636 results about "Attitude control" patented technology

The invention belongs to the technical field of coupling alignment, and particularly relates to an intelligent auxiliary system for coupling alignment based on dual-laser displacement and an MEMS gyroscope, which adopts a mode of cooperative work of an active stable attitude measurement module and a space reference beacon module to establish a dynamic stable measurement basis which is not influenced by barring operation and environmental disturbance. The micro attitude change of the measuring device can be sensed and actively compensated in real time in the measuring process, it is ensured that laser displacement data at all angles are collected in the same absolute space coordinate system, and the high consistency and accuracy of multi-point measurement data are ensured. And then fusing the attitude feedback signal and the attitude reference signal by using an intelligent resolving module to generate an attitude control instruction, and processing displacement measurement data acquired by a double-laser displacement sensor after the attitude is stable to resolve a centering deviation parameter, thereby being beneficial to improving the efficiency, precision and automation level of coupling alignment work.

The invention provides a satellite weak and small target on-orbit observation system and method based on intelligent closed-loop feedback, and the system comprises a detection module which carries out the image enhancement and time sequence consistency enhancement of an infrared image, obtains an enhancement feature, and obtains a candidate target set based on the enhancement feature; the tracking module is used for carrying out target matching in the search area; when the matching succeeds, the candidate position is used as an observation value, and the observation value is input into a Kalman filter to obtain a target state vector; when the matching fails, taking a prediction state of the Kalman filter as a target state vector, expanding a search window by taking a prediction position as a center, and executing re-identification; the control module is used for mapping the target state vector into an attitude error and generating a control instruction by adopting a single-neuron self-adaptive PID (Proportion Integration Differentiation) controller; and the closed-loop scheduling module is used for dynamically adjusting operation parameters of at least one module according to the execution error and the detection confidence coefficient. According to the invention, the continuous tracking precision and attitude control stability of the weak and small target are improved.

The invention discloses an input-limited and coupled-output-limited quadrotor unmanned aerial vehicle motion control method and system based on an extended state observer, and the method comprises the steps: building a quadrotor unmanned aerial vehicle kinetic model, and carrying out the modeling and decoupling of lumped disturbance. And designing an extended state observer to estimate the position, speed and lumped disturbance of the unmanned aerial vehicle. Coupling output constraint is converted into time-varying non-coupling constraint through the rotation matrix, and tracking errors are defined accordingly. And designing a position controller and an attitude controller based on the error and an estimated value of the observer, and generating expected thrust and expected angular velocity. An input limited function and an auxiliary variable are introduced, and the saturation problem of the controller is solved. The system comprises a dynamic modeling and disturbance decoupling module, a state estimation module, an output constraint processing module, a position control and attitude control module and an input saturation compensation module. According to the invention, the trajectory tracking precision, robustness and constraint processing capability of the unmanned aerial vehicle are significantly improved.

The invention relates to the technical field of robots, in particular to a robot arm grabbing control method and system based on multi-sensor data analysis, and the method comprises the steps: obtaining the spatial position and morphological feature data of a grabbing area and surrounding objects, and the local contact state data of a target object; the internal stress distribution and the local deformation state of the flexible object in the grabbing process are predicted in real time; generating a clamping control instruction based on a prediction result, and dynamically planning a motion path and a grabbing posture in a grabbing process by combining adjacent object disturbance modeling and disturbance risk quantification to form an executable grabbing track and grabbing posture control instruction; and meanwhile, a microcosmic contact state model is constructed, the grabbing process is dynamically adjusted in combination with clamping control and a grabbing track, and real-time updating of local grabbing force and action is achieved. Through multi-sensing data fusion and dynamic modeling, the local stress change of the flexible object can be effectively sensed, and damage and sliding are inhibited.

The invention relates to the technical field of dynamic object pose recognition and mechanical arm grabbing control algorithms, and discloses a dynamic object pose recognition and mechanical arm grabbing control algorithm. The framework comprises a multi-source heterogeneous sensing fusion module, a motion state joint estimation engine, a grabbing feasibility online evaluator and a rolling time domain grabbing controller, and low-delay collaboration is achieved through unified state space modeling and event-driven scheduling. Wherein the sensing module fuses RGB-D and inertial data to output a six-degree-of-freedom pose with covariance, the estimation engine adopts self-adaptive unscented Kalman filtering to recursion a complete motion state, the evaluator combines dynamic constraints to screen feasible grabbing postures, and the controller solves an optimal joint trajectory with obstacle avoidance constraints on line based on a self-adaptive target trajectory. And feedforward compensation is introduced to suppress dynamic disturbance. According to the technical scheme, the real-time performance is guaranteed, and meanwhile the grabbing success rate and robustness of high-speed, non-uniform-speed and sudden turning dynamic objects are remarkably improved.

The invention provides an intelligent unmanned aerial vehicle autonomous control system and method based on multi-sensor fusion, and relates to the technical field of unmanned aerial vehicle attitude control. Determining an attitude decision instruction of the intelligent unmanned aerial vehicle during autonomous flight path decision, and determining a swing control quantity of the intelligent unmanned aerial vehicle during autonomous flight attitude adjustment according to the attitude decision instruction; performing compensation identification on the calibrated obstacle avoidance condition and the attitude planning information of the intelligent unmanned aerial vehicle to obtain an attitude compensation strategy expected to be allocated by each actuator in the intelligent unmanned aerial vehicle, and determining a planned attitude angle of the intelligent unmanned aerial vehicle during autonomous switching of a flight mode according to the attitude compensation strategy; and according to the swing control quantity and the planned attitude angle, carrying out deviation correction control on the course of the intelligent unmanned aerial vehicle when the intelligent unmanned aerial vehicle executes the autonomous flight task. According to the invention, full-process cooperative control can be carried out on the attitude stability of the unmanned aerial vehicle under the support of multi-sensor data, so that the accuracy of autonomous flight of the intelligent unmanned aerial vehicle is improved.

The invention provides a flying robot control method and device based on force feedback and a medium, and the method comprises the steps: deploying a six-dimensional force torque sensor at an operation end effector of a flying robot, and obtaining and screening effective torque data in real time to obtain a force error signal; a compensation layer based on the Lyapunov self-adaptive law is utilized, the total disturbance is cooperatively estimated in combination with double observers, and the disturbance serves as a feed-forward quantity to be injected into an attitude controller; and calculating the adjustment amount according to the target impedance model and the force error, and generating an execution mechanism control instruction. According to the technical scheme provided by the invention, stable control of air interaction operation can be realized, and the anti-disturbance capability and interaction force control precision of the flying robot are effectively improved.

The invention discloses an unmanned aerial vehicle attitude control method for complex scene cruise, and belongs to the technical field of unmanned aerial vehicle attitude control. The invention aims to solve the problems that an existing unmanned aerial vehicle attitude control method is insufficient in robustness under complex environment disturbance, unreasonable in safety redundancy distribution and lack of foresight and adaptive ability. Therefore, the invention provides an unmanned aerial vehicle attitude control method, and the method comprises the steps: dynamically up-regulating or down-regulating the long-term disturbance baseline and risk level of each grid and the neighborhood thereof through the consistency deviation between the attitude error standard deviation in a certain time window and the expected error of a corresponding gear, enabling the disturbance atlas and risk distribution to be continuously self-corrected along with the flight data, and achieving the unmanned aerial vehicle attitude control. Therefore, a real environment can still be accurately reflected after long-term operation, risk identification misjudgment and control strategy mismatching caused by aging or distortion of an environment model are reduced, and attitude control robustness and overall task completion efficiency of the unmanned aerial vehicle during cruising in a complex scene are improved.

The invention relates to an unmanned aerial vehicle attitude control method based on motor state disturbance compensation, belongs to the technical field of unmanned aerial vehicle control, and solves the problems of hysteresis and limited control effect of an existing unmanned aerial vehicle attitude control method. The position controller calculates to obtain expected tension, a roll angle and a pitch angle; the attitude feedback controller calculates a feedback torque according to the expected attitude, the actual Euler angle and the body angular velocity; the load identification module calculates an estimated disturbance torque based on the target rotating speed, the actual rotating speed and the current of each motor; the feedforward neural network module adopts a trained RBF neural network to calculate torque residual error estimation, and torque synthesis is carried out to obtain a torque feedforward compensation amount; adding the feedback torque and the feed-forward compensation amount to obtain a total control torque; and the mixing controller calculates the target rotating speed of each motor according to the expected tension and the total control torque, and finally the control distributor drives the motors to execute. The attitude stability and the control response speed of the unmanned aerial vehicle in the wind disturbance environment are remarkably improved.

The invention relates to the field of control, in particular to a flight attitude control method and system for an unmanned aerial vehicle, and the method comprises the steps: obtaining an expected attitude angle instruction and actual attitude angle feedback of the unmanned aerial vehicle, calculating an attitude angle error, employing a tracking differentiator to calculate a transition process for the expected attitude angle instruction, and enabling a tracking rate factor to achieve the control of the flight attitude of the unmanned aerial vehicle when the instruction is subjected to step change. Based on initial attitude angle error setting, instruction smooth transition is ensured, based on a transition signal output by a tracking differentiator and an estimated value of an expansion state observer, a basic control quantity is generated through nonlinear state error feedback, and control gain is adjusted on line according to a lumped disturbance amplitude. And predicting the lumped disturbance historical sequence by using a grey prediction model, calculating a predicted value at a future moment, and carrying out algebraic summation on the basic control quantity, a compensation component of the lumped disturbance predicted value and a gyroscopic moment decoupling component to generate an attitude control moment signal so as to realize stable flight of the unmanned aerial vehicle.

The invention provides an unequal-span steel box girder swivel construction measuring point arrangement and monitoring method, and relates to the technical field of steel box girder construction, and the method comprises the following construction steps: S1, installing a reference system; s2, establishing a central reference; s3, monitoring the turning process; s4, carrying out falling position control and fine adjustment; s5, measuring point arrangement and synchronous monitoring; s6, data analysis and feedback control; and S7, confirming and recording in place. According to the invention, through combination of optical reference and multi-point synchronous monitoring, attitude control and alignment fine adjustment of the whole rotation process are realized, and high-precision in-place of the box girder under complex conditions is ensured.

The invention relates to the technical field of road condition simulation driving simulation, in particular to a vehicle driving simulation system and method suitable for a road condition simulation test, and the method comprises the steps: obtaining various instruction signal amplitudes for simulating the operation behavior of a driver and the inclination angle data of a six-degree-of-freedom motion platform; extracting inclination angle high-frequency and low-frequency sets, and obtaining high-frequency motion inhibition degrees of all acquisition periods; calculating a motion gain characteristic value of each instruction signal, obtaining a scaling characteristic value of each instruction signal in combination with the high-frequency motion suppression degree, and adjusting a time-varying proportionality coefficient of each instruction signal in a classical washout algorithm; and the target extension amount of each electric cylinder of the six-degree-of-freedom motion platform is obtained by utilizing a classic washout algorithm and combining a six-degree-of-freedom motion platform pose inverse solution algorithm, and the pose of the six-degree-of-freedom motion platform is controlled. According to the invention, the vehicle driving simulation precision can be improved.

The invention relates to the field of space irradiation tests, and provides a multi-degree-of-freedom pose adjusting device for a space irradiation test. The device is formed by sequentially connecting a supporting base, a shear type lifting mechanism, a linear translation mechanism and a pitching mechanism, and can realize accurate translation of a test sample in X, Y and Z axis directions and pitching turnover around a horizontal axis in a vacuum environment. The device provided by the invention is compact in structure and high in adjustment precision, is especially suitable for performing multi-dimensional attitude control on a test sample in a vacuum irradiation environment, and remarkably improves the flexibility and stability of sample positioning and attitude adjustment in a space irradiation test; the problems of motion coupling, precision loss, large occupied space and the like existing in a traditional single-shaft or double-shaft mechanism are solved, high-precision multi-degree-of-freedom motion control under the complex vacuum environment is achieved, and the high-precision multi-degree-of-freedom motion control mechanism has the remarkable advantages of being high in structural integration degree, high in adaptability, high in repeated positioning precision and the like.

The invention discloses an attitude control method and system for continuously locking a ground target by an unmanned aerial vehicle, and the method comprises the steps: obtaining a target position and an unmanned aerial vehicle attitude data stream, carrying out the coordinate transformation to generate a target attitude relation identifier, and carrying out the deviation vector decomposition to form a visual axis deviation feature set; disassembling the image into a fast and slow response chain through attitude mapping processing, repairing a fracture node, constructing an attitude correction track, extracting a control feature mode, generating a response feature factor, and constructing an attitude compensation constraint matrix; frequency domain decomposition and cross coupling calculation are carried out on the optical axis deviation feature set to determine the coupling correlation degree, and a superposition disturbance sequence is identified and dynamically reconstructed to generate a compensation gain sequence; executing stability evaluation to determine time sequence distribution, identifying abnormal disturbance characteristics and extracting key moment control characteristics; the constraint matrix and the gain sequence are fused to generate a fusion control law, a dynamic priority control coefficient is determined, a target continuous locking attitude control instruction is output, and continuous and stable locking of the moving target is achieved.

The invention discloses a multi-degree-of-freedom flying mechanical arm aerial operation stability control method and system, and relates to the technical field of aircraft control. The method comprises the steps that attitude information and current contact force of a flying mechanical arm are obtained; constructing an attitude control model according to the attitude information; constructing an impedance model according to expected inertia, damping, a stiffness matrix, a tail end pose, a tail end speed, a tail end acceleration, a tail end reference trajectory, the current contact force and the expected contact force; calculating a joint control moment according to the impedance model; calculating a comprehensive performance index according to the attitude control model and the impedance model; and according to the comprehensive performance index and the joint control torque, stable control over the flying mechanical arm is conducted. The attitude control model and the impedance model can be combined to calculate the comprehensive performance index so as to adjust the control parameters of the flying mechanical arm, so that stable control of the flying mechanical arm is realized, and the control precision and the flight stability are improved.

The application belongs to the field of shaft coupling alignment technology, in particular to a shaft coupling alignment intelligent auxiliary system based on double laser displacement and MEMS gyroscopes, which adopts a mode of cooperative work of an active stable attitude measurement module and a space reference beacon module to establish a dynamic stable measurement reference unaffected by turning operation and environmental disturbance. The system can perceive and actively compensate for the slight attitude change of the measurement device in real time during the measurement process, ensure that the laser displacement data under all angles are collected under the same absolute space coordinate system, ensure the high consistency and accuracy of the multi-point measurement data, then use an intelligent calculation module to fuse the attitude feedback signal and the attitude reference signal to generate an attitude control instruction, and process the displacement measurement data collected by the double laser displacement sensors after the attitude is stabilized to calculate the centering deviation parameters, which helps to improve the efficiency, accuracy and automation level of the shaft coupling alignment work.

To provide a drive module capable of efficiently performing attitude control of a moving body, and a moving body including the same.SOLUTION: According to an aspect of the present invention, there is provided a driving module including a wheel configured to rotate about a first rotation axis that is a virtual straight line extending in a first direction, a first frame having a fixed height relative to the wheel, a second frame configured to move relative to the first frame, a link unit configured to connect the first frame and the second frame, and a posture adjuster configured to adjust a posture of the driving module by controlling a movement of the link unit to change a position of the second frame relative to the first frame.SELECTED DRAWING: Figure 1

The invention discloses a city security patrol unmanned aerial vehicle fusing edge agent decision, relates to the crossing field of unmanned aerial vehicle technology and city security technology, and provides the following scheme that the city security patrol unmanned aerial vehicle comprises a vehicle body and further comprises rotor wing assemblies arranged on the periphery of the exterior of the vehicle body in an array mode and used for achieving flight attitude control of the unmanned aerial vehicle; the sensing module is arranged at the top of the machine body. According to the invention, localized processing and decision-making of security and protection data are realized, dependence on a remote control center is not needed, abnormal event identification and processing instruction generation time is shortened to millisecond level, processing lag caused by communication delay is effectively avoided, patrol paths and decision-making strategies can be automatically adjusted according to on-site environments, waiting for remote instructions is not needed, and operation is simple and convenient. The method is suitable for complex and changeable urban security protection scenes, the edge computing power of the unmanned aerial vehicle is fully utilized through cooperative interaction between the edge intelligent agents, idle equipment resources are avoided, the algorithm precision is continuously optimized through an autonomous learning function, and the long-term security protection patrol effect is improved.

The present application relates to high-altitude hoisting technical field, disclose a kind of hoisting operation control method, comprising the following steps: one, real-time acquisition the state information of tower material to be hoisted;Two, construct multi-source data fusion model to process the state information of tower material to be hoisted, and obtain the high-precision state information estimate of tower material to be hoisted;Three, based on the layout information of pedestal, hoist arm and sling, establish fixed coordinate system;Four, based on the elastic deformation of tower material to be hoisted and crane's sling, gravity and visual feedback information, establish the differential equation of sling shape;Five, predict the state trajectory of tower material to be hoisted in future time window, design model predictive controller, with the error between tower material desired pose and actual pose minimization as goal, solve the optimal control parameter of tractor;The present application is aimed at hoisting tower material state feedback demand, installs multiple sensors in hoist arm end, hook and other positions, constructs tower material closed-loop attitude control algorithm, realizes the accurate control of tower material attitude.

The application discloses a rocket attitude self-adaptive control method and system based on reinforcement learning, and belongs to the technical field of rocket attitude control. The method constructs an adaptive controller for controlling the rocket attitude through a backstepping method, and the adaptive controller is used for realizing the self-adaptation of the rocket to unknown disturbances based on an Actor-Critic (AC) of reinforcement learning, so that the system can rapidly converge to a desired state, unknown nonlinear observation is realized without depending on an internal model, and the tracking control of the rocket attitude is realized.

The invention discloses a flexible picking motion planning method and system, a product, equipment and a storage medium, belongs to the technical field of mechanical arm humanoid flexible picking, and solves the problems that in the prior art, when single fruits at different positions and postures are picked, flexible track adjustment and posture control picking planning cannot be performed, and the picking efficiency is high. Therefore, the pose requirement in the picking scene conflicts with joint execution, and the adaptability to complex tracks is weak. Collecting demonstration data; constructing a strategy function, inputting a current mechanical arm tail end pose state, obtaining mechanical arm action probability distribution, and generating a current execution action; constructing a multi-dimensional perception neural reward network, and calculating a current total reward; constructing a value function, and obtaining the value advantage of the current execution action in combination with the current total reward; value loss and strategy loss are calculated, and after the strategy function and the value function are updated, the mechanical arm is adopted to execute the current action. The device is used for realizing smooth picking of fresh fruits.

The application discloses a flying car, a control method and system thereof, and the control method receives a mode selection instruction of the flying car, and when it is determined according to the mode selection instruction that the flying car is switched from a ground driving mode to an air flight mode, it is indicated that the control mode of the flying car needs to be changed, and then the controlled objects of a steering device and a gear shifting device are reconfigured so that the steering device controls the yaw angle of the flying car and the gear shifting device controls at least the pitch angle of the flying car. Since the steering device and the gear shifting device are more in line with the control habits of the driver, the control logic is closer to the control perception of the driver, and when the steering device and the gear shifting device are controlled according to the flight control instruction, the flight attitude control of the flying car in the air flight mode is easier to control, which is beneficial to the driver to adapt to the control in the air flight mode, and the controllability of the flying car in the flight control is improved.

This invention addresses the common failure problems encountered by actuators during the flight of heavy-lift launch vehicles in disturbed environments. It studies a method for achieving rocket attitude stabilization and tracking under complex conditions, proposing an adaptive fault-tolerant backstepping attitude control design method. First, to avoid attitude singularities, a quaternion-based kinematic and dynamic model of the launch vehicle oriented towards actuator failures is established. Based on this model, an adaptive fault-tolerant backstepping attitude controller is designed to adaptively estimate and compensate for uncertainties and external disturbances, handling potential failures and ensuring the stability of the control system. The algorithm proposed in this invention is more effective and superior than traditional adaptive backstepping methods.

The invention discloses a test simulation method for a photoelectric load of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: collecting the attitude information of a tested photoelectric load in real time, generating a two-dimensional image consistent with the real-time visual angle of the tested photoelectric load based on the attitude information, and transmitting the two-dimensional image to the tested photoelectric load in a real-time video stream mode; attitude information of the unmanned aerial vehicle is collected and transmitted to the motion platform, and the motion platform simulates a flight state according to the attitude information, so that physical motion characteristics of the motion platform are synchronized with a sensor state of the tested photoelectric load; and the tested photoelectric load performs servo control action based on the attitude information of the unmanned aerial vehicle according to the received two-dimensional image and the test task condition so as to realize real-time detection and tracking of the target. The invention further discloses a system of the test simulation method for the photoelectric load of the unmanned aerial vehicle. The target detection precision, the servo control response and the flight attitude control precision of the photoelectric load in a real flight state are effectively evaluated.

The invention discloses a deceptive signal injection and control method for an MEMS inertial sensor. The invention relates to the technical field of safety protection of MEMS (micro-electromechanical system) inertial sensors, and in the method, a resonant frequency interference signal subjected to amplitude modulation (AM) and phase modulation (PM) is injected into a target sensor to simulate a Coriolis force effect generated by real inertial input (such as angular velocity), so that a physically static MEMS device outputs preset erroneous motion data which seems legal, and the erroneous motion data is detected. And therefore, cheating on an upper-layer control system (such as an automatic driving attitude control unit) is realized. According to the method, by accurately controlling modulation parameters (such as modulation depth and phase offset) and a signal injection time sequence, a false inertial measurement value with high concealment and credibility can be generated, and the method is suitable for scenes such as sensor safety test, anti-interference algorithm verification and fault simulation.

The invention relates to the technical field of space non-cooperative target capturing and racemization, in particular to a space non-cooperative target variable-stiffness racemization device based on a dielectric elastomer and application of the space non-cooperative target variable-stiffness racemization device, and the space non-cooperative target variable-stiffness racemization device is suitable for attitude control and racemization operation of space tumbling satellites, space debris and other non-cooperative targets. The supporting assembly comprises a middle shaft, a middle shaft servo motor and a fixing base, the middle shaft vertically penetrates through the fixing base, and the middle shaft servo motor is in transmission connection with the middle shaft and used for driving the middle shaft to rotate around the axis of the middle shaft or driving the middle shaft to pitch in the vertical direction so as to adjust the space posture of the arm rotation eliminating body. Compared with the prior art, the racemization device is high in racemization precision, good in operation flexibility, free of fuel consumption and suitable for long-term space tasks.

This invention discloses a distributed, event-triggered, low-communication fine-grained attitude control method for spacecraft, aiming to overcome the problems of high communication frequency, severe resource waste, and difficulty in effectively compensating for multi-source interference in existing technologies. This method constructs a deeply coupled attitude model for the spacecraft, comprehensively considering the dynamic effects of combined interferences such as center-of-mass changes and flexural vibrations; designs an event-triggered mechanism based on changes in control signals to update control commands as needed, thereby reducing the communication frequency; and constructs an adaptive composite controller to estimate and compensate for interference and communication errors online, ensuring attitude control accuracy. In a 50-second simulation, this method triggers only 75 communications while controlling the attitude tracking error to within 5 × 10⁻⁶. ‑3 Within rad, it has the advantages of low communication load, high control precision, and strong anti-interference capability, and is suitable for distributed spacecraft systems with strict requirements for attitude stability and communication resource consumption.

The invention discloses a suspension flight anti-swing control method for a quad-rotor unmanned aerial vehicle. Comprising the following steps: acquiring an expected position, a yaw angle, an actual position and an attitude angle of the quad-rotor unmanned aerial vehicle in real time, and acquiring a load swing angle in real time; compensating the expected position according to the load swing angle to obtain a compensated expected position; position control is carried out according to the actual position and the compensated expected position of the quadrotor unmanned aerial vehicle, a virtual control quantity is obtained, and the vertical virtual control quantity is expected vertical pulling force; performing attitude calculation according to the virtual control quantity to obtain an expected roll angle and a pitch angle; attitude control is carried out according to the expected attitude angle and the actual attitude angle, expected torque is obtained, then expected rotating speeds of the four rotor motors are obtained, and the four-rotor unmanned aerial vehicle is controlled according to the expected rotating speeds. The damping controller provided by the invention considers the coupling characteristic between the four rotors and the hanging load, so that the hanging system can effectively inhibit the load swing angle while accurately following the expected path.

The invention discloses a multi-mode attitude control method for a two-wheeled mobile platform, and the method comprises the steps: driving a real vehicle through a prior controller, collecting data, and constructing a real vehicle dynamics data set; fitting platform dynamics by adopting a radial basis function neural network, and constructing a data driving model; building a reinforcement learning agent proxy, playing back a control track, minimizing a behavior difference between a proxy strategy and a prior controller, and completing behavior simulation; constructing a simulation environment by using a data-driven model, training an agent proxy by adopting a near-end strategy optimization algorithm, and searching an optimal control strategy through environment interaction iteration; and accessing the real vehicle to the optimal control strategy, operating the agent model and collecting data, and dynamically updating the data driving model to complete physical environment alignment. According to the method, a platform dynamics model capable of being dynamically updated is constructed in a data driving mode, multi-mode attitude control is completed by applying a reinforcement learning PPO algorithm and combining priori knowledge and high-dimensional features, and self-adaptive control can be rapidly and stably achieved.

The utility model discloses a kind of worm disc devices suitable for aerial refueling pipe carrying, driving shaft is provided with the radial protruding limit ring, and the connecting end of driving shaft is provided with shaft sleeve, lead disc is tightly fitted on shaft sleeve, and the end surface of lead disc and the end surface of limit ring abut, shaft hole is opened on shaft sleeve, and the shaft hole of shaft sleeve is installed in by key in the one end of driven shaft, limit protruding ring is further provided on driving shaft, and the shaft rod between limit protruding ring and shaft sleeve forms range-increasing shaft, worm disc is installed with clearance fit on range-increasing shaft, variable-diameter spiral groove is opened on worm disc, and the small diameter end of spiral groove is close to lead disc, and lead hole is opened on lead disc.The utility model has the beneficial effects that: worm disc rotation drives the winding and unwinding of refueling hose, overcome inherent defects of traditional unmanned aerial vehicle in winding and unwinding hose efficiency and stability, and worm disc adopts openwork design, significantly enhance unmanned aerial vehicle in air encounter strong wind and other bad weather, so that unmanned aerial vehicle can maintain accurate flight attitude control in complex and changeable air environment.