459 results about "Flight stability" patented technology

The invention discloses an unmanned aerial vehicle flight path optimization system and method based on artificial intelligence and Internet of Things, and relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: collecting communication delay, environment data and an unmanned aerial vehicle state in real time; analyzing historical communication delay data by using a Markov chain, and predicting a basic delay value in a short time in the future; correcting the basic delay value through a machine learning model; outputting a final delay prediction result; calculating a delay risk index, and judging a delay risk level; based on the delay risk level, when the delay risk level is low risk, sending a control instruction in advance according to the final delay prediction result; and when the delay risk level is medium or high risk, calling a pre-trained reinforcement learning strategy library, and generating a self-adaptive control instruction. According to the method, the multi-dimensional risk index is constructed, multiple strategies are provided to adjust the flight path according to the real-time data and the risk index, and the flight stability of the unmanned aerial vehicle is improved.

The invention discloses an unmanned aerial vehicle path planning and obstacle avoidance optimization method based on an improved elite colony algorithm, and the method comprises the following steps: carrying out three-dimensional grid environment modeling and obstacle generation, and obtaining a discrete model of a whole three-dimensional space according to a layering + two-dimensional grid method; elite strategy and path generation: ants select paths by using a random proportion strategy, set a transition probability function and introduce a fluctuation coefficient to prevent excessive concentration of path weights caused by pheromone volatilization; dynamic volatilization rate self-adaptive adjustment: carrying out self-adaptive adjustment according to pheromone distribution, and constructing a dynamic volatilization rate model; path cost calculation and dynamics constraint are integrated, a multi-objective planning method is applied, the path length and flight stability are optimized at the same time, and a path cost function is constructed; and performing path post-processing and smooth optimization, including processing a balanced path to improve the flyability and performing collision detection, thereby establishing an unmanned aerial vehicle dynamics constraint model, and ensuring the flight safety on the premise of path optimization.

The invention discloses a flight control method and system for an electric power inspection unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle inspection flight control. According to the flight control method of the electric power inspection unmanned aerial vehicle, the current flight position of the unmanned aerial vehicle is obtained in real time, deviation analysis is performed on the current flight position and a target inspection position, and when the deviation exceeds a preset threshold value, disturbance sensing data in a set area is further obtained and a disturbance sensing intensity index is calculated; according to a comparison result of the index and a disturbance attribution judgment threshold value, an offset cause is judged, and a corresponding disturbance response control strategy or a flight error correction strategy is executed respectively, so that the flight stability and the control precision of the electric power inspection unmanned aerial vehicle are dynamically guaranteed; according to the invention, through dual discrimination of the disturbance perception intensity index and the flight error adjustment index, external interference and flight control error causes are accurately distinguished, path offset cause identification and strategy matching are realized, and the flight stability and control precision of the electric power inspection unmanned aerial vehicle in a complex environment are improved.

The invention discloses an aircraft attitude control method and device based on a semiconductor microcomputer system, and the method comprises the steps: collecting the multi-source sensor data of an aircraft, calculating an attitude error vector, and constructing a three-dimensional error space coordinate system; taking the three-dimensional error space coordinate system as a reference, adjusting the model in real time, and solving the optimal attitude adjustment amount in a prediction window period; the optimal attitude adjustment amount is input into an execution mechanism distribution module, and a thrust adjustment instruction sequence and a control surface deflection angle instruction queue of each vector propeller are generated through calculation in combination with a propeller response matrix and a control surface efficiency coefficient; dynamically correcting and predicting weight parameters of the controller through closed-loop verification; and updating the multi-objective optimization model based on the corrected parameters, adjusting the instruction distribution proportion through a dynamic reconfiguration interface, and writing the updated parameters into the attitude database to form a complete closed-loop period. According to the invention, high-precision real-time control of the attitude of the aircraft is realized, and the flight stability and the energy efficiency ratio in a complex environment are improved.

The invention discloses a transmission driving control method of a bimodal integrated engine. The transmission driving control method comprises the following steps: S1, state sensing; s2, mode decision making; S3, dynamic adjustment; s4, mode switching; S5, power optimization distribution; s6, adaptive learning is carried out; and S7, fault-tolerant guarantee. The invention further discloses a bimodal integrated engine transmission system which comprises the following modules: a power input module; a transmission adjusting module; a state sensing module; an intelligent control module; and a fault-tolerant guarantee module. Parameters are dynamically adjusted through fuzzy PID control according to speed deviation, meanwhile, real-time correction is conducted in combination with a multi-mode intelligent algorithm, speed fluctuation is precisely controlled within + / -3 km / h, flight stability is guaranteed, a model prediction control and multi-mode intelligent control cooperation mechanism is adopted, an optimal power output sequence is calculated in advance, coordinated distribution is completed, and the optimal power output sequence is controlled to be within + / -3 km / h. The dynamic response speed is increased by 40%, and the high-dynamic task requirement is met.

The invention provides an unmanned aerial vehicle flight attitude adaptive prediction and control method and system, and relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: building a prediction compensation amount through obtaining environment data, carrying out the multi-scale prediction and adaptive fusion of a flight attitude, building a prediction control relation containing a state variable item, a reference input item and an interference compensation item, and carrying out the adaptive prediction of the flight attitude. And performing hierarchical updating on the control parameters according to the state change rate, and finally generating a control instruction to adjust the flight attitude. The flight stability and adaptability of the unmanned aerial vehicle in a complex environment are improved.

The invention discloses a Beidou-based patrol inspection unmanned aerial vehicle positioning system, and relates to the field of unmanned aerial vehicles. The method comprises the following steps: an unmanned aerial vehicle positioning estimation module which performs positioning optimization through cloud processing based on Beidou satellite and unmanned aerial vehicle data so as to realize position estimation; the unmanned aerial vehicle position correction module obtains the accurate position of the unmanned aerial vehicle through an intelligent error correction function; a multi-unmanned aerial vehicle task allocation module which constructs a scene influence index, performs task allocation among multiple unmanned aerial vehicles by using the task execution adaptation score, and improves the efficiency; the map construction and path planning module is used for constructing an environment map and carrying out optimal path planning according to a scene influence index optimization A * algorithm; and the real-time positioning and obstacle avoidance module is used for acquiring unmanned aerial vehicle data, performing obstacle detection and making an obstacle avoidance decision in combination with obstacle information. Through intelligent error correction and real-time obstacle detection, the positioning precision, flight stability and obstacle avoidance capability of the unmanned aerial vehicle in a complex environment are improved, and efficient and safe execution of a task is ensured.

The invention provides an unmanned aerial vehicle autonomous obstacle avoidance and dynamic path planning method and system based on multi-modal perception and hybrid intelligent decision. Environmental parameters such as wind speed, illuminance, temperature and humidity and image quality indexes are collected in real time through an airborne weather station, an IMU and a visual sensor, a flight parameter-image quality coupling model is established, and multi-target optimization is achieved through support vector regression (SVR) and particle swarm optimization (PSO). And designing a dynamic strategy optimization module based on Q-learning, and designing a reward function in combination with image quality, obstacle avoidance safety and energy consumption. An obstacle three-dimensional model is constructed in real time through ORB-SLAM3, a dynamic danger coefficient is calculated, and an obstacle avoidance track is generated by adopting an improved APF-RRT * algorithm. And the online cooperative control module optimizes the control quantity by using a BFGS algorithm so as to ensure the flight stability and the task efficiency. The method realizes high-precision obstacle avoidance and path planning of the unmanned aerial vehicle in a complex environment, has the characteristics of high robustness and wide adaptability, and is suitable for practical application scenes such as routing inspection, surveying and mapping and the like.

The invention discloses a flight control method and system for unmanned aerial vehicle tracking, and relates to the technical field of unmanned aerial vehicle flight control. The flight control method for unmanned aerial vehicle tracking comprises the following steps of flight stability detection, frequency rise adjustment judgment and frequency drop adjustment judgment. According to the invention, the stability degree of the flight control power performance of the unmanned aerial vehicle is detected based on the obtained performance data of the unmanned aerial vehicle to obtain the stability detection result, and the initial attitude update frequency rising and falling adjustment judgment is executed in combination with the stability detection result to obtain the corresponding rising judgment update frequency and falling judgment update frequency; the effect of more accurately controlling the flight attitude of the unmanned aerial vehicle in the distribution line inspection operation is achieved, and the problem of inaccurate control of the flight attitude of the unmanned aerial vehicle in the distribution line inspection operation based on the unmanned aerial vehicle in the prior art is solved.

The invention discloses an unmanned aerial vehicle automatic homeward voyage method based on a global topological map and a graph search algorithm, which comprises a global passable area topological connected graph module, a homeward voyage path search module, a homeward voyage path optimization module and a homeward voyage path error processing module. According to the method, global path searching is carried out in combination with a Dijkstra algorithm, path smoothness, flight time and obstacle avoidance are optimized by using a B spline curve, the precision and speed of path planning are effectively improved, and meanwhile, the system can cope with changes in the environment by updating a topological connected graph and optimizing the path in real time, so that the path planning efficiency is improved. And secondly, the path safety and the flight stability are both considered, and an obstacle distance penalty term is introduced, so that the flight path can avoid the obstacle, and the collision risk is reduced.

The invention discloses an unmanned aerial vehicle wind resistance performance evaluation method, device and equipment and a storage medium, and the method comprises the steps: obtaining flight parameters of an unmanned aerial vehicle under different wind speed conditions, and carrying out the quantification processing of the flight parameters, and obtaining flight stability performance scores under different wind speed conditions; according to the flight stability performance scores under the different wind speed conditions and the actual wind speed, wind resistance scores of the unmanned aerial vehicle under the different wind speed conditions are calculated; and based on the wind resistance score and the weight coefficients corresponding to different wind speeds, determining a comprehensive wind resistance score of the unmanned aerial vehicle. According to the quantitative evaluation method, the comprehensive wind resistance performance of the unmanned aerial vehicle at low, medium and high wind speeds can be comprehensively evaluated, the limitation of evaluation under a single wind speed condition is avoided, objective quantitative evaluation of the wind resistance performance is realized, and the wind resistance performance of the unmanned aerial vehicle can be accurately reflected.

The invention discloses a fire-fighting unmanned aerial vehicle autonomous navigation method and system oriented to a complex building environment, and relates to the technical field of unmanned aerial vehicle navigation.The method comprises the steps that firstly, obstacle distribution point cloud data and thermodynamic data are obtained based on a laser radar and other sensors, and a spatial constraint coefficient and a thermal disturbance intensity factor are calculated respectively; therefore, the space trafficability and stability of the flight environment are comprehensively reflected. And then, fusing the global path planning and the local obstacle avoidance to generate a comprehensive environment evaluation parameter, adaptively configuring a weight ratio of the global path planning to the local obstacle avoidance according to the comprehensive environment evaluation parameter, and carrying out weighted fusion on instructions output by different algorithms so as to generate a smooth and safe flight control instruction. According to the invention, the dynamic adjustment of the navigation strategy can be realized according to the change of the building environment, the obstacle avoidance safety in the complex environment is ensured, the continuity and efficiency of the overall path planning are also considered, and the autonomous flight stability and task execution reliability of the fire-fighting unmanned aerial vehicle in the high-risk building environment are significantly improved.

The invention discloses an automatic control method of a four-power-source tiltable aircraft, relates to the technical field of flight control of tiltable aircrafts, is realized based on a PX4 flight control system, and is suitable for a tiltable aircraft provided with four independent tiltable power sources and corresponding tilting execution mechanisms. According to the method, through configuration of a tilting angle control module, a power distribution module and a full-stage flight logic scheduling module, full-stage automatic control of vertical take-off and landing, suspension, horizontal take-off, fixed-point horizontal flight, automatic cruise, one-key return flight, fixed-angle flight, power source fault handling and the like is achieved. Smooth transition of all flight modes is achieved, the stability of the attitude, the height and the position of the tiltable aircraft in different flight stages is maintained, meanwhile, the functions of automatic obstacle avoidance, fault emergency and the like are integrated, flight safety is guaranteed, flight stability and applicability are improved, and the method can be widely applied to various tiltable aircraft operation scenes.

The invention belongs to the technical field of intelligent disaster relief equipment, and particularly relates to a long-endurance high-altitude fire-fighting unmanned aerial vehicle, which comprises a flying fuselage, no water tank load is arranged on the fuselage, a water pipe is fixedly arranged in the fuselage, and one end of the water pipe is communicated with a sprinkler head; the other end of the water pipe communicates with a water injection head, and a cushioning sealing assembly is arranged in the water injection head. The control seat is arranged on the machine body, a plurality of detection units are arranged on the control seat and the machine body, and a power supply end is arranged on one side wall of the control seat; through the design of the ground end, the buffer sealing assembly and the like, the unmanned aerial vehicle can carry a cable and a water pipe, the water pipe or the cable can be prevented from excessively floating in the air while long-time endurance fire extinguishing in the air is completed, the flight stability is guaranteed, various data can be collected, and the rescue efficiency is improved.

The invention relates to the technical field of underwater robots, discloses an underwater autonomous flight control method and system for a submersible type unmanned aerial vehicle, and aims to solve the technical defects of rigid route planning, high energy consumption and poor task adaptability of an existing submersible type unmanned aerial vehicle in complex dynamic underwater environment flight control. The method comprises the steps of executing multi-modal underwater environment perception, constructing an environment state fusion model under a unified space-time reference, generating a predictive hydrodynamic field four-dimensional model, executing multi-target route optimization based on energy and risk cost, and implementing self-adaptive flight control based on feedforward compensation. By adopting the above technical scheme, the method can effectively reduce the energy consumption of the unmanned aerial vehicle, remarkably prolong the operation endurance time, improve the intelligence and task adaptability of route planning, and improve the flight stability and trajectory tracking precision. Therefore, the autonomy, the economy and the task success rate in an unknown, unstructured and strong dynamic underwater environment are enhanced.

The invention provides an unmanned aerial vehicle adaptive path planning method and system fused with environment uncertainty, and the method comprises the steps: obtaining surrounding environment data based on an environment perception module, generating a local grid map and a dynamic obstacle list, inputting the local grid map and the dynamic obstacle list into an environment uncertainty evaluation module, obtaining an uncertainty factor, and carrying out the calculation of the uncertainty factor; and performing path planning through a global path planner and a local path planner based on the uncertainty factor, and adjusting the weight of a global path and the weight of a local path according to the environment uncertainty factor through a dynamic weight fusion device to obtain a final track. According to the method, the flexibility and the real-time performance of unmanned aerial vehicle path planning are effectively improved, the obstacle avoidance capability and the flight stability of the unmanned aerial vehicle in a complex environment are enhanced, and the flight efficiency is improved.

The invention relates to a highway roadbed high slope displacement monitoring system and method based on an unmanned aerial vehicle laser radar, the system comprises an unmanned aerial vehicle, a holder, a laser radar, a GPS, a buffer seat, a control assembly and a balancing weight, the buffer seat is connected between the unmanned aerial vehicle and the holder through an oil box, a sliding cavity, a piston rod and an oil liquid circulation structure, and is used for filtering flight vibration; the holder is of a double-rotating-frame structure, the laser radar is installed in the second rotating frame, the control assembly drives the second rotating frame to turn over through the ball screw and the electromagnet ring, protection and angle adjustment of the laser radar are achieved, and gear abrasion is avoided. The balancing weight is connected to the bottom of the second rotating frame through a clamping assembly and can be replaced according to the wind speed to maintain flight stability. The problem that vibration generated in the flight process of an existing unmanned aerial vehicle affects the measurement precision of a laser radar and affects the accuracy and reliability of monitoring data is solved.

The invention belongs to the technical field of aircraft control, particularly relates to a range extender control system for an unmanned aerial vehicle and a controller, and aims to solve the problems of limited endurance, poor flight stability and the like caused by discontinuous energy supply and power response lag. The system comprises a range extender power source module, an electric energy conversion and distribution module, a flight state sensing module, a load power prediction module, a multi-target optimization scheduling module and a closed-loop feedback execution module. Through flight state real-time perception and load power prediction based on a recurrent neural network, an optimal power generation instruction is generated in combination with multi-target optimization scheduling, and precise rotating speed tracking is realized through adaptive PID control. A fuel consumption, power supply smooth switching and battery health combined cost function is introduced, dynamic weighting is carried out according to task types, and the cruising ability and the system robustness are improved; the system has the functions of fault emergency response, power battery hot plug and model online updating, and safety and maintainability are enhanced.

The invention relates to the technical field of unmanned aerial vehicle autonomous navigation, and discloses a mine unmanned aerial vehicle autonomous route dynamic adjustment system which comprises a multi-mode sensing module, a dynamic environment field potential modeling module, a field potential spatio-temporal evolution prediction module, a route wave function resolving and generating module, an unmanned aerial vehicle platform and flight control module and a self-adaptive calibration module. A safe and smooth air route expected position is generated in a predicted risk potential field by solving an air route wave function equation, and the core of the method is that a self-adaptive calibration module carries out closed-loop feedback adjustment on fusion weight of environment field potential by quantifying trajectory tracking deviation and flight stability deviation of actual flight of an unmanned aerial vehicle. According to the method, the problem that the risk model is solidified and cannot adapt to the dynamic environment in the prior art is solved, so that the unmanned aerial vehicle can autonomously learn and correct the cognition of the unmanned aerial vehicle on the environmental risk according to the actual flight experience, and the autonomous navigation adaptability and safety in the complex dynamic environment are remarkably improved.

The invention discloses an agricultural plant protection unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicles. The agricultural plant protection unmanned aerial vehicle comprises a vehicle body provided with supporting legs and further comprises wings, the multiple wings are circumferentially and evenly arranged on the vehicle body, the tail end of each wing is provided with a fan blade driven by a motor, and the side, away from the fan blade, of each wing is provided with a nozzle; the water tank is arranged on the lower side of the machine body, and a feeding assembly for supplying water to the nozzles is arranged on the water tank; the anti-shaking assembly is arranged in the water tank and used for restraining water in the water tank from shaking; the movable floating plate capable of moving up and down along with the liquid level is attached to the liquid level all the time, the elastic element is used for buffering, shaking of liquid in flight is effectively restrained, and flight stability is guaranteed.

The invention discloses a fixed-wing unmanned aerial vehicle distributed formation and obstacle avoidance method based on diffusion reinforcement learning, and the method comprises the steps: processing single observation data through a graph attention network, and enabling the single observation data to serve as a condition for generating an optimal action in a reverse denoising process; the method is suitable for distributed cluster control of a fixed-wing unmanned aerial vehicle cluster in an unknown and disordered environment, treats huge challenges brought by complex dynamics and non-integral constraints in the cluster, and effectively solves a series of problems that an existing method is difficult to capture multi-modal action distribution necessary for robust obstacle avoidance under an uncertain condition. A large number of numerical simulation results show that the method is obviously superior to an existing baseline method in the aspects of flight stability and collision rate, the potential of a diffusion model in the aspect of extensible and robust unmanned aerial vehicle flight control is highlighted, and the method has good theoretical popularization value and engineering application prospects.

The deformable land-air amphibious robot comprises a robot body, a deformation mechanism, a land-air combined power device, an environment sensor and a controller, the deformation mechanism is installed on the robot body, the land-air combined power device is installed on the deformation mechanism, and the controller communicates with and controls a transverse rod steering engine, a longitudinal rod steering engine and the land-air combined power device. The environment sensor is installed on the machine body. The air-ground amphibious robot integrates a rotor power device and a wheel driving force device and can deform in multiple modes, and compared with existing cage type and wheel type air-ground amphibious robots, the air-ground amphibious robot has the advantages of being compact in structure, low in weight, long in endurance and high in task efficiency. Deformation resistance can be reduced through cooperative tilting in the air-ground switching process, the height / width size of the aircraft can be adjusted through cooperative tilting in the flight / ground movement process, and the aircraft has better obstacle space passing capacity, flight stability and holder detection view.

The invention provides a quadrotor unmanned aerial vehicle fault-tolerant control method and system considering random disturbance, and belongs to the field of unmanned aerial vehicle flight control. The method comprises the steps that a random control system model fusing Wiener process random disturbance, actuator faults and input saturation is established, a six-degree-of-freedom control problem is decoupled into a position and attitude tracking sub-problem, and an expected attitude angle is inversely solved; applying constraints to the state variables by adopting a mixed constraint strategy fusing a delay state conversion function and nonlinear state dependence mapping; based on a self-adaptive backstepping method control framework, a controller is designed for six-degree-of-freedom sub-channels of the four-rotor unmanned aerial vehicle, and final input control signals of the degree-of-freedom sub-channels are obtained; and constructing a comprehensive Lyapunov function covering six degrees of freedom of the unmanned aerial vehicle, and proving that all signals of a closed-loop system are finally consistent and bounded. According to the invention, multiple complex factors can be coped with synchronously, the flight stability and reliability of the unmanned aerial vehicle in a complex environment are improved, and the method is suitable for multi-scene quadrotor unmanned aerial vehicle control.

The invention discloses an unmanned aerial vehicle anti-wind disturbance controller and a control method, and belongs to the technical field of unmanned aerial vehicle flight control. The method runs on an independent processing module which is connected in series between a main flight controller and an electronic speed regulator of the unmanned aerial vehicle, a dynamic reference is constructed by collecting motor current in real time, deviation is calculated, and wind disturbance equivalent disturbance torque is estimated in a prospective mode through a third-order linear extended state observer (LESO) with bandwidth parameterization design; in combination with a'user operation state + flight mode 'two-dimensional intelligent decision compensation strategy, a'look-ahead wind resistance + attitude backup' dual-redundancy channel is matched, so that the wind disturbance is compensated in advance, and the flight stability in a complex scene is ensured. A corresponding controller adopts a standardized independent hardware design, the adaptability is high, the integration cost is low, and the method can be widely applied to high-precision operation scenes of various multi-rotor unmanned aerial vehicles.

The invention discloses a highway tunnel inspection system and method based on an unmanned aerial vehicle, and relates to the field of highway tunnel inspection, an unmanned aerial vehicle module, a monitoring module and a protection module, the monitoring module is arranged on the unmanned aerial vehicle module, and the monitoring module is used for obtaining images and data in a tunnel; the protection module comprises a protection frame, the protection frame comprises a plurality of polygonal frames, the protection frame is a polyhedral frame formed by connecting the vertexes of the polygonal frames, the unmanned aerial vehicle module and the monitoring module are located in the protection frame, and each polygonal frame is provided with a plurality of anti-collision air bags. According to the system, the unmanned aerial vehicle module and the monitoring module are wrapped in the polyhedral frame, through the polyhedral frame and the rolling anti-collision air bag on the polyhedral frame, the anti-collision performance and the flight safety performance of the unmanned aerial vehicle are effectively improved, the system can roll and fly close to the tunnel wall, and the influence of vehicle wind pressure on the flight stability of the unmanned aerial vehicle is prevented.

The invention relates to the technical field of aircraft power systems, and discloses a hybrid power management system suitable for a vertical take-off and landing aircraft and a control method. A lithium battery pack; a super capacitor; the power distribution module is electrically connected with the main turboprop engine, the lithium battery pack and the super capacitor and used for controlling energy flow among the main turboprop engine, the lithium battery pack and the super capacitor according to instructions. The control method comprises the steps that a staged power distribution strategy is executed according to judged flight stages such as vertical take-off and landing, horizontal cruise or emergency, instantaneous power is compensated through a super capacitor during vertical take-off and landing, and combined propulsion or energy recovery is decided according to key parameters such as the lift-drag ratio during horizontal cruise. According to the scheme, the vertical take-off and landing response and flight stability are improved, the endurance mileage is increased, and the intelligence and safety of the system are improved through self-adaptive control and redundancy design based on the ground digital twin model.

The invention discloses an unmanned aerial vehicle formation communication system based on a LoRa technology and a method thereof. The communication system comprises a ground control unit, a main control processing unit, a sensing array unit, a power supply management unit and a mobile communication unit. The ground control unit generates a formation flight scheme, and the main control processing unit fuses RTK positioning data to generate a dynamic control instruction; the mobile communication unit constructs a radio data transmission module based on a LoRa technology, supports dynamic switching between an ESP-NOW broadcast mode and a TCP transparent transmission mode, and realizes low-delay instruction transmission and low-power-consumption data interaction. The sensing array unit integrates an RTK positioning module and an inertial measurement unit, monitors the state of the unmanned aerial vehicle in real time, and ensures that the formation spacing error is less than 10cm. Through long-distance low-power-consumption communication and power and frequency band dynamic optimization of the LoRa technology, in combination with high-precision positioning and anti-interference spread spectrum modulation, large-scale formation synchronization efficiency and flight stability are remarkably improved, and the method is suitable for scenes such as agriculture, rescue and cluster performance and has the advantages of low cost and high reliability.

The invention provides a modular free-combination rotor unmanned aerial vehicle and a combination method, and the unmanned aerial vehicle comprises a plurality of independent rotor unmanned aerial vehicle units, and each rotor unmanned aerial vehicle unit comprises a fuselage and a rotor; a battery, a motor, a communication module and a power control module are arranged in the machine body; a standard socket is arranged outside the fuselage and used for being fixedly connected with other rotor wing unmanned aerial vehicle units or rods with the same interfaces, and sharing of power supply and communication is achieved through the standard socket. The power control module dynamically adjusts rotor power distribution in real time according to the form of the combined unmanned aerial vehicle, and the communication module automatically establishes a master-slave control relation after combination to achieve unified coordination of flight control. According to the technical scheme provided by the invention, through free combination of the modular rotor unmanned aerial vehicle units, a specific unmanned aerial vehicle can be quickly formed, the purchase and use cost is reduced, and the flight stability and safety are improved.

The utility model relates to the technical field of unmanned aerial vehicles, in particular to a propeller hub, a rotor wing and an unmanned aerial vehicle. The propeller hub comprises a body, the body is provided with a swinging shaft and can swing around the swinging shaft, the propeller hub further comprises a mounting base and a damping part, the body is mounted on the mounting base and is arranged in the swinging direction of the body, and the damping part is clamped between the mounting base and the body and used for damping swinging movement of the body. The propeller hub provided by the embodiment of the utility model can be used for damping through swinging of the swinging shaft, and meanwhile, the damping piece arranged along the swinging direction of the body can be used for buffering the vibration of the body, inhibiting violent oscillation and improving the stability of the propeller hub, so that the flight stability is improved.

The invention provides a hydrogen energy unmanned aerial vehicle health monitoring and management method based on a hybrid excitation operator, and belongs to the field of hydrogen energy unmanned aerial vehicles, and the method comprises the steps: building a hydrogen fuel cell voltage estimator based on online parameter identification, estimating voltage output in real time, generating a voltage residual error with a voltage measurement value, and obtaining the maximum output power of a fuel cell; a hybrid excitation operator is designed, high-frequency excitation is injected into the fuel cell through a DC / DC converter, low-frequency excitation which does not influence flight stability is injected through maneuvering of the active unmanned aerial vehicle, characteristic frequency impedance is calculated online by using an injected excitation signal and a response voltage signal, and the characteristic frequency impedance is used as a fault diagnosis characteristic; designing a fault classifier, and classifying the faults into water logging, film dryness and oxygen deficiency based on the characteristic frequency impedance; and based on the diagnosed specific fault type, controlling components such as an air inlet fan and an exhaust valve to perform fault recovery. According to the invention, online health management of the hydrogen energy unmanned aerial vehicle is realized, and the method is suitable for a hydrogen energy unmanned aerial vehicle system requiring online health management.