A method for dynamic modeling and motion control of a variable-wing underwater glider

Abstract

The application provides a variable wing underwater glider dynamics modeling method and motion control method, the dynamics modeling method comprises the following steps: A. defining the coordinate system and transformation rule; B. deriving the rigid body kinematics equation; C. calculating the static force and torque; D. calculating the dynamics force and torque; E. calculating the fin combined external force and combined external torque; F. calculating the inertia parameter; G. integrating the dynamic control model. The application aims to systematically solve the technical defects of existing underwater vehicles, including: first, breaking through the maneuverability bottleneck of traditional underwater gliders, giving the platform multi-modal motion capability on the basis of retaining the long-range advantage; second, for bionic gliders, establishing a unified and accurate dynamics model framework to describe the nonlinear coupling between systems, providing a basis for stability and maneuverability evaluation and analysis; third, clarifying the influence law of key control parameters on motion performance, providing theoretical support for platform design optimization and motion control strategy formulation.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of computer-aided engineering (CAE), computational fluid dynamics (CFD), and biomimetic underwater robot technology, and in particular to a dynamic modeling method and motion control method for a variable-wing underwater glider. Background Technology

[0002] In the field of underwater vehicles, underwater gliders have become an important tool for long-term monitoring in the deep sea due to their advantages of long range, long endurance, and low energy consumption. They achieve gliding motion through net buoyancy and attitude adjustment, and the relevant theoretical system is relatively mature. However, traditional underwater gliders are limited by fixed-wing configuration and buoyancy-driven methods, resulting in problems such as low speed, weak maneuverability, and slow dynamic response, making them difficult to adapt to tasks such as rapid turns and complex trajectory tracking.

[0003] To balance endurance and maneuverability, biomimetic technology has become a research hotspot. Among these, variable-wing biomimetic technology, by dynamically adjusting wing surface morphology and motion patterns to achieve a fusion of gliding and flapping propulsion, represents a cutting-edge direction for improving underwater platform performance. However, traditional CFD simulation methods do not optimize mesh generation and equation solving processes for variable-wing structures, resulting in long model iteration cycles and low computational accuracy. Furthermore, the connection between the dynamic model and motion control algorithm lacks computer simulation verification, and control parameter tuning relies on physical experiments, leading to high costs and low efficiency. Although existing technologies attempt to improve computational efficiency by simplifying dynamic equations, they neglect the dynamic coupling characteristics of variable-wing systems, resulting in insufficient control accuracy.

[0004] Biomimetic dynamics modeling suffers from significant shortcomings: most approaches establish gliding and biomimetic propulsion models separately or simply superimpose them, lacking a unified framework to describe the nonlinear coupling effects of buoyancy propulsion, internal mass regulation, and biomimetic fin motion. This leads to design optimization relying on expensive simulations or extensive testing, resulting in low control efficiency and hindering the full realization of platform performance. The closest existing technology is the manta ray-inspired glider integrating buoyancy propulsion and biomimetic pectoral fins. While compact in structure, it still fails to address the core modeling and maneuverability-related issues mentioned above. Summary of the Invention

[0005] This invention provides a dynamic modeling method and motion control method for a variable-wing underwater glider, aiming to systematically solve the technical defects of existing underwater vehicles. The core objectives include: first, overcoming the maneuverability bottleneck of traditional underwater gliders and endowing the platform with multimodal motion capabilities while retaining its long-range advantage; second, establishing a unified and accurate dynamic model framework for biomimetic gliders to describe the nonlinear coupling effects between various systems, providing a foundation for stability and maneuverability assessment and analysis; and third, clarifying the influence of key control parameters on motion performance, providing theoretical support for platform design optimization and motion control strategy formulation.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A dynamic modeling method for a variable-wing underwater glider includes: A. Define an inertial frame, a glider fixed coordinate system, and three biomimetic fin fixed frames. Implement motion parameter transformation through preset coordinate transformation rules, and output the coordinate system and transformation rules. B. Based on the momentum theorem and the angular momentum theorem, input the coordinate system and transformation rules of step A, and derive the rigid body kinematic equations of the variable-wing underwater glider. C. Input the total mass of the variable-wing underwater glider, the preset gravitational acceleration, the fluid density and the volume of displaced fluid, and calculate and output the static forces and torques, including gravity, buoyancy and gravitational translation torque; D. Based on the ideal fluid assumption and the geometric symmetry of the glider, input the motion velocity parameters and calculate the output dynamic forces and torques, which include hydrodynamic damping forces, additional mass forces, and stress torques; E. Input the biomimetic fin fixation system of step A, the rigid body kinematic equation of step B, and the preset hydrodynamic coefficients. Output the net external force and net external torque of the fin through the Morrison equation and the fin surface area integral. F. Input the instantaneous mass and instantaneous position of each mechanism in the adjustment module, and calculate the output inertial parameters using the parallel axis theorem. The inertial parameters include the total mass, the moment of inertia matrix relative to the center of buoyancy, the rate of change of the moment of inertia matrix, the position vector of the center of mass pointing to the center of buoyancy, and the rate of change of the position vector of the center of mass. G. Input the rigid body kinematic equations from step B, the static forces and moments from step C, the dynamic forces and moments from step D, the net external forces and moments of the fins from step E, and the inertial parameters from step F, and integrate them to output the dynamic control model.

[0007] In this specification, the coordinate transformation rules in step A are predefined by mapping the origin and rotating the coordinate axes, ensuring the accurate transformation of motion parameters in step B, and providing a unified benchmark for the integration of static forces and torques, dynamic forces and torques, and net external forces and torques of the fins in step G under multiple coordinate systems.

[0008] In this specification, the additional mass matrix in step D adopts a geometrically symmetric design, retaining only the translational and rotational uncoupled terms, which simplifies the calculation process of dynamic forces and moments, reduces the computational load of the dynamic control model in step G, and improves the model solution efficiency.

[0009] In this specification, the fin surface area integral in step E covers the entire effective action surface of the right pectoral fin, left pectoral fin, and caudal fin, ensuring that the fin forces and torques fully reflect the fluid action effect. This works in conjunction with the static forces and torques in step C and the dynamic forces and torques in step D to optimize the attitude response description accuracy of the model in step G.

[0010] In this specification, step F involves real-time parameter acquisition using a mass position sensor, periodic updating of inertial parameters, and synchronous adjustment of the adaptability of static forces and torques in step C and dynamic forces and torques in step D, ensuring the real-time response performance of the model in step G.

[0011] A motion control method for a variable-wing underwater glider, employing the dynamic modeling method for a variable-wing underwater glider described in any one of the above-mentioned methods, wherein the motion control method for the variable-wing underwater glider includes: a. Collect the initial position, velocity, and attitude data of the variable-wing underwater glider and output them as initial conditions for the dynamic control model; b. Receive preset or remote control commands and output control inputs for the pectoral fin, caudal fin and adjustment module. The control inputs include the pitch angle and roll angle of the pectoral fin, the pitch angle of the caudal fin, and the buoyancy adjustment amount and center of mass adjustment amount of the adjustment module, which are used to adjust the inertial parameters of the model and the parameters of static forces and torques, dynamic forces and torques, and fin forces and torques (net external forces and net external torques of the fins). c. Input the control input from step b into the dynamic control model, output the motion trajectory and force data through numerical solution, and feed it back to the control terminal; d. Input the feedback data from step c, dynamically adjust the control input from step b, balance the static forces and torques, dynamic forces and torques, and the net external forces and torques of the fins, and output the coordinated control commands for the pectoral fins, caudal fins, and adjustment modules to achieve the preset motion modes of zigzag gliding and spiral gliding.

[0012] In this specification, the sawtooth gliding mode includes a pectoral fin pitch adjustment sub-mode. This sub-mode sets the pectoral fin pitch angle and the buoyancy and center of mass parameters of the adjustment module through the control input in step b, so that the static forces and torques, dynamic forces and torques, and the resultant external forces and resultant external forces rectangles of the fins solved in step c are in dynamic equilibrium, ensuring the stability of the gliding trajectory.

[0013] In this specification, the sawtooth gliding mode includes a tail fin pitch adjustment sub-mode. This sub-mode adjusts the tail fin pitch angle through step b, optimizes the heading moment term in the resultant external torque of the fin in step c, and achieves fine-tuning of heading in conjunction with static forces and moments, dynamic forces and moments. The adjustment range is determined by the solution result of step c.

[0014] In this specification, the serrated gliding mode includes a pectoral fin roll differential adjustment sub-mode. This sub-mode sets the roll differential angle of the left and right pectoral fins in step b, changes the lateral torque term in the resultant external torque of the fins in step c, and achieves lateral control by combining static force and torque, dynamic force and torque. The control effect is verified by the trajectory data in step c.

[0015] In this specification, the spiral gliding mode fixes the pectoral fin roll angle and adjusts the pectoral fin pitch angle, caudal fin pitch angle, and buoyancy and center of mass parameters of the adjustment module in step b, and optimizes the relationship between static force and torque, dynamic force and torque, and net external force and net external torque of the fin in step c, thereby controlling the circling radius and period and achieving efficient full-coverage observation of the target water area.

[0016] In summary, this invention has at least the following beneficial effects: Feasibility verification: Through multi-mode motion simulation, it is proven that the technical solution is feasible in both physical principles and engineering implementation. Rich motion modes: By simply adjusting the fin attitude, multiple optimized gliding modes and three-dimensional composite motion modes can be derived, significantly improving mission adaptability. Performance optimization support: The optimization direction of key parameters is clarified, providing clear guidance for parameter tuning in actual engineering. Simplified control design: The specific motion of the pectoral fins and longitudinal gliding performance are approximately decoupled, allowing for independent design of longitudinal and lateral control laws, reducing the complexity of the control system. Expanded application scenarios: It has the ability to actively control the area search mode, achieving efficient and comprehensive observation of target waters, breaking through the limitations of traditional underwater applications. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the dynamic modeling method for the variable-wing underwater glider involved in this invention.

[0018] Figure 2 This is a schematic diagram of the motion control method for the variable-wing underwater glider involved in this invention.

[0019] Figure 3 This is a schematic diagram of the motion mechanism of the underwater glider involved in this invention.

[0020] Figure 4 This is a schematic diagram of the variable-wing underwater glider and its coordinate system involved in this invention.

[0021] Figure 5 The mode involved in this invention is the pectoral fin control mode: relying on the pectoral fin pitch angle ( A schematic diagram illustrating the simulation results of adjusting parameters to drive the device to complete a sawtooth gliding motion.

[0022] Figure 6 The second mode involved in this invention is the caudal fin control mode: relying on the caudal fin pitch angle ( The simulation results of the device completing the sawtooth gliding motion are shown in the figure below, based on the parameter adjustment of the device.

[0023] Figure 7 The third mode involved in this invention is the pectoral fin roll differential control mode: relying on the pectoral fin roll differential angle ( The simulation results of the device completing the sawtooth gliding motion are shown in the figure. Detailed Implementation

[0024] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0025] like Figure 1 As shown, this embodiment provides a dynamic modeling method for a variable-wing underwater glider, including the following steps: A. Define three coordinate systems: an inertial frame for describing absolute motion, a glider-fixed coordinate system fixed to the body of the variable-wing underwater glider and moving synchronously, and three biomimetic fin fixed frames fixed to the right pectoral fin, left pectoral fin, and tail fin of the variable-wing underwater glider, respectively. The three coordinate systems realize the transformation of motion parameters through a preset coordinate transformation rule, which provides the basis for subsequent equation derivation and force and torque integration. B. Based on the momentum theorem and the angular momentum theorem, and combined with the three coordinate systems and coordinate transformation rules defined in step A, the rigid body kinematic equations of the variable wing underwater glider in the connected coordinate system are derived. These equations are used to describe the dynamic relationship between the position, velocity and attitude of the variable wing underwater glider. C. Analyze the underwater static characteristics, calculate the gravity and buoyancy acting on the variable-wing underwater glider, and the gravity translation moment generated when the gravity moves from the center of mass of the variable-wing underwater glider to the center of buoyancy. The gravity is calculated based on the total mass of the variable-wing underwater glider and the preset gravitational acceleration, and the buoyancy is calculated based on the preset fluid density and the volume of fluid displaced by the variable-wing underwater glider. The above gravity, buoyancy and gravity translation moment together constitute the static force and moment terms of the rigid body kinematic equation. D. Analyze the underwater dynamic characteristics, calculate the hydrodynamic damping force and its generated hydrodynamic damping torque, the additional mass force and its generated additional mass torque. The hydrodynamic damping force ignores the interdirectional coupling terms, and only considers the linear terms and second-order higher-order terms in the same direction as the motion velocity. The additional mass force is obtained by constructing the additional mass matrix based on the ideal fluid assumption and the geometric symmetry of the variable-wing underwater glider. The above hydrodynamic damping force, additional mass force and the corresponding hydrodynamic damping torque and additional mass torque together constitute the dynamic force and torque terms of the rigid body kinematic equation. E. Based on the biomimetic fin fixation system in step A and the rigid body kinematic equations in step B, analyze the kinematic and dynamic characteristics of the pectoral and caudal fins. Consider the velocity of the fin particles as the superposition of the translational and rotational velocities of the rigid body of the variable-wing underwater glider (velocity parameters are derived from the rigid body kinematic equations). Combined with preset hydrodynamic coefficients (obtained in advance through underwater fluid dynamics experiments or simulations), use the Morrison equation to calculate the force of the fluid acting on the micro-element surface of the fin. Then, by integrating over the surface area of ​​the fin, obtain the net external force and net external torque of the fluid acting on the fin, and convert it to the fixed coordinate system of the glider in step A. The above net external force and net external torque of the fin are added to the external force and external torque terms of the rigid body kinematic equations. F. Model the adjustment module of the variable-wing underwater glider. The adjustment module includes a translational mass block, a rotating mass block, and a water intake / discharge device. The instantaneous mass and instantaneous position of each adjustment mechanism are collected in real time by the mass position sensor mounted on the variable-wing underwater glider. Combined with the parallel axis theorem, calculate the total mass of the variable-wing underwater glider, the rotational inertia matrix relative to the center of buoyancy, the position vector of the center of mass pointing to the center of buoyancy, and its rate of change. The total mass, rotational inertia matrix, center of mass position vector, and its rate of change are used to update the inertial parameter terms in the rigid body kinematic equations. G. Integrate the rigid body kinematics equations from step B, the gravity, buoyancy, and gravity translation moment from step C, the hydrodynamic damping force, additional mass force and corresponding hydrodynamic damping moment and additional mass moment from step D, the net external force and net external moment of the fin from step E, and the updated inertial parameter terms from step F to construct a dynamic control model describing the multimodal motion characteristics of the variable-wing underwater glider. This model is based on a set of ordinary differential equations extended from the rigid body kinematics equations. All the aforementioned forces and corresponding moments are used as force inputs to this model, and the inertial parameter terms are the core fundamental parameters of the model.

[0026] In some embodiments, the preset coordinate transformation rules in step A are predetermined through the mapping relationship of the coordinate system origin and the definition of the coordinate axis rotation angle. This ensures that the motion parameters between the inertial frame, the glider fixed coordinate system, and the bionic fin fixed system can be accurately converted when deriving the rigid body kinematic equations in step B. At the same time, it ensures that gravity, buoyancy, gravity translation torque, hydrodynamic damping torque, additional mass torque, and fin net external torque are integrated and calculated in the same coordinate system in step G, avoiding parameter conflicts.

[0027] In some embodiments, the additional mass matrix in step D is based on the geometric symmetry design of the variable-wing underwater glider, retaining only the uncoupled terms related to translation and rotation, simplifying the calculation process of hydrodynamic damping force, additional mass force and corresponding hydrodynamic damping torque and additional mass torque, reducing the computational load of the dynamic control model in step G, and improving the numerical solution efficiency of the model.

[0028] In some embodiments, the integral calculation of the fin surface area in step E covers the entire effective action surface of the right pectoral fin, left pectoral fin, and caudal fin, ensuring that the resultant external force and resultant external torque of the fin can fully reflect the fluid action effect of the three fins. This works in conjunction with the gravity translation torque in step C, the hydrodynamic damping torque in step D, and the additional mass torque to improve the accuracy of the dynamic control model in describing the attitude response of the variable-wing underwater glider.

[0029] In some embodiments, in step F, the mass position sensor collects parameter data of each adjustment mechanism in real time, and updates the total mass, moment of inertia matrix and center of mass position vector at preset intervals, so that the inertial parameter terms can dynamically match the working state of the adjustment module, thereby allowing the calculation of gravity translation torque in step C to be adjusted in real time with the change of center of mass position, and simultaneously optimizing the adaptability of hydrodynamic damping torque and additional mass torque in step D, ensuring the real-time response accuracy of the dynamic control model in step G.

[0030] A motion control method for a variable-wing underwater glider based on any of the above-described dynamic modeling methods includes the following steps: a. The initial position, initial velocity and initial attitude data are collected in real time by the positioning sensor and attitude sensor carried by the variable-wing underwater glider. The initial parameters are used as the initial conditions of the dynamic control model (based on the ordinary differential equation system extended from the rigid body kinematic equation) constructed in step G, providing the starting reference for model solution. b. The central controller of the variable-wing underwater glider receives preset mission commands or remote control commands and generates control inputs for the pectoral fin, tail fin and adjustment module. The control inputs include the pitch angle and roll angle of the pectoral fin, the pitch angle of the tail fin, and the buoyancy adjustment and center of mass adjustment of the adjustment module. The control inputs are used to adjust the inertial parameters in the dynamic control model, as well as the input parameters of gravity, buoyancy, gravity translation torque, hydrodynamic damping torque, additional mass torque and fin net external torque. c. Substitute the control input generated in step b into the dynamic control model in step G, and numerically solve the equations of rigid body kinematics in the model and the relationship between various forces and stress moments to obtain the motion trajectory and force data of the variable wing underwater glider, and feed it back to the central controller in step b in real time. d. Based on the motion trajectory and force data fed back from step c, the central controller dynamically adjusts the control input of step b. By optimizing the inertial parameters and the input parameters of various forces and stress torques, it coordinates and balances gravity, buoyancy, gravity translation torque, hydrodynamic damping torque, additional mass torque, and the resultant external force of the fins. This controls the attitude of the pectoral and caudal fins and the working state of the adjustment modules, enabling preset motion modes such as zigzag gliding and spiral gliding.

[0031] In some embodiments, the sawtooth gliding mode includes a pectoral fin pitch adjustment sub-mode. In this sub-mode, the tail fin pitch angle and the pectoral fin roll differential angle are kept at zero. During the descent phase, the synchronous pitch angles of the left and right pectoral fins are set to negative values ​​to generate a downward lift component, and during the ascent phase, they are set to positive values ​​to generate an upward lift component. At the same time, the buoyancy magnitude and center of mass position of the adjustment module are adjusted through the control input in step b, so that gravity, buoyancy, gravity translation torque, hydrodynamic damping torque, additional mass torque and fin lift form a dynamic balance to ensure the stability of the gliding trajectory. This balance state is verified by the numerical solution results in step c.

[0032] In some embodiments, the sawtooth gliding mode includes a tail fin pitch adjustment sub-mode. In this sub-mode, the pectoral fin pitch angle and roll differential angle are kept to zero. The tail fin pitch angle is periodically changed through the control input in step b, adjusting the heading moment term in the resultant external torque of the fin. This works in conjunction with the gravity translation torque, hydrodynamic damping torque, and additional mass torque to achieve heading stability and fine-tuning. The adjustment range of the tail fin pitch angle does not exceed a preset threshold, which is determined by optimization through the numerical solution results in step c, ensuring the convergence of the dynamic control model and avoiding damage to gliding efficiency.

[0033] In some embodiments, the sawtooth gliding mode includes a pectoral fin roll differential adjustment sub-mode. In this sub-mode, the pectoral fin pitch angle and tail fin pitch angle are kept at zero. The roll differential angle of the left and right pectoral fins is periodically set through the control input in step b, changing the lateral torque term in the resultant external torque of the fins. This is combined with the gravity translation torque, hydrodynamic damping torque, and additional mass torque to achieve lateral heading control. Moreover, this differential motion does not interfere with the longitudinal gliding stability and forward speed of the variable-wing underwater glider. Its control effect is verified by the motion trajectory data output in step c.

[0034] In some embodiments, in the spiral gliding mode, the pectoral fin roll angle is fixed by the control input in step b, and the pectoral fin pitch angle, caudal fin pitch angle, and buoyancy and center of mass parameters of the adjustment module are adjusted in coordination to optimize the inertial parameters and the input relationship between various forces and stress torques. Gravity, buoyancy, gravity translation torque, hydrodynamic damping torque, additional mass torque, and fin forces are balanced to actively control the spiral search's rotation radius and period. This parameter adjustment is dynamically optimized based on the force data fed back in step c to ensure that the output of the dynamic control model meets the preset search requirements and achieves efficient and full-coverage observation of the target water area.

[0035] In some embodiments, the origin of the inertial frame in step A is selected from a fixed reference point at the sea level of the target water area. The x-axis points east along the tangent of the Earth's equator, the y-axis points north along the tangent of the Earth's meridian, and the z-axis points vertically downward. The origin of the glider's fixed coordinate system is fixed to the geometric center of the variable-wing underwater glider. The x-axis points to the head along the longitudinal axis of the fuselage, the y-axis points to the starboard side along the transverse axis of the fuselage, and the z-axis is perpendicular to the xy plane and points downward to the fuselage. The origins of the three biomimetic fin fixed systems are respectively fixed to the connection points of the right pectoral fin, left pectoral fin, and tail fin with the fuselage. Their coordinate axes are initially parallel to the glider's fixed coordinate system and deflect synchronously with the pitch and roll movements of the corresponding fins.

[0036] In some embodiments, the total mass of the variable-wing underwater glider in step C is determined by accumulating the masses of structural components, electronic equipment, energy modules, and other parts during the design phase, and calibrated by actual weighing; the displaced fluid volume is obtained by volume integration calculation on the three-dimensional geometric model of the glider body and fins; if the glider has a variable-wing structure, the volume integration result is corrected in real time according to the wing deployment angle; the preset gravitational acceleration adopts the average gravitational acceleration value of the target sea area (e.g., 9.806 m / s²). 2 The fluid density is collected in real time by the density sensor on board, which collects seawater density data of the target water area.

[0037] In some embodiments, the motion speed parameters in step D include the glider's translational speed and rotational angular velocity. The translational speed is calculated differentially from the position data collected by the positioning sensor, and the rotational angular velocity is directly collected by the attitude sensor. The added mass matrix designed based on the glider's geometric symmetry is a diagonal matrix, where the translational added mass corresponds to the independent components in the x, y, and z axis directions, and the rotational added mass corresponds to the independent components around the x, y, and z axes. The matrix elements are pre-solved through CFD (Computational Fluid Dynamics) simulation and stored in the parameter library of the central controller.

[0038] In some embodiments, the preset hydrodynamic coefficients in step E are determined by two methods: first, a fin model test is conducted in the towing tank, and the fluid forces acting on the fins are collected by changing the incoming flow velocity and the angle of attack of the fins, and the hydrodynamic coefficients are obtained by fitting; second, a three-dimensional fluid simulation model of the fins is established, and numerical simulation is performed using the RNG k-ε turbulence model to output the hydrodynamic coefficients under different working conditions. The final coefficient values ​​are determined after comparison and calibration with the test results. The fin surface area integration adopts an adaptive mesh generation method, and the mesh is densified in key areas such as the leading edge and trailing edge of the fins to ensure integration accuracy.

[0039] In some embodiments, the mass position sensor in step F includes a miniature displacement sensor and a mass sensor installed on each mechanism of the adjustment module. The displacement sensor is a laser displacement sensor with a measurement accuracy better than 0.01 mm, which collects the instantaneous position of each mechanism in real time. The mass sensor is a piezoelectric mass sensor with a measurement accuracy better than 0.1 g, which collects the instantaneous mass of each mechanism. The parameter update frequency is set to 10-100 Hz according to the motion response characteristics of the glider to ensure that the inertial parameters can match the dynamic changes of the adjustment module in a timely manner.

[0040] In some embodiments, the model integration in step G adopts a hierarchical coupling strategy. First, the inertial parameters of step F are substituted into the rigid body kinematic equations of step B to update the inertial terms of the equations. Then, the static forces and torques of step C, the dynamic forces and torques of step D, and the net external forces and torques of the fins of step E are sequentially superimposed onto the force terms of the equations according to their priority. Among them, the static forces and torques are the dominant force terms, while the dynamic forces and torques and the fin forces and torques are the correction terms. At the same time, adaptive weight coefficients are introduced to dynamically adjust the weights of each force and torque according to the motion state of the glider (such as uniform gliding or accelerated turning), so that the dynamic control model can adapt to different motion scenarios. This hierarchical coupling strategy breaks through the limitations of the traditional simple superposition of models and improves the adaptability and prediction accuracy of the model.

[0041] In some embodiments, the fluid-structure coupling effect is also considered in the dynamic modeling process. By feeding back the structural deformation data of the glider body and fins to the hydrodynamic calculation stage, the calculation results of hydrodynamic damping force, additional mass force, and net external force and net external moment of the fins are corrected. The structural deformation data is collected in real time by strain sensors installed on the fuselage and fins, or a deformation database is pre-established through structural dynamics simulation. The matching deformation parameters are called according to the motion state to realize the dynamic coupling modeling of multi-physics fields. This solves the problem of traditional models ignoring the influence of structural deformation on hydrodynamics and improves the modeling accuracy.

[0042] In some embodiments, the positioning sensor in step a uses a combination of an underwater acoustic positioning module and an inertial navigation system (INS) for positioning. The underwater acoustic positioning module provides an absolute position reference with an update frequency of 1-10Hz, while the INS outputs continuous position data in real time with an update frequency of 100-500Hz. The two are fused using a Kalman filter algorithm to obtain initial position data with an accuracy better than 0.5m. The attitude sensor uses a microelectromechanical system (MEMS) inertial measurement unit (IMU) to collect the glider's pitch angle, roll angle, yaw angle, and corresponding angular velocity. The data is filtered by moving average to remove noise and ensure the stability of the initial attitude data.

[0043] In some embodiments, the control input generation in step b employs a model predictive control (MPC) algorithm. The central controller, based on preset task instructions (such as target flight trajectory and observation area), combines a dynamic control model to predict the glider's motion state over a future period. With the objective functions of minimizing trajectory tracking error and optimizing energy consumption, it solves for the optimal control inputs of the pectoral fin pitch angle, roll angle, tail fin pitch angle, and adjustment module. The optimal energy consumption objective is achieved by establishing an energy consumption model for the adjustment module and fin drive motor. This model predictive control strategy overcomes the limitations of traditional open-loop control, improving the accuracy and energy efficiency of motion control.

[0044] In some embodiments, the numerical solution in step c adopts the fourth-order Runge-Kutta algorithm. The solution step size is adaptively adjusted according to the response speed of the dynamic control model. When the glider's motion state changes drastically (such as rapid turning), the step size is automatically reduced to 0.001-0.01s. When the motion state is stable (such as uniform gliding), the step size is automatically increased to 0.01-0.1s, balancing solution accuracy and computational efficiency. During the solution process, boundary constraints are checked to ensure that the motion trajectory and force data do not exceed the structural bearing capacity and performance limits of the glider.

[0045] In some embodiments, the control input adjustment in step d employs a fuzzy PID control algorithm. The motion trajectory error (such as position error and attitude error) and error change rate fed back in step c are used as inputs to the fuzzy controller. The proportional coefficient, integral coefficient, and derivative coefficient of the PID controller are dynamically adjusted to optimize the control input. Simultaneously, a multi-modal switching logic is set up. When the glider encounters external disturbances such as water flow interference, it automatically switches to an anti-interference control mode, increasing the adjustment weight of the fin force to quickly offset the disturbance effect. This strategy of combining fuzzy PID control with multi-modal switching improves the robustness of the control system and solves the problem that traditional PID control is difficult to adapt to complex underwater environments.

[0046] In some embodiments, in the zigzag gliding mode and the spiral gliding mode, the control inputs of the pectoral fin and the caudal fin employ a collaborative optimization algorithm. The optimal combination of the pectoral fin pitch angle, roll angle, and caudal fin pitch angle is solved through a genetic algorithm, enabling the glider to achieve the minimum hydrodynamic drag while meeting the trajectory requirements. For example, in the spiral gliding mode, the genetic algorithm uses the turning radius error and period error as constraints and the minimum drag coefficient as the objective to iteratively obtain the optimal combination of the pectoral fin roll angle, pitch angle, and caudal fin pitch angle. This collaborative optimization strategy breaks through the limitations of traditional single fin adjustment and further improves the glider's motion performance and energy efficiency.

[0047] In some embodiments, environmental perception feedback is also introduced during motion control. The central controller collects the water flow speed and direction of the target water area in real time through the onboard water flow sensor, and dynamically corrects the control input based on the water flow data. For example, when downstream navigation is detected, the adjustment amplitude of the fins is appropriately reduced to reduce energy consumption; when upstream or cross current is detected, the force of the fins is increased to ensure the stability of the navigation trajectory. At the same time, based on environmental parameters such as seawater density and temperature, the fluid-related parameters in the dynamic control model are corrected to achieve environmentally adaptive motion control, thus expanding the applicable sea area range of the glider.

[0048] In some embodiments, the additional mass matrix in step D and damping matrix The results were obtained through a combination of CFD simulation and tank testing on a specific glider prototype (overall length 1.5m, wingspan 2.0m, main body diameter 0.2m). The diagonal elements of the additional mass matrix are as follows: , , , , , ,in, Add mass to the translation along the x-axis. Add mass to the y-axis translation. Add mass to the z-axis translation. Add mass to rotate about the x-axis. Add mass to rotate about the y-axis. Add mass for rotation about the z-axis. The coefficient matrix of the linear terms of the damping matrix is... ,unit: or The coefficient matrix of the second-order terms is ,unit: or To obtain specific parameters, a 3D model of the prototype was first built using SolidWorks. Then, the SSTk-ω turbulence model was used in ANSYS Fluent, with the incoming flow velocity set to 0.1-1.0 m / s. The fluid reaction force under step acceleration conditions for each degree of freedom was calculated, and the added mass was obtained through fitting. Subsequently, the prototype was fixed in a circulating water tank, and the fluid forces under different steady-state velocities and small-amplitude oscillating motions were measured using a six-component force sensor. The damping coefficient was then obtained through fitting. This specific parameter acquisition embodiment not only solves the problem of lacking clear guidance due to reliance on expensive simulations or extensive experiments in the background technology, but also achieves a leap from a theoretical framework to a concrete, computable instance of the dynamic model by disclosing a complete and verifiable parameter determination process and typical values.

[0049] In some embodiments, the hydrodynamic coefficient of the fin in step E The method for determining the Reynolds number is as follows: For the pectoral and caudal fin models with airfoil NACA0018, the Reynolds number is... Within this range, calibration was performed using wind tunnel tests (corresponding to aerodynamic similarities) combined with underwater towing tests. During the tests, the lift and drag of the fin model were measured within an angle of attack range of -30° to +30°, and then fitted to the angle of attack. Functions: , ,in, The lift coefficient of the fin is... This is the fin drag coefficient. The angle of attack for the fins. In the Morrison equation, take as and The relevant equivalent values. The fin surface area integral is discretized: each fin is divided into at least 200 quadrilateral elements. The normal velocity on each element is calculated using the rigid body kinematics equations from step B, combined with the fixed position of the element's center in the fin coordinate system. The element force is calculated based on its local angle of attack and the aforementioned coefficient formulas. Finally, the total external force and torque are obtained by summing the forces of all elements. This method proposes for the first time a specific implementation scheme for determining coefficients and calculating integrals for the unsteady, large-range motion characteristics of the fins of variable-wing gliders. It overcomes the shortcomings of traditional linear assumptions for small angles of attack on fixed-wing underwater gliders or the difficulty in practical application of complex fluid-structure interaction models for biomimetic propulsion. Furthermore, it transforms the complex fluid interactions of the fins into a process based on measurable coefficients and executable integration.

[0050] In some embodiments, after the dynamic control model in step G is integrated, its complete state-space equations for numerical solution in step c are in the following specific form: ; where, state vector Including the position of the inertial frame Posture Quaternions , fixed connection linear velocity and angular velocity Control input vector ,in For the piston displacement of the buoyancy adjustment mechanism, To translate the mass block's displacement, For the angular displacement of the rotating mass block, The pitch angle of the left / right pectoral fin. The roll angle of the left / right pectoral fin. The pitch angle of the caudal fin. (Function) The specific expression is derived from the formula in step AF above, and its core is the rigid body dynamics equation described in step G, where the mass matrix... The Coriolis force term is updated by the parameters of steps F and D. Calculated according to the corresponding formula, the force vector This embodiment is the first to explicitly define and structure the variables for incorporating buoyancy adjustment, center of mass adjustment, and multi-fin motion into a unified state-space model, thus solving the problem of "lack of a unified framework for describing nonlinear coupling" in the background technology. This specific model form is the direct basis for numerical solutions (such as step c) and controller design (such as steps b and d), transforming the "dynamic control model" from a concept into an operable computational object.

[0051] In some embodiments, the implementation details of the model predictive control (MPC) algorithm in step b include: setting the prediction time domain. and control time domain Sampling time The objective function of the optimization problem is: ;in, Here is the state error weight matrix. To control the incremental weight matrix, Energy consumption weighting coefficient To control the increment for smooth control, For time-domain indexing, For the reference state vector in Model Predictive Control (MPC), The instantaneous power consumption is estimated based on the current and voltage model of the drive motor. This is the energy consumption weighting coefficient. Constraints include: control input. Physical limitations (such as pectoral fin pitch angle) ), state variables The safety range (such as depth and attitude angle limitations) is defined. Online solutions are obtained using the effective set method or interior point method. This embodiment not only discloses the specific application parameters and considerations (such as energy consumption optimization) of MPC on this particular MIMO underwater platform, but more importantly, it combines predictive control based on the unified dynamics model of this invention with specific motion modes (zigzag, spiral), demonstrating how to utilize the model's foresight to synergistically optimize buoyancy, center of mass, and multi-fin movements, thereby achieving optimal energy efficiency while ensuring trajectory tracking. This breaks through the limitations of traditional open-loop or simple feedback control for underwater gliders, providing a concrete and advanced closed-loop control method to achieve the two major invention objectives of "breaking through maneuverability bottlenecks" and "efficient area search," greatly enhancing control efficiency.

[0052] In some embodiments, a reproducible sawtooth gliding simulation example is provided to verify the effectiveness of the modeling and control methods. The model is initialized using the parameters provided in the above specific embodiment. The initial state is: depth 0 meters, speed 0 m / s, pitch angle 0°. The control objective is to achieve a sawtooth gliding with a period of approximately 100 seconds and a depth variation range of 20 meters. The control input sequence is set as: buoyancy adjustment amount. Switches between ±0.05L in square wave form with a period of 100 seconds; center of mass adjustment. Synchronized with buoyancy adjustment, it switches between ±0.01m to maintain pitch; pectoral fin pitch angle The descent angle is set to -10°, and the ascent angle to +10°; all other fin angles are zero. The fourth-order Runge-Kutta method (step size 0.01 seconds) is used to solve the model for step G. The simulation results will reproduce the following... Figure 5 The typical sawtooth trajectory shown is displayed, and it can output the same trajectory as... Figure 5 Similar attitude angle curves. This embodiment provides a complete chain from specific parameters, explicit initial conditions, detailed control commands to solution settings.

[0053] In some embodiments, the process of updating the mass position sensor data and calculating the inertial parameters in step F specifically involves: assuming the mass of the translational mass block is... Its displacement Measured by a linear encoder, range The mass of the rotating mass block is Equivalent radius of rotation Its angular displacement Measured by a rotary encoder. The central controller reads the data every 0.01 seconds. and Data. According to the formula Calculate the instantaneous centroid position vector ,in Let be the position vector of the translated mass block in the fixed system. Let be the position vector of the rotating mass in the fixed system. To translate the mass of the mass block, To translate the mass block's displacement, For the mass of the rotating mass block, For the angular displacement of the rotating mass block, Let the mass be the glider's base mass. Update the moment of inertia matrix according to the parallel axis theorem. This embodiment discloses the quantitative calculation details of the dynamic influence of the adjustment module on the inertial parameters, solving the simplification problem that traditional models often treat the inertial parameters as constants.

[0054] This solution constructs a dynamic control model through a six-step core process, including defining multiple coordinate systems to complete kinematic modeling, analyzing the static characteristics of underwater gravity and buoyancy, calculating the dynamic effects of hydrodynamic damping and added mass, establishing kinematic and dynamic models of the pectoral and caudal fins, quantifying the influence of adjustment modules on mass and inertial parameters, and integrating and simplifying a system of ordinary differential equations. Finally, by coordinating the control of fin attitude and adjustment modules, multiple composite motion modes are achieved.

[0055] The aim is to systematically address the limitations of traditional platforms and the lack of theoretical support for novel biomimetic platforms. Specific invention objectives include: 1. Breaking through the traditional underwater maneuverability bottleneck: Through an innovative configuration that integrates buoyancy drive, inertial tuning, and biomimetic pectoral and caudal fins, the platform retains its long range advantage while possessing multimodal motion capabilities, overcoming the inherent shortcomings of traditional UG systems such as low speed, large turning radius, and slow dynamic response.

[0056] 2. Establishing a unified and accurate general dynamic modeling framework: A dynamic modeling method is proposed that can simultaneously and uniformly describe the highly nonlinear coupling between buoyancy-driven propulsion, internal mass regulation, and biomimetic fin flapping. This framework aims to bridge the gap in physical modeling between gliding and biomimetic propulsion, providing a theoretical foundation for solving existing modeling problems.

[0057] 3. The motion performance under different fin control modes was systematically simulated, and the quantitative effects of key control input parameters (i.e., pectoral fin pitch angle, roll angle, and caudal fin pitch angle) on overall motion performance (such as gliding trajectory, speed, attitude angular stability, and turning radius) were analyzed.

[0058] The specific technical approach is as follows: Step 1: Perform kinematic modeling for the variable-wing underwater glider: The motion mechanism of underwater gliders is as follows Figure 3 To describe the mathematical model of the manta ray-inspired glider, three coordinate systems were defined, such as... Figure 4 As shown: Inertial frame { I}, Glider fixed coordinate system { E} and bionic fish fin fixation system { }.here i =1, 2, 3 correspond to the right pectoral fin, left pectoral fin, and caudal fin, respectively. i The roll and pitch angles of each fin are respectively determined by... and This indicates. Therefore, from { }arrive{ E The coordinate transformation matrix of} is expressed as: ; in Indicates from { }arrive{ E The coordinate transformation matrix of} Indicates from { E}arrive{ The coordinate transformation matrix of}, with the superscript at the right. T This indicates transpose.

[0059] In this specification, square brackets [] are used to represent matrices, and curly braces {} are used to represent vectors.

[0060] Let the position vector at the center of buoyancy of the torso be: ; in Indicates that the center of buoyancy B is relative to the inertial frame of reference. I The position vector of}, with the top left index I This indicates that the vector is in the inertial frame { I The components of} are expanded. These represent the coordinate components of the position vector in directions 1, 2, and 3, respectively.

[0061] Let the quaternion of the posture at the center of the torso be: ; in Indicates that the center of buoyancy B is relative to the inertial frame of reference. I Quaternion vectors of} These are the quaternion coordinate components.

[0062] Let the velocity vector at the center of buoyancy of the torso be... ; in Indicates that the center of buoyancy B is relative to the inertial frame of reference. I The velocity vector of}, with the superscript at the left. E This indicates that the vector is in the glider's fixed coordinate system { E The components of} are expanded. These represent the coordinate components of the velocity vector in directions 1, 2, and 3, respectively.

[0063] Let the angular velocity vector at the center of buoyancy of the torso be... ; in Indicates that the center of buoyancy B is relative to the inertial frame of reference. I The angular velocity vector of}, with the superscript at the left. E This indicates that the vector is in the glider's fixed coordinate system { E The components of} are expanded. These represent the coordinate components of the angular velocity vector in directions 1, 2, and 3, respectively.

[0064] To describe the motion and attitude of a rigid body, its position, orientation, velocity, and angular velocity are defined as column vectors, as shown below: ; The superscript at the top left indicates the coordinate system (inertial frame) in which the vector is located. I}, Glider fixed coordinate system { E} or biomimetic fish fin fixation system { }).For example, express Therefore, { E The velocity vector is based on the coordinate system.

[0065] The coordinate transformation matrix from the inertial frame to the glider's fixed coordinate system is expressed as: ; in This is the coordinate transformation matrix from the inertial frame to the glider's fixed coordinate system. This is the coordinate transformation matrix from the fixed coordinate system to the inertial system of the glider.

[0066] The relationship between the velocity of a rigid body and its spatial position is expressed as: ; The quaternion derivative of a rigid body with respect to time is related to the angular velocity of the rigid body, specifically expressed as: ; The transformation matrix is: ; Using the hat operator Indicates satisfaction The relation is a 3×3 antisymmetric matrix (this operator is applicable to three-dimensional vectors). a and b For any vector ={ , , Hat Operator A three-dimensional vector The corresponding 3×3 antisymmetric matrix is ​​used for vector cross product operations: ; Therefore, the momentum theorem and angular momentum theorem based on the basis vectors of the rigid coordinate system of a glider are stated as follows: ; ; in This represents the momentum vector of the glider in a rigid, fixed coordinate system. This represents the angular momentum vector of the glider in a rigid, fixed coordinate system. The vector of the net external force. The vector of the net external torque.

[0067] The position vector from the center of buoyancy to the center of mass is defined as... After that, center of mass G velocity vector at point Represented as: ; According to the law of conservation of momentum, the total momentum of a rigid body is independent of the choice of reference point. Therefore, B The momentum at the point is expressed as follows: ; in m The total mass of the glider Center of mass G Momentum at that point.

[0068] relative B The inertial tensor of a point is defined as Then, according to the parallel axis theorem, G The inertial tensor at point A can be written as: ; According to the rigid body angular momentum transfer theorem B The angular momentum at a point can be expressed as: ; in Center of mass G Angular momentum at point Center of mass G The angular velocity vector at the point.

[0069] Ultimately expressed as angular velocity vector and linear velocity vector B Point angular momentum can be written as: ; By rearranging the above formulas, we can obtain the system of dynamic differential equations expressed in a connected coordinate system: ; The superscript "·" indicates the rate of change, such as For floating heart B The rate of change of acceleration at that point For floating heart B The rate of change of angular acceleration at that point.

[0070] For the quality matrix, The angular velocity antisymmetric matrix, The velocity antisymmetric matrix has the following expansion: ; Let the mass change rate matrix be denoted as , and let the mass change rate be . The rate of change of moment of inertia , It can be written as: ; The net external force and net external moment terms consist of gravity, buoyancy, hydrodynamic damping, added mass, and the control force generated by the actuator, and their expressions are as follows: ; in These are gravity and gravitational torque, respectively. These are buoyancy and buoyancy moment, respectively. These are hydrodynamic damping force and torque, respectively. These are the additional mass force and torque, respectively. These are the control force and torque generated by the actuator, respectively.

[0071] Step 2: Analyze underwater statics: Gravity in an inertial frame of reference can be expressed as: ; Where g represents the acceleration due to gravity.

[0072] According to the law of translation of forces, when gravity is translated from point G to point B, the corresponding position vector... A torque will be generated at point B. Therefore, the matrix form of the gravity term can be written as: ; According to Archimedes' principle, buoyancy is related to the volume of fluid displaced by the rigid body. For a fully submersible underwater vehicle, the volume of fluid displaced is equal to its own geometric volume. And this force acts on the center of buoyancy. B Point. Therefore, the buoyancy in the inertial coordinate system can be written as: ; in Defined as the density of the fluid; Therefore, the matrix form of the buoyancy term can be written as: ; Step 3: Analyze underwater dynamics: Hydrodynamic damping force comprises the force and torque generated by translational and rotational velocities. In this invention, coupling terms are ignored, and it is assumed that the force (or torque) in a certain direction is only related to the velocity (or angular velocity) in the same direction. Therefore, the hydrodynamic damping force can be written as: ; In the formula, Here is the damping matrix. The matrix contains linear damping terms. and higher order damping terms The coefficients of the linear terms are proportional to the velocity, and the coefficients of the second-order terms are proportional to the square of the velocity. These coefficients are obtained through CFD simulation and tank testing calibration. In this invention, only the second-order terms among the higher-order terms are considered. ; in , , , , and The coefficients of the linear terms in each direction, , , , , and These are the coefficients of the second-order terms in each direction.

[0073] When an underwater vehicle accelerates or decelerates, the previously stationary water around it is also accelerated, generating a reaction force and a reaction torque. These forces and torques are called additional mass forces. Based on the ideal fluid assumption, additional mass forces and additional mass torques can be expressed as: ; In the formula, Let be the added mass matrix. Based on the geometric symmetry of the variable-wing glider robot, this added mass matrix can be written in the following form: ; in , , , , and The coefficient of the diagonal term. and The coefficients are for the off-diagonal terms.

[0074] Step 4: Analyze the kinematics and dynamics of the pectoral and caudal fins: During the motion, assume the relative velocity between the fins and the rigid body of the variable-wing glider is zero. Let... F For the first i For any point mass on a pectoral fin, the velocity of that point mass is generated by the combined translation and rotation of the rigid body, in the fin coordinate system { Under}, its expression can be written as: ; in, , , for{ } B The position vector from point F to point F can be written as: ; in express{ E} B Click M The position vector of a point express{} M Click F The position vector of a point.

[0075] in: ; According to Morrison's equations, the force exerted by a fluid on a micro-element surface can be expressed as: ; In the formula Hydrodynamic drag coefficient, It is the normal velocity of particle F on the fin surface.

[0076] Acting on the fins and relatively B The resultant external force and resultant external torque of the hydrodynamic drag at a point can be obtained by considering the surface area of ​​the fin. A The integral yields: ; ; The above expression can be represented in the fixed coordinate system of the glider: ; In the dynamic model, the right pectoral fin, left pectoral fin, and caudal fin jointly provide the control force and control torque, which can be expressed as: ; Step 5: Model the adjustment module: The influence of adjustment modules (such as translating mass blocks, rotating mass blocks, and water intake / drainage devices) on the dynamic system is reflected in changes in the total mass, center of mass, and moment of inertia, thus affecting the inertia matrix. and its derivative The changes. For this type of adjustment module that does not change the displacement volume, this section proposes a general modeling method.

[0077] Assuming the object is not equipped with a center of mass adjustment mechanism and a buoyancy adjustment mechanism, its total mass is denoted as... The position vector pointing from the center of buoyancy to the center of mass is denoted as The moment of inertia matrix is ​​denoted as The instantaneous mass of the k-th regulating mechanism With instantaneous position vector The definition is as follows: ; in These are the instantaneous position vector components in each direction.

[0078] The total mass of an object can be expressed as: ; in This represents the change in mass.

[0079] object relative to B The moment of inertia matrix of a point can be expressed as: ; in This represents the change in moment of inertia.

[0080] The position vector from the center of mass to the center of buoyancy can be expressed as: ; The rate of change of the moment of inertia can be expressed as: ; The specific expressions for each component are as follows: ; The rate of change of the centroid position vector is expressed as: ; Step Six: Constructing and Simplifying the Dynamic Control Model: The spatial motion model of the variable-wing glider is expressed as a system of ordinary differential equations consisting of kinematic models: ; Its dynamic model is as follows: ; Its initial conditions should be given as follows: ; By setting control inputs for the pectoral fin, caudal fin, and adjustment module, numerical solutions can be performed on the system to obtain data on the movement trajectory, force, and other parameters that change over time.

[0081] Through specific control methods and corresponding numerical simulations, this invention fully verifies its feasibility and superiority. (1) Feasibility verification: The embodiments demonstrate in detail the specific control command sequence from basic zigzag gliding to complex spiral gliding, and simulation was carried out based on a rigorous 6-DOF dynamic model. All modes achieved stable and controllable motion trajectories, proving that the method is feasible in terms of both physical principles and engineering implementation.

[0082] (2) The beneficial effects are prominent: Diverse movement modes: By simply adjusting the attitude of a pair of pectoral fins and a tail fin, multiple optimized gliding modes and three-dimensional spiral modes can be derived from basic gliding, greatly improving the underwater robot's mission adaptability.

[0083] Motion performance optimization: Through the "pectoral fin pitch motor adjustment mode" example, it was found that there exists an optimal pectoral fin pitch adjustment amplitude (±10°) that achieves the best dynamic stability and propulsion efficiency. This provides clear guidance for parameter tuning in practical engineering.

[0084] (3) Control decoupling: Simulation results of the “pectoral fin roll motor adjustment mode” embodiment show that the pectoral fin roll motion has little effect on longitudinal gliding performance. This near-decoupling characteristic allows designers to design longitudinal (buoyancy, pitch) and lateral (roll, yaw) control laws relatively independently, simplifying the design of the control system.

[0085] (4) High-efficiency area search capability: The “spiral gliding mode” embodiment shows that by setting different fixed pectoral fin roll angles, the density (circling radius) and speed (circling period) of the spiral search can be actively controlled, realizing the high-efficiency and full-coverage observation capability of the target water area, which is not available in traditional underwater gliding that can only perform vertical profile gliding.

[0086] In one specific embodiment, the present invention is applied using the manta ray, a gliding machine based on a biomimetic variable wing.

[0087] 1. Overview of the Implementation Examples: The gliding manta ray mainly consists of a sealed pressure-resistant shell, an internal buoyancy adjustment unit, a center of gravity adjustment unit, a pair of bionic pectoral fins, a bionic tail fin, a central controller, and a sensor system. The bionic pectoral fins are controlled by independent pitch / roll drive motors (corresponding to the pectoral fin pitch angle). Differential roll angle of pectoral fins The bionic tail fin is controlled by an independent pitch drive motor (corresponding to the tail fin pitch angle). This method can be used as an active control surface to regulate hydrodynamics. The core of this method lies in the coordinated control of the attitude of the pectoral and caudal fins, based on the zigzag gliding achieved by buoyancy, thereby realizing a variety of efficient and stable compound motion modes, including zigzag gliding and spiral gliding.

[0088] 2. Connection relationship: The electrical connections of the biomimetic variable-wing gliding manta ray are as follows: the central controller is connected to the buoyancy adjustment unit, the center of gravity adjustment unit, and the left / right pectoral fin drive motors (to achieve pitch). With roll differential (Motion), tail fin drive motor (to achieve pitch) The system is electrically connected to motion sensors, depth sensors (IMUs), and underwater acoustic communication modules. The central controller generates control signals for each actuator based on preset tasks or remote commands.

[0089] 3. Specific implementation steps: 3.1 Specific implementation of the zigzag gliding mode: A complete cycle of zigzag gliding consists of two phases: descent and ascent. This example demonstrates three optimized zigzag gliding modes achieved by adjusting different fins: (a) Pectoral fin pitch adjustment mode: Control method: Maintain the pitch angle of the tail fin throughout one gliding cycle. =0°, pectoral fin roll differential angle =0°, only periodically changing the synchronous pitch angle of the left and right pectoral fins. During the descent phase, set A negative value (e.g., -10°) causes the pectoral fins to generate a downward lift component; during the ascent phase, [the following is set / adjusted / adjusted]... When the value is positive (e.g., +10°), an upward lift component is generated. At the same time, the buoyancy unit and the center of mass adjustment unit work according to a preset pattern (e.g., when descending, oil is discharged and the center of mass moves forward; when ascending, oil is drawn in and the center of mass moves backward).

[0090] Dynamic processes and effects: such as Figure 5 (corresponding to pectoral fin) As shown in the simulation diagram, in this mode Gliding trajectories at different amplitudes (0°, ±10°, ±20°) It exhibits typical sawtooth characteristics; the corresponding pitch angle curve shows: when At ±20°, the system exhibits smaller attitude oscillation amplitude, faster stabilization speed, and better horizontal forward speed, thus achieving a better balance between longitudinal stability and propulsion efficiency.

[0091] (b) Tail fin pitch adjustment mode: Control method: Maintain the pectoral fin posture ( =0°、 =0°), periodically changing the pitch angle of the caudal fin. .

[0092] Dynamic processes and effects: such as Figure 6 (corresponding to the tail fin) As shown in the simulation diagram, When different amplitudes (0°, ±10°, ±20°) are taken, the sawtooth period of the gliding trajectory varies. The amplitude increases and changes; the corresponding pitch angle curve shows that as it increases... The adjustment range will lead to a decrease in heading speed, an increase in system pitch oscillation, and a longer settling time—compared to =±10°, At an angle of ±20°, attitude fluctuations are more pronounced. This example illustrates that the tail fin primarily serves for directional stabilization and fine-tuning; excessive tail fin deflection can impair gliding efficiency.

[0093] (c) Differential roll adjustment mode of pectoral fins: Control method: Maintain the pitch angle of the pectoral fins Caudal fin pitch angle The roll differential angle of the left and right pectoral fins is set periodically. (like & , & and & combination).

[0094] Dynamic processes and effects: such as Figure 7 (corresponding to pectoral fin) As shown in the simulation diagram, adjust At that time, gliding trajectory (three-dimensional) The curves show a serrated feature that extends laterally; the corresponding roll angle and yaw angle curves show that this mode has a slight impact on the pitch stability and forward speed of longitudinal gliding, verifying that the pectoral fin roll differential motion can be used as an independent lateral / heading control degree of freedom without interfering with the basic gliding profile, providing a design basis for multi-mode composite motion.

[0095] The embodiments described above are for illustrative purposes only and are not intended to limit the invention. Therefore, any changes in numerical values ​​or substitutions of equivalent elements should still fall within the scope of this invention.

Claims

1. A dynamic modeling method for a variable-wing underwater glider, characterized in that, include: A. Define an inertial frame, a glider fixed coordinate system, and three biomimetic fin fixed frames. Implement motion parameter transformation through preset coordinate transformation rules, and output the coordinate system and transformation rules. B. Based on the momentum theorem and the angular momentum theorem, input the coordinate system and transformation rules of step A, and derive the rigid body kinematic equations of the variable-wing underwater glider. C. Input the total mass of the variable-wing underwater glider, the preset gravitational acceleration, the fluid density and the volume of displaced fluid, and calculate and output the static forces and torques, including gravity, buoyancy and gravitational translation torque; D. Based on the ideal fluid assumption and the geometric symmetry of the glider, input the motion velocity parameters and calculate the output dynamic forces and torques, which include hydrodynamic damping forces, additional mass forces, and stress torques; E. Input the biomimetic fin fixation system of step A, the rigid body kinematic equation of step B, and the preset hydrodynamic coefficients. Output the net external force and net external torque of the fin through the Morrison equation and the fin surface area integral. F. Input the instantaneous mass and instantaneous position of each mechanism in the adjustment module, and calculate the output inertial parameters using the parallel axis theorem. The inertial parameters include the total mass, the moment of inertia matrix relative to the center of buoyancy, the rate of change of the moment of inertia matrix, the position vector of the center of mass pointing to the center of buoyancy, and the rate of change of the position vector of the center of mass. G. Input the rigid body kinematic equations from step B, the static forces and moments from step C, the dynamic forces and moments from step D, the net external forces and moments of the fins from step E, and the inertial parameters from step F, and integrate them to output the dynamic control model.

2. The dynamic modeling method for a variable-wing underwater glider according to claim 1, characterized in that, The coordinate transformation rules in step A are defined by the origin mapping and the coordinate axis rotation angle in advance, which ensures the accuracy of motion parameter transformation in step B and provides a unified benchmark for the integration of static forces and torques, dynamic forces and torques, and net external forces and torques of the fins in the multi-coordinate system of step G.

3. The dynamic modeling method for a variable-wing underwater glider according to claim 1, characterized in that, The additional mass matrix in step D adopts a geometrically symmetric design, retaining only the translational and rotational uncoupled terms, which simplifies the calculation process of dynamic forces and moments, reduces the computational load of the dynamic control model in step G, and improves the model solution efficiency.

4. The dynamic modeling method for a variable-wing underwater glider according to claim 1, characterized in that, The fin surface area integral in step E covers the entire effective action surface of the right pectoral fin, left pectoral fin, and caudal fin, ensuring that the fin forces and torques fully reflect the fluid action effect. This works in conjunction with the static forces and torques in step C and the dynamic forces and torques in step D to optimize the attitude response description accuracy of the model in step G.

5. The dynamic modeling method for a variable-wing underwater glider according to claim 1, characterized in that, Step F involves real-time parameter acquisition using a mass position sensor, periodic updating of inertial parameters, and synchronous adjustment of the adaptability of static forces and torques in step C and dynamic forces and torques in step D, ensuring the real-time response performance of the model in step G.

6. A motion control method for a variable-wing underwater glider, characterized in that, The dynamic modeling method for the variable-wing underwater glider according to any one of claims 1-5, wherein the motion control method for the variable-wing underwater glider includes: a. Collect the initial position, velocity, and attitude data of the variable-wing underwater glider and output them as initial conditions for the dynamic control model; b. Receive preset or remote control commands and output control inputs for the pectoral fin, caudal fin and adjustment module. The control inputs include the pitch angle and roll angle of the pectoral fin, the pitch angle of the caudal fin, and the buoyancy adjustment amount and center of mass adjustment amount of the adjustment module, which are used to adjust the inertial parameters of the model and the parameters of static force and torque, dynamic force and torque, and fin force and torque. c. Input the control input from step b into the dynamic control model, output the motion trajectory and force data through numerical solution, and feed it back to the control terminal; d. Input the feedback data from step c, dynamically adjust the control input from step b, balance the static forces and torques, dynamic forces and torques, and the net external forces and torques of the fins, and output the coordinated control commands for the pectoral fins, caudal fins, and adjustment modules to achieve the preset motion modes of zigzag gliding and spiral gliding.

7. The motion control method for the variable-wing underwater glider according to claim 6, characterized in that, The sawtooth gliding mode includes a pectoral fin pitch adjustment sub-mode. This sub-mode sets the pectoral fin pitch angle and the buoyancy and center of mass parameters of the adjustment module through the control input in step b, so that the static forces and torques, dynamic forces and torques, and the resultant external forces and resultant external forces rectangles of the fins solved in step c are in dynamic equilibrium, ensuring the stability of the gliding trajectory.

8. The motion control method for the variable-wing underwater glider according to claim 6, characterized in that, The sawtooth gliding mode includes a tail fin pitch adjustment sub-mode. This sub-mode adjusts the tail fin pitch angle in step b and optimizes the heading moment term in the resultant external torque of the fin in step c. It works in conjunction with static forces and moments, and dynamic forces and moments to achieve fine-tuning of the heading. The adjustment range is determined by the solution result of step c.

9. The motion control method for the variable-wing underwater glider according to claim 6, characterized in that, The zigzag gliding mode includes a pectoral fin roll differential adjustment sub-mode. This sub-mode sets the roll differential angle of the left and right pectoral fins in step b, changes the lateral torque term in the resultant external torque of the fins in step c, and achieves lateral control by combining static force and torque, dynamic force and torque. The control effect is verified by the trajectory data in step c.

10. The motion control method for the variable-wing underwater glider according to claim 6, characterized in that, The spiral gliding mode fixes the pectoral fin roll angle and adjusts the pectoral fin pitch angle, caudal fin pitch angle, and buoyancy and center of mass parameters of the adjustment module in step b. It optimizes the relationship between static force and torque, dynamic force and torque, and net external force and net external torque of the fin in step c, controls the circling radius and period, and achieves efficient and full-coverage observation of the target water area.

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