between the target quantity and the current state is denoted as . b The iteration termination time, α This is the gain factor, with a value range of 1 < α <2.

4. The control method as described in claim 3, characterized in that, In step S2, an expert control algorithm combined with an improved S-plane algorithm is used to control the rudder, which acts as the actuator, including: S21: When | x E ( k )|> M At time 1, the feedback results of motion information are transmitted to the actuator for closed-loop control, and the gain coefficient is set. kh,kh ( k ) =kh ( k- 1) + 2 * ( kh ( k- 1)-1) ， coefficients in the improved S-surface control algorithm k 1( k ) =kh ( k ) *k 1( k- 1), k 2( k ) =kh ( k ) *k 2( k- 1) The output of the actuator is: in, k、k- 1 represents the current time and the previous time. x E ( k )express k Time deviation, x E ( k- 1) indicates k -1 time deviation express k Rate of change of time deviation A Maximum rudder angle, M 1 represents the specified tolerance level for deviation; S22: When x E ( k )Δ x E ( k When )>0: (1) | x E ( k )|≥ M 2. Parameters of the actuator k 1( k ), k 2( k Take them as respectively kh ( k )* k 1( k -1), kh ( k )* k 2( k -1), the actuator output is: ； (2) | x E ( k )|< M 2. The output expression of the actuator remains unchanged, that is: ; Where, Δ x E ( k ) =x E ( k ) -x E ( k- 1), M 2 represents the specified tolerance level for deviation. M 2< M 1; S23: Δ x E ( k )=0 x E ( k ) =x E ( k- 1) The executing agency outputs according to strategy (1) in S22; S24: x E ( k )Δ x E ( k )<0 and Δ x E ( k )Δ x E ( k -1)>0, or x E ( k If ) = 0, the output expression of the actuator remains unchanged, that is: ; S25: x E ( k )D x E ( k )<0 and Δ x E ( k )D x E ( k -1)<0: (1) | x E ( k )|≥ M 2, k 1( k )= kh ( k )* k 1( k- 1), k 2( k )= kh ( k )* k 2( k- 1) The output of the actuator is: ； (2) | x E ( k )|< M 2. Set the suppression coefficient kd , k 1( k )= kd * k 1( k- 1), k 2( k )= kd * k 2( k- 1) The output of the actuator is: ； S26:| x E ( k )|≤ e P ，e P To improve the accuracy of the deviation, an integral term is added to reduce the steady-state deviation. ki The integral term parameter needs to be adjusted based on the feedback results. The actuator output is: 。 5. The control method according to claim 4, characterized in that, The gain coefficient ranges from 1 to 2, and the suppression coefficient ranges from 0 to 1.

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