Hovercraft multi-constraint control method based on composite error transformation preset performance function

Abstract

The invention provides a hovercraft multi-constraint control method based on a composite error transformation preset performance function, and relates to the technical field of hovercraft motion control, and the method comprises the steps: building a motion mathematical model of a full hovercraft, designing an observer, and carrying out the real-time estimation and compensation of the uncertainty of a system, introducing a nonlinear mapping function and a biological excitation model to process asymmetric time-varying constraints; a position control rate and a speed control rate are designed based on a composite error conversion preset performance function, so that the problem of sideslip and drifting in high-speed navigation is effectively avoided, and the trajectory tracking precision and the system stability are improved; in addition, through a disturbance observer and a composite error transformation technology, the initial condition dependence is eliminated, and the robustness of the system is enhanced. The method can significantly improve the trajectory tracking precision, stability and safety of the hovercraft in a complex environment, is suitable for various complex environments such as water surface, land, marsh and the like, and has a wide application prospect.

Description

Technical Field

[0001] The invention relates to the technical field of hovercraft motion control, in particular to a multi-constraint control method based on composite error transformation preset performance function. Background Art

[0002] A fully-lifted hovercraft is a cross-media special ship that is suspended in complex environments such as water, land, and swamps through a lift system. It is widely used in civil fields and naval equipment. However, since the hovercraft is easily affected by external environmental factors (such as wind, waves, load changes, etc.) during operation, its control system has large errors, resulting in poor navigation accuracy and stability. To solve the above problems, current research focuses on multi-model fusion control and nonlinear solution optimization: existing research has proposed a multi-condition weight coefficient iteration method based on reinforcement learning, which improves track stability by dynamically adjusting the actuator strategy; other studies use the Newton iteration method combined with model linearization to improve the accuracy of the lift pressure solution, but the real-time performance and anti-disturbance performance are still limited; the self-disturbance rejection control (ADRC) compensates for disturbances through an extended state observer, but there is still a problem of fuzzy preset performance boundaries under multiple constraints. Therefore, most of the existing hovercraft control methods lack effective consideration of multiple constraints and cannot achieve precise motion control. Summary of the invention

[0003] In order to solve the above problems, the present invention designs a trajectory tracking method based on a preset performance function of a composite error transformation, constrains the control accuracy under the premise of considering the transient steady-state performance, realizes direct constraints on the state variables of the hovercraft system, avoids the side slip and tail swing problem during high-speed navigation, and improves safety performance.

[0004] The present invention specifically provides the following technical solutions: A multi-constraint control method for a hovercraft based on a composite error transformation preset performance function, the control method comprising the following steps: S1. Obtain the hull data and experimental data of the full-lift air cushion vehicle, transform the non-affine mathematical model into a vector angular velocity control model, define the system state variables and introduce uncertainty terms, and construct a vector dynamics model of the full-lift air cushion vehicle including dynamic parameters and external disturbances; S2. Based on the full-lift hovercraft vector dynamics model, a nonlinear disturbance observer is designed, and the observer estimates and compensates for the system uncertainty problem in the hovercraft trajectory tracking; S3. Design nonlinear mapping functions and construct bio-inspired models; S4. Design position control law and speed control law based on composite error transformation preset performance function; S5. Based on the disturbance observer, the composite error transformation technology of continuously differentiable time-varying functions is combined to eliminate the initial condition dependence; and the sliding mode control is coupled with the improved mapping function to synchronously constrain the speed, turning rate and sideslip angle to be in the asymmetric safety range; S6. Dynamically adjust parameters according to the actual operating status of the hovercraft and environmental changes, and verify the effectiveness of the control method.

[0005] Optionally, in S1, the angular velocity control model is specifically: ; in, is the position vector of the hovercraft in the global coordinate system; is the rotation matrix, which is composed of the heel angle and heading angle composition; is the velocity vector in the ship coordinate system; is the inertia matrix; for The instantaneous acceleration, is the Coriolis-centripetal force matrix; is the control input vector; is the external disturbance force; is the total uncertainty, i.e. the damping matrix; Expand the angular velocity control model into a vector form and define , the vector dynamics model of the full-lift hovercraft is specifically as follows: ; in, is the nonlinear coupling term, is the position and attitude vector of the hovercraft in the global coordinate system; is the residual disturbance.

[0006] Optionally, in S2, the process of the nonlinear disturbance observer performing estimation compensation is specifically as follows: ; in, is the dynamic mixing coefficient; is the preset performance function, i.e., the gain matrix, which corresponds to the inertia matrix in the observer , Coriolis matrix , damping matrix The compensation weight of is a nonlinear compensation function used to deal with the nonlinear coupling terms in the hovercraft dynamics model ; is the observation error.

[0007] Optionally, in S3, the nonlinear mapping function Directly handle asymmetric time-varying constraints, The specific expression is: ; in, and They are the state quantities under time constraints. The upper and lower dynamic boundaries of and are the static benchmark values ​​under the upper and lower limit constraints respectively.

[0008] Optionally, in S3, the function of the biological incentive model is: ; in, is the upper bound, is the passive attenuation rate; is the action potential of the neuron, and These are excitatory and inhibitory inputs respectively.

[0009] Optionally, in S4, the position control law is to respectively control the longitudinal position deviation after executing S3. and lateral position deviation Make envelope constraints, specifically: ; in, is the preset performance function to be defined.

[0010] Optionally, the speed control law includes a desired control law of longitudinal speed and lateral speed, specifically: ; in, and are the desired control rates of longitudinal and lateral velocities, respectively; , , They are heading angle, pitch angle and heel angle respectively; and are respectively the target longitudinal coordinate and lateral coordinate of the hovercraft in the global coordinate system; and are preset performance functions for longitudinal and lateral position deviations, respectively; and is the normalized tracking error in the longitudinal and lateral directions; is the weight coefficient.

[0011] Optionally, in said S5, the design is based on improving the consistent nonlinear mapping function Combined with the speed control law of the biological incentive model, it is specifically: ;

[0012] in, The control torque to drive the hovercraft to rotate around the vertical axis Z; , , are the moments of inertia of the hovercraft around the X-axis, Y-axis, and Z-axis respectively; is the damping moment around the Z axis; and are the rotation rates of the hovercraft around the longitudinal and transverse axes, respectively; is the air cushion damping coefficient; is a constant; is the turning resistance component of the hovercraft; and are the linear and nonlinear components of the turning resistance of the hovercraft, respectively; To adjust the resistance weights in the control law; is the equivalent action radius of the contact area between the air cushion and the water surface; is the longitudinal velocity component; is the lateral error velocity.

[0013] Optionally, in S6, a motion control simulation platform of a full-lift hovercraft is built based on MATLAB to perform simulation experiments on the control method; the simulation parameters include the mass, moment of inertia, thrust coefficient, and external disturbance of the hovercraft.

[0014] Optionally, the simulation experiment includes designing a variety of motion scenarios to verify the performance of the control method under different working conditions; the various motion scenarios include straight-line navigation, curved navigation, and sharp turns.

[0015] The present invention has the following beneficial technical effects: The present invention provides a multi-constraint control method for a hovercraft based on a composite error transformation preset performance function. 1) In the present invention, the conventional hovercraft control method often leads to large tracking errors during trajectory tracking due to the lack of effective processing of system uncertainty and external disturbances, especially in complex environments (such as wind and waves, load changes, etc.). By introducing a composite error transformation and a preset performance function, the tracking error can be strictly constrained within a preset range, significantly improving the trajectory tracking accuracy; 2) By designing a disturbance observer to estimate and compensate for system uncertainty in real time, and combining the preset performance function, the robustness of the system is significantly enhanced. Even in the presence of strong disturbances, the system can still maintain stable operation. By introducing an improved consistent nonlinear mapping function, the speed, turning rate and sideslip angle of the hovercraft can be directly constrained, effectively avoiding the side slip and tail swing problem during high-speed navigation, and improving navigation safety; 3) By designing a nonlinear mapping function, asymmetric time-varying constraints can be directly processed, and constrained and unconstrained situations can be uniformly processed, significantly improving the applicability and flexibility of the control method. By introducing the composite error transformation technology, the initial deviation of the hovercraft position can be compressed into a definable range, eliminating the initial condition dependence and improving the stability and reliability of the control method. The control method proposed in the present invention has wide applicability and can be applied to the motion control of the full-lift hovercraft in different environments (such as water surface, land, swamp, etc.), and has high versatility and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A control flow chart of a full-lift hovercraft provided by an embodiment of the present invention.

[0018] Figure 2 A schematic diagram of a multi-constraint control method for a hovercraft based on a composite error transformation preset performance function provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0020] The following specific examples are used to illustrate the embodiments of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present application.

[0021] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any labeled structures and / or functions described herein are merely illustrative. Based on the present application, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number and aspect set forth herein may be used to implement an apparatus and / or practice a method.

[0022] It should also be noted that the illustrations provided in the following embodiments are only used to schematically illustrate the basic concept of the present application.

[0023] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the examples can be practiced without these marked details.

[0024] The object of the present invention is to provide a multi-constraint control method for a hovercraft based on a composite error transformation preset performance function.

[0025] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] Reference Figure 1 , showing a control flow chart of a full-lift hovercraft according to an embodiment of the present application.

[0027] Figure 1The control logic is a multi-actuator collaborative control architecture based on closed-loop feedback. Its core process takes the desired navigation trajectory as the input target, and generates a multi-degree-of-freedom tracking error signal by real-time collection of the hovercraft's position, heading and attitude data. Subsequently, the motion controller uses a nonlinear decoupling algorithm to convert the error into an independent control component (such as longitudinal thrust and lateral torque), and introduces a preset performance function to dynamically constrain the error amplitude and convergence rate to avoid overshoot or actuator saturation; the decoupled instructions are optimized and distributed to actuators such as propellers, air rudders and bow nozzles through the control distributor, and finally the disturbance deviation is corrected in real time through closed-loop feedback from the sensor, forming a complete control loop of "trajectory input-error solution-instruction distribution-dynamic compensation".

[0028] Figure 2 The control logic is Figure 1 The technical refinement and implementation expansion of the architecture focuses on the precise control of cushion pressure and multi-degree-of-freedom motion.

[0029] Specifically, Figure 2 A method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to an embodiment of the present application is shown, and the method comprises the following steps: S1. Obtain the hull data and experimental data of the full-lift hovercraft, transform the non-affine mathematical model into a vector angular velocity control model, define the system state variables and introduce uncertainty terms, and construct a vector dynamics model of the full-lift hovercraft including dynamic parameters and external disturbances.

[0030] In S1, the angular velocity control model is specifically: ; in, is the position vector of the hovercraft in the global coordinate system; is the rotation matrix, which is composed of the heel angle and heading angle composition; is the velocity vector in the ship coordinate system; is the inertia matrix; for The instantaneous acceleration, is the Coriolis-centripetal force matrix; is the control input vector; is the external disturbance force; is the total uncertainty, i.e. the damping matrix, including linear / nonlinear damping such as fluid resistance and air resistance.

[0031] Specifically, , represents the position and attitude of the hovercraft in the global coordinate system, Corresponding to the three-dimensional position coordinates, is the heel angle, is the pitch angle, is the heading angle; represents the linear velocity and angular velocity of the hovercraft in the hull coordinate system, is the longitudinal linear velocity, is the transverse linear velocity, is the vertical linear velocity, is the heel angular velocity, is the pitch angular velocity, is the heading angular velocity; is the rotation matrix, which represents the mapping to the global coordinate system pose η, and R1 is given by ,θ, The linear velocity rotation matrix composed of R2 is ,θ, The angular velocity rotation matrix is ​​composed of: R1 and R2 are expressed as follows: ;

[0032] The inertia matrix M contains the symmetric positive definite matrix of the mass and moment of inertia of the hovercraft, reflecting the inertial characteristics of the translation and rotation motion of the hull, which is specifically expressed as follows: ;

[0033] Coriolis-Centriptial Force Matrix It is the virtual force / torque generated by the hull motion coupling, which is related to the velocity vector ν and reflects the nonlinear dynamic characteristics. The specific expression is as follows: ;

[0034] Where m is the total mass of the hull, in kg. is the moment of inertia around the x-axis of the hull coordinate system, in kg·m², is the moment of inertia around the y-axis of the hull coordinate system, in kg·m², is the moment of inertia about the z-axis of the hull coordinate system, in kg·m².

[0035] Characterizes external disturbance forces, including the forces / torques exerted by external environments such as wind, waves, and ocean currents on the hull. The specific expressions are as follows: ; ;

[0036] in, is the fluid density, is the pressure, the pressure inside the air cushion or the hydrostatic pressure, is the velocity of the hovercraft relative to the air; g is the acceleration due to gravity, implicit in the hydrostatic term; are the total resistance components of the hull in the x, y, and z directions, respectively, which are composed of the superposition of aerodynamic resistance, fluid resistance, shear force, etc.; are the moment resistance components around the x, y, and z axes respectively; , are the components of the aerodynamic force in the x and y directions respectively; is the air cushion momentum force, which is related to the air cushion flow rate. , where Q is the volume flow rate, such as the air cushion fan flow rate; It is the buoyancy or vertical support force generated by the hydrostatic pressure; is the shear force, which is related to the fluid viscosity effect: is the force generated by the air cushion pressure; is the tilt angle of the hovercraft or the angle of the fluid action direction; is a characteristic length, such as the air cushion length or the hull contact surface length; is the fluid layer height or air cushion thickness; is the width of the air cushion; is the hull heel angle or geometry correction factor; is the reference height, such as the initial fluid layer thickness; is the characteristic length of shear action; is a reference area, such as the air cushion projection area or the fluid action surface area; is the characteristic length of the air cushion, used for pressure distribution calculation; is the general force / torque coefficient, is the aerodynamic attack angle coefficient acting in the x direction; , The aerodynamic moment coefficients around the x-axis and z-axis respectively; Shear coefficient; is the water density; is the air density. The core parameters in the above formula have been given, and the definitions of other related parameters can be directly obtained or inferred according to the mission scenario, so they will not be repeated here.

[0037] The units and values ​​of the above-mentioned relevant parameters in the hovercraft model are specifically shown in Table 1.

[0038] Table 1. Relevant parameters in the hovercraft model .

[0039] Expanding the formula to vector form, considering the hovercraft model with system uncertainty, we define , rewritten as: ; in, is the nonlinear coupling term, is the position and attitude vector of the hovercraft in the global coordinate system; is the residual disturbance.

[0040] Step S2. Using the full-lift hovercraft vector mathematical model established in step S1, the following observer is designed for estimation compensation in view of the system uncertainty problem in hovercraft trajectory tracking: ; in, is the dynamic mixing coefficient; is the preset performance function, i.e., the gain matrix, which corresponds to the inertia matrix in the observer , Coriolis matrix , damping matrix The compensation weight of is a nonlinear compensation function used to deal with the nonlinear coupling terms in the hovercraft dynamics model ; is the observation error. Specifically, , and .in Specifically, it represents the dynamic coupling error between the system pose η and the observed state ξ, including the influence of unmodeled dynamics or external disturbances. is the observation value vector, which represents the estimated value of the linear velocity and angular velocity in the ship coordinate system; is the observed error vector, which represents the estimated deviation of the three-axis position and three-axis torque. . They are expressed as correction values ​​in different intervals, and can ensure that the observation error converges to the origin. The correction function is as follows: ; Among them, H1(e) is a mixed correction term, including the time function h(t), the gain matrix Θ, and the error scaling factor ; H2(e) is the second-order correction term, which strengthens the time dependence; H3(e) is the third-order correction term, which is used for high-order error suppression; is the convergence parameter and is determined by solving the linear matrix inequality LMI, which is used to ensure the exponential convergence of the observation error; It can be written as follows: ; Among them, N1(e) is a nonlinear sliding mode correction term, including gain l1 and sign function sign(e); N2(e) is a mid-order sliding mode correction term, which reduces chattering; N3(e) is a first-order sliding mode correction term, which directly acts on the error; is the Lipschitz constant, are the parameters to be designed and satisfy: , and .

[0041] Step S3 specifically includes three sub-steps, namely: Step 3-1: Design a nonlinear mapping function that can directly handle asymmetric time-varying constraints without changing its own structure, and can uniformly handle constrained and unconstrained situations. The designed function : ; in, and Define the state quantity under time constraints separately The upper and lower dynamic boundaries of and are the static benchmark values ​​under the upper and lower limit constraints respectively.

[0042] Step 3-2: Design a bioinspiration model. The bioinspiration model represents the rate of change of the action potential ζi of neuron i over time. Therefore, the bioinspiration model function is defined as: ; ; in, is the upper bound, representing the maximum saturation value of the neuronal action potential, limiting the positive excitation amplitude of the excitatory input; is the passive decay rate, which describes the natural decay rate of neurons when there is no external input; is the action potential of the neuron, indicating the membrane potential state of neuron i, and is the state variable of the model; and They are excitatory and inhibitory inputs, respectively, triggered according to the polarity of the input signal a.

[0043] Step 3-3: Design the position control rate based on the preset performance function of the composite error transformation. Under the premise of executing step 3-2, the longitudinal position deviation is and lateral position deviation The envelope constraint is: ; in, is a preset performance function to be defined. Preferably, an exponential preset performance function is selected.

[0044] Redefine the conversion error as follows: ; in, and .

[0045] in , Normalized error is to scale the original error to within the preset performance boundary; is the time-varying mixing coefficient, 0≤ ≤1, which is used to dynamically adjust the nonlinear tanh and linear The error conversion ratio. is a hyperbolic tangent function, which is used to limit the amplitude of the error after conversion and enhance robustness. is the original error constrained by nonlinear mapping Convert to a new unconstrained error , which is convenient for controller design. The converted error satisfies the inequality , the tracking error will be within the preset performance range.

[0046] Therefore, the following longitudinal speed and lateral speed expected control rate are designed: ; in, and are the desired control rates of longitudinal and lateral velocities, respectively; , , They are heading angle, pitch angle and heel angle respectively; and are respectively the target longitudinal coordinate and lateral coordinate of the hovercraft in the global coordinate system; and are preset performance functions for longitudinal and lateral position deviations, respectively; and is the normalized tracking error in the longitudinal and lateral directions; is the weight coefficient.

[0047] Step S5: Design a speed control rate based on an improved consistent nonlinear mapping function. Under the premise of executing step 3-3, introduce the improved consistent nonlinear mapping function designed in step 3-1. In order to avoid the differential expansion problem and simplify the control design, the bioinspiration model designed in step 3-2 is introduced to obtain: ;

[0048] in, The control torque to drive the hovercraft to rotate around the vertical axis Z; , , are the moments of inertia of the hovercraft around the X-axis, Y-axis, and Z-axis respectively; is the damping moment around the Z axis; and are the rotation rates of the hovercraft around the longitudinal and transverse axes, respectively; is the air cushion damping coefficient; is a constant; is the turning resistance component of the hovercraft; and are the linear and nonlinear components of the turning resistance of the hovercraft, respectively; To adjust the resistance weights in the control law; is the equivalent action radius of the contact area between the air cushion and the water surface; is the longitudinal velocity component; is the lateral error velocity.

[0049] Step S6. According to the actual operating state of the hovercraft and environmental changes, dynamically adjust parameters and verify the effectiveness of the control method.

[0050] In order to verify the effectiveness of the present invention, system simulation and experimental verification were carried out. The specific implementation steps are as follows: 1. Simulation environment construction: Use MATLAB / Simulink to build a motion control simulation platform for a full-lift hovercraft. Set simulation parameters, including the mass, moment of inertia, thrust coefficient, external disturbances (such as wind and waves) of the hovercraft. Design a variety of typical motion scenarios, such as straight-line navigation, curved navigation, and sharp turns, to verify the performance of the control method under different working conditions.

[0051] 2. Analysis of simulation results: In the comparative experiment, the control method based on the preset performance function of composite error transformation proposed in the present invention is compared with the trajectory tracking accuracy and stability of the traditional control method (such as PID control, sliding mode control), and the robustness of the system in the presence of external disturbances and uncertainties is analyzed to verify the estimation and compensation effect of the observer on the system uncertainty. The simulation results show that the side slip and tail swing problem of the hovercraft at high speed is significantly improved, which verifies the effective constraint of the preset performance function on the state variables.

[0052] The actuator constraints of the full-lift hovercraft are the rudder angle constraint, the thrust speed constraint and the pitch angle constraint. Considering that the propeller drive mechanism and the steering gear of the hovercraft are affected by the mechanical properties, their motion range and speed are limited, and then the bounded constraints of the control quantity and control increment and the bounded constraints of the hull yaw angle rate are introduced, which are respectively ; in, , are the minimum and maximum values ​​of propeller thrust and torque, respectively; and are the minimum and maximum permissible changes of the control increment respectively; , are the minimum and maximum values ​​of the yaw rate of the ship respectively; is the current iteration number, To control the time domain length, is the total number of steps.

[0053] Experimental verification: Experiments were conducted on an actual full-lift hovercraft platform to collect actual operating data. The simulation results were compared with the experimental data to verify the actual application effect of the control method. The experimental results show that the control method proposed in the present invention can significantly improve the trajectory tracking accuracy and stability of the hovercraft, while effectively avoiding the side slip and tail swing problem.

[0054] Parameter adaptive adjustment: According to the actual operating status of the hovercraft and environmental changes, the parameters in the preset performance function and control law are dynamically adjusted to further improve the control accuracy and robustness.

[0055] Multi-objective optimization: Combined with multi-objective optimization algorithms, the parameters in the control law are optimized to achieve the best balance between trajectory tracking accuracy, energy consumption and safety.

[0056] Based on the same inventive concept, according to another aspect of the present invention, an embodiment of the present invention further provides a computer device, including: at least one processor; and The memory stores a computer program that can be run on the processor, and the processor executes the steps of any one of the above control methods when executing the program.

[0057] Based on the same inventive concept, according to another aspect of the present invention, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer program instructions. When the computer program instructions are executed by a processor, the steps of any of the above control methods are performed.

[0058] Finally, it should be noted that a person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only storage memory (ROM) or a random access memory (RAM), etc. The above-mentioned computer program embodiments can achieve the same or similar effects as the corresponding above-mentioned arbitrary method embodiments.

[0059] In addition, typically, the devices and equipment disclosed in the embodiments of the present invention may be various electronic terminal devices, such as mobile phones, personal digital assistants (PDAs), tablet computers (PADs), smart TVs, etc., or large terminal devices, such as servers, etc. Therefore, the protection scope disclosed in the embodiments of the present invention should not be limited to a certain type of device or equipment. The client disclosed in the embodiments of the present invention may be applied to any of the above electronic terminal devices in the form of electronic hardware, computer software, or a combination of the two.

[0060] In addition, the method disclosed in the embodiment of the present invention can also be implemented as a computer program executed by a CPU, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the CPU, the above functions defined in the method disclosed in the embodiment of the present invention are performed.

[0061] In addition, the above method steps and system units may also be implemented using a controller and a computer-readable storage medium for storing a computer program that enables the controller to implement the above steps or unit functions.

[0062] The above are exemplary embodiments disclosed in the present invention, but it should be noted that various changes and modifications may be made without departing from the scope disclosed in the embodiments of the present invention as defined in the claims. The functions, steps and / or actions of the method claims according to the disclosed embodiments described herein do not need to be performed in any marked order. In addition, although the elements disclosed in the embodiments of the present invention may be described or required in individual form, they may also be understood as multiple unless explicitly limited to the singular.

[0063] In this specification, the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the embodiments described later, the description is relatively simple, and the relevant parts can be referred to the partial description of the previous embodiments.

[0064] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A multi-constraint control method for a hovercraft based on a composite error transformation preset performance function, characterized in that: The control method comprises the following steps: S1. Obtain the hull data and experimental data of the full-lift air cushion vehicle, transform the non-affine mathematical model into a vector angular velocity control model, define the system state variables and introduce uncertainty terms, and construct a vector dynamics model of the full-lift air cushion vehicle including dynamic parameters and external disturbances; S2. Based on the full-lift hovercraft vector dynamics model, a nonlinear disturbance observer is designed, and the observer estimates and compensates for the system uncertainty problem in the hovercraft trajectory tracking; S3. Design nonlinear mapping functions and construct bio-inspired models; S4. Design position control law and speed control law based on composite error transformation preset performance function; S5. Based on the disturbance observer, the composite error transformation technology of continuously differentiable time-varying functions is combined to eliminate the initial condition dependence; and the sliding mode control is coupled with the improved mapping function to synchronously constrain the speed, turning rate and sideslip angle to be in the asymmetric safety range; S6. Dynamically adjust parameters according to the actual operating status of the hovercraft and environmental changes, and verify the effectiveness of the control method.

2. The method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to claim 1, characterized in that: In S1, the angular velocity control model is specifically: ； in, is the position vector of the hovercraft in the global coordinate system; is the rotation matrix, which is composed of the heel angle and heading angle composition; is the velocity vector in the ship coordinate system; is the inertia matrix; for The instantaneous acceleration, is the Coriolis-centripetal force matrix; is the control input vector; is the external disturbance force; is the total uncertainty, i.e. the damping matrix; Expand the angular velocity control model into a vector form and define , the vector dynamics model of the full-lift hovercraft is specifically as follows: ； in, is the nonlinear coupling term, is the position and attitude vector of the hovercraft in the global coordinate system; is the residual disturbance.

3. The method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to claim 2, characterized in that: In S2, the process of the nonlinear disturbance observer performing estimation compensation is specifically as follows: ； in, is the dynamic mixing coefficient; is the preset performance function, i.e., the gain matrix, which corresponds to the inertia matrix in the observer , Coriolis-centripetal force matrix , damping matrix The compensation weight of is a nonlinear compensation function used to deal with the nonlinear coupling terms in the hovercraft dynamics model ; is the observation error.

4. The method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to claim 1, characterized in that: In S3, the nonlinear mapping function Directly handle asymmetric time-varying constraints, The specific expression is: ； in, and They are the state quantities under time constraints. The upper and lower dynamic boundaries of and are the static benchmark values ​​under the upper and lower limit constraints respectively.

5. A multi-constraint control method for a hovercraft based on a composite error transformation preset performance function according to any one of claims 1 or 4, characterized in that: In S3, the function of the biological incentive model is: ； in, is the upper bound, is the passive attenuation rate; is the action potential of the neuron, and These are excitatory and inhibitory inputs respectively.

6. The method for multi-constraint control of a hovercraft based on a composite error transformation preset performance function according to claim 5, characterized in that: In S4, the position control law is to respectively control the longitudinal position deviation after executing S3. and lateral position deviation Make envelope constraints, specifically: ； in, is the preset performance function to be defined.

7. The method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to claim 6, characterized in that: The speed control law includes the longitudinal speed and lateral speed desired control law, which are specifically: ； in, and are the desired control rates of longitudinal and lateral velocities, respectively; , , They are heading angle, pitch angle and heel angle respectively; and are respectively the target longitudinal coordinate and lateral coordinate of the hovercraft in the global coordinate system; and are preset performance functions for longitudinal and lateral position deviations, respectively; and is the normalized tracking error in the longitudinal and lateral directions; is the weight coefficient.

8. A method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to any one of claims 1 or 7, characterized in that: In S5, the design is based on improving the consistent nonlinear mapping function Combined with the speed control law of the biological incentive model, it is specifically: ; in, The control torque to drive the hovercraft to rotate around the vertical axis Z axis; , , are the moments of inertia of the hovercraft around the X-axis, Y-axis, and Z-axis respectively; is the damping moment around the Z axis; and are the rotation rates of the hovercraft around the longitudinal and transverse axes, respectively; is the air cushion damping coefficient; is a constant; is the turning resistance component of the hovercraft; and are the linear and nonlinear components of the turning resistance of the hovercraft, respectively; To adjust the resistance weights in the control law; is the equivalent action radius of the contact area between the air cushion and the water surface; is the longitudinal velocity component; is the lateral error velocity.

9. The method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to claim 1, characterized in that: In S6, a motion control simulation platform of a full-lift hovercraft is built based on MATLAB to perform simulation experiments on the control method; the simulation parameters include the mass, moment of inertia, thrust coefficient, and external disturbance of the hovercraft.

10. The method for controlling a hovercraft with multiple constraints based on a composite error transformation preset performance function according to claim 9, characterized in that: The simulation experiment includes designing a variety of motion scenarios to verify the performance of the control method under different working conditions; the various motion scenarios include straight-line navigation, curved navigation, and sharp turns.

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