336 results about "Flight stability" patented technology

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 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 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 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 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 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 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 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 discloses a blade tip blowing method for lift augmentation of a rotor unmanned aerial vehicle, belongs to the technical field of lift augmentation of rotor unmanned aerial vehicles, and aims to solve the problem of insufficient lift force caused by vortex induced resistance generated by a blade tip vortex of a traditional rotor unmanned aerial vehicle. Transverse distributed jet flow is arranged on the 25% c-75% c section of the blade end face airfoil profile (the jet flow is blown out at the double blade tip speed, the two blades symmetrically apply the jet flow, and the jet flow is conveyed through a titanium alloy guide pipe). During design, jet parameters are simulated and optimized through pneumatic modeling (multiple reference coordinate systems and SST k-omega turbulence models), working conditions are dynamically adapted, and vorticity analysis and lift comparison verification are combined. According to the scheme, blade tip vortexes can be damaged, resistance is reduced, lift force is improved, meanwhile, flight stability is guaranteed, and multiple flight working conditions are adapted.

The invention is suitable for the technical field of unmanned aerial vehicle energy consumption management and intelligent control, and provides an unmanned aerial vehicle logistics transportation intelligent management platform fusing multi-source data, and the platform comprises a flux regulation and control module which is used for predicting the gas release flux in an unmanned aerial vehicle cabin in unit time, and dynamically adjusting the ventilation flow rate of a ventilation system according to the gas release flux, the gas concentration in the cabin is maintained to be in a gas concentration steady-state interval corresponding to the heat balance optimal time period of the gas in the cabin. According to the technical scheme, the influence rule of the volatile pollutant micro-thermal effect on the energy efficiency of the unmanned aerial vehicle battery is disclosed, and the unmanned aerial vehicle battery continuously operates in the optimal energy efficiency state corresponding to the discharge efficiency peak value interval through real-time trend correction; therefore, the energy utilization rate and the flight stability of the unmanned aerial vehicle under the task of carrying the recycled objects are remarkably improved.

The invention discloses a multi-rotor unmanned aerial vehicle carrying satellite communication equipment and an aircraft thereof, the unmanned aerial vehicle adopts a six-rotor layout and has flight stability and redundancy control capability, and when a certain rotor fails, flight is maintained through the remaining rotors; a lightweight satellite communication module is integrated, and a plurality of antennas are arranged below the unmanned aerial vehicle body; peripheral obstacle avoidance sensing devices are mounted at the tail ends of connecting rods of the six groups of rotors, and vertical obstacle avoidance sensing devices are mounted above and below the head of the fuselage respectively. A flight control program adopts an intelligent filtering algorithm, small target interference data is automatically filtered out, and false triggering is prevented. Compared with a conventional multi-rotor unmanned aerial vehicle, the unmanned aerial vehicle has the characteristic of carrying satellite communication equipment, and unmanned aerial vehicle control communication can be carried out nationwide through the satellite communication equipment; meanwhile, the unmanned aerial vehicle has the characteristic of long endurance, and can fly for 2 hours and above 60km; the problems of limited remote communication, short endurance, short voyage and the like in the prior art can be solved.

The invention discloses an unmanned aerial vehicle flight control method and system based on a Mangbar and a dual-channel attention mechanism under wind field disturbance, and particularly relates to the technical field of unmanned aerial vehicle autonomous navigation and intelligent control. The method comprises the following steps: constructing a wind field disturbance model based on computational fluid mechanics, and simulating an unsteady wind field environment among urban building groups; designing a deep reinforcement learning network fusing a Mama framework and a double-channel attention mechanism, wherein the deep reinforcement learning network is used for realizing dynamic modeling of long-sequence wind field features and attention weighting of key spatial-temporal features; a dynamic road sign point guiding mechanism and a multi-stage attenuation greedy strategy are put forward, the sparse reward problem is relieved, and the local path optimization capability is improved; and a multi-target composite reward function including energy constraint, safety distance and path efficiency is constructed, and global path planning of energy consumption perception is realized. The method can improve the flight stability, path smoothness and energy efficiency of the unmanned aerial vehicle in a strong wind disturbance environment, and is suitable for unmanned aerial vehicle autonomous navigation tasks in an urban complex environment.

The invention relates to the technical field of insulator detection, and discloses an unmanned aerial vehicle and insulator detection mechanism rapid butt joint and separation method, system, equipment and medium, and the method comprises the steps: building a comprehensive basic sensing system through collecting various sensor data, carrying out the optimization processing of multi-source data through employing a dynamic weight fusion algorithm, and carrying out the rapid butt joint and separation of the unmanned aerial vehicle and the insulator detection mechanism; high-precision recognition and pose calculation of an insulator support target are achieved by combining SIFT feature matching, ICP point cloud registration and infrared temperature contour information, then the distance between the unmanned aerial vehicle and the target support is calculated in real time based on a power transmission tower three-dimensional map and a three-level decision mechanism, and an action control instruction is output. The flight stability and the accurate docking capability of the unmanned aerial vehicle in the complex electromagnetic environment are ensured, and the reliability and the robustness of the system in the complex electromagnetic environment are improved by receiving a guide pipe contact signal and executing mechanical locking and releasing.

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 technical field of unmanned aerial vehicle navigation. A pipeline inspection unmanned aerial vehicle navigation method and system based on reinforcement learning are provided. By collecting inertial measurement, visual inertial odometry, cross array ranging and electronic governor feedback data, a state vector is constructed and high-frequency motion prediction and measurement update are realized through extended Kalman filtering to output high-precision unmanned aerial vehicle body state. The best anti-interference height is solved by combining the pipeline wind disturbance and rotor airflow disturbance model, and the external disturbance torque is decoupled. A dual-frequency reinforcement learning state is constructed and control instructions are output, and safe speed is obtained through safety shield filtering. With safe speed as the target, the motor speed is directly output through the reinforcement learning network to control flight, and the three-dimensional topological mapping of pipeline defects is completed synchronously. The application can realize high-precision navigation, active disturbance rejection and safe inspection in the pipeline, and improve the flight stability and operation reliability in complex aerodynamic environment.

This invention discloses an air-sea collaborative underwater topographic survey system and its deployment control method, belonging to the field of underwater topographic survey technology. It adjusts the flight attitude of the target UAV in the hoisted state through a center-of-gravity adaptive hoisting module, compensating for the center-of-gravity shift of the target unmanned vessel, improving transport speed, and ensuring flight stability. A sonar water-entry protection module decelerates the target unmanned vessel, reducing mechanical impact upon entry into the water and preventing sonar damage. An air-sea collaborative scheduling module enables synchronous scheduling of the target UAV and the target unmanned vessel, ensuring accurate and automatic recovery of the target unmanned vessel, greatly improving the efficiency and automation level of underwater topographic mapping. A multi-dimensional sonar fusion sensing module performs synchronous multi-sonar scanning, avoiding blind spots at land-water boundaries and misalignment of dynamic and static data, forming an accurate point cloud map, and greatly improving the geometric precision and spatial continuity of the detection results.

The utility model belongs to the technical field of unmanned aerial vehicles, and discloses a loading unmanned aerial vehicle. The loading unmanned aerial vehicle comprises an unmanned aerial vehicle body, a loading basket and an adjustable clamp. And a loading platform is arranged on the top back part of the unmanned aerial vehicle body and is detachably fixed. The object carrying basket is placed on the object carrying platform with an opening facing upwards, and the object carrying basket is used for carrying objects. The adjustable clamp comprises two clamping plates, the two clamping plates are oppositely arranged on the carrying platform, and the two clamping plates can be close to or away from each other to clamp or loosen the carrying basket. The object-carrying unmanned aerial vehicle is good in flight stability; manufacturing and fixing are easy, article loading and unloading are convenient, and the device is more suitable for convenient carrying of miniature articles; and the adaptability to carried articles is high.

The application relates to a power inspection unmanned aerial vehicle and a control method. The power inspection unmanned aerial vehicle comprises a body part and a power part. The body part comprises a main frame and an outer shell, the main frame comprises a top plate, a bottom plate, a main plate, two side plates and two end plates, the two side plates are arranged between the top plate and the bottom plate, the two side plates are spaced apart and parallel, the two end plates are arranged between the two side plates, the top plate, the bottom plate, the two side plates and the two end plates surround to form a cabin, the main plate is parallel to the top plate, the main plate penetrates the cabin, and the two ends of the main plate in a first direction respectively protrude from one side of the two end plates away from the cabin, and the side plates and the end plates are provided with weight-reducing holes communicating the inside and the outside of the cabin; the power part is arranged outside the main frame, the power part comprises two groups of power assemblies, the two groups of power assemblies are distributed upwards and downwards, and the lower power assembly is installed on the top plate. The flight stability is good, and the power inspection is facilitated.

The invention relates to the field of unmanned aerial vehicles, and particularly discloses an unmanned aerial vehicle folding arm locking anti-loosening structure which comprises an unmanned aerial vehicle body, a connecting arm is arranged on the unmanned aerial vehicle body, a folding arm is hinged to the connecting arm, a propeller connected with a driving system is installed on the folding arm, a first butt joint box is arranged on the connecting arm, and a second butt joint box is arranged on the butt joint box. A second butt joint box matched with the first butt joint box is arranged on the folding machine arm. The multi-stage locking and anti-loosening effect is achieved through movement of the protection assembly, the reliability of the locking function and the flight stability are greatly improved, the abnormal flight phenomena such as out-of-control and aerial photography shaking are reduced, meanwhile, the connection arm and the folding machine arm are integrated through the protection assembly, and therefore the closed environment is formed, the locking structure is hidden inside, and the anti-loosening effect is achieved. Therefore, the flight resistance is reduced, the flight and cruising ability of the unmanned aerial vehicle is improved, the phenomenon that fatigue of the locking structure is aggravated due to wind resistance disturbance is reduced, the overall performance of the unmanned aerial vehicle is improved, and the service life of the unmanned aerial vehicle is prolonged.

The application discloses a fire extinguishing bomb throwing device for a unmanned aerial vehicle, which comprises a pitch adjusting mechanism, a bomb storage and bomb conveying mechanism capable of being adjusted in pitch on the pitch adjusting mechanism, two groups of mounting pipes, a spacing adjusting plate, a conveying structure and a throwing acceleration structure, and the throwing acceleration structure comprises an acceleration connecting frame, an acceleration conveying belt assembly, an acceleration motor and an acceleration transmission assembly. The application has the advantages that the high-pressure gas launching mode is replaced by the throwing acceleration structure, the recoil force is small, the flight stability of the unmanned aerial vehicle during launching of the fire extinguishing bomb is ensured, and the safety hidden danger is reduced. Meanwhile, the spacing between the upper and lower mounting pipes is adjusted by adjusting the position of the lower mounting pipe on the spacing adjusting plate, and the throwing of fire extinguishing bombs with different specifications is realized.

The utility model discloses a kind of damping device of unmanned plane rotating shaft, it is related to unmanned plane technical field, including: unmanned plane body and damping protection piece, unmanned plane body has rotor support, the end of rotor support is equipped with rotor drive structure, the end of rotor support is located below rotor drive structure and is equipped with through mounting hole;Damping protection piece is connected in the outside of rotor drive structure by mounting rod through mounting hole, the connecting place of mounting rod and mounting hole has elastic damping part, the outside of mounting rod is formed with damping and protection structure.The utility model sets up mounting hole by being arranged at the end of rotor support, connects damping protection piece in the outside of rotor drive structure, and sets up elastic damping part at the connecting place of mounting rod and mounting hole, can effectively buffer the vibration and impact of rotor rotating shaft, improve the flight stability and reliability of unmanned plane under complex environment.

This invention provides an adaptive planning system and method for UAV inspection paths based on transfer learning, belonging to the field of human-machine inspection path planning technology. The system includes: constructing a vertical airflow layer structure representation model of the inspection space for inspection areas with densely packed tall structures, and outputting a set of vertical airflow layer structures for the inspection space; performing airflow layer mapping processing on the inspection path based on the set of vertical airflow layer structures, and outputting a set of airflow-adapted paths; constructing a path cost model with airflow constraints based on the set of airflow-adapted paths, and outputting a set of path costs including the total cost of the inspection path and the comprehensive cost of path segments; and performing cross-airflow layer path reconstruction based on the set of path costs and the set of vertical airflow layer structures, outputting the optimal inspection path. This accurately identifies airflow separation layers in the inspection space, achieving airflow adaptation, risk quantification, and adaptive planning of the inspection path, effectively improving the flight stability and operational safety of UAVs during inspections in areas with densely packed tall structures.

The application discloses a UAV flight trajectory optimization system and method based on artificial intelligence and the Internet of Things, and relates to the technical field of UAV control.The method comprises the following steps: collecting communication delay, environmental data and UAV state in real time; analyzing historical communication delay data by using a Markov chain to predict a basic delay value in a short time in the future; correcting the basic delay value by using a machine learning model; outputting a final delay prediction result; calculating a delay risk index to judge 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; when the delay risk level is medium or high risk, calling a pre-trained reinforcement learning strategy library to generate an adaptive control instruction.The application constructs a multi-dimensional risk index, and provides various strategy adjustment flight trajectories according to real-time data and the risk index, thereby improving the flight stability of the UAV.

This invention relates to the field of unmanned aerial vehicle (UAV) flight control technology, and discloses a method for adaptive adjustment control of UAV flight attitude. Addressing the problems of unstable flight and untimely or inaccurate attitude adjustment of UAVs in complex weather conditions and variable terrain, this method deploys multiple types of sensors on the UAV to collect flight data in real time, including information such as air pressure, wind speed and direction, and attitude angles, and transmits the data to a central processing unit (CPU). The CPU analyzes and processes the data based on a preset algorithm model. When it detects a deviation in flight attitude from a set value, it automatically adjusts the UAV's rotor speed, wing angle, and other actuators to achieve rapid adaptive adjustment of flight attitude. This method effectively improves the flight stability and reliability of UAVs in complex environments and can be widely applied in fields such as aerial surveying, material delivery, and environmental monitoring, ensuring efficient and safe operation of UAVs.