19 results about "Wind disturbance" patented technology

This invention discloses a dynamically adjustable forest gap simulation device, belonging to the technical field of ecological experimental equipment. The device includes a supporting column, a supporting frame, a driving component, a shading component, and an intelligent control unit. The supporting column is a multi-stage telescopic structure equipped with a field anchoring mechanism. The supporting frame consists of a central connecting part and multiple radially telescopic and foldable radial arm-shaped components. The shading component is laid on the arm-shaped components to form a variable shading area. The driving component drives the arm-shaped components to extend and retract. The intelligent control unit uses off-grid photovoltaic power and can adaptively control the movement of the arm-shaped components according to preset strategies, light intensity, and wind speed parameters, realizing dynamic forest gap simulation and dynamic restoration of wind-disturbed light spots. This invention features high modularity, accurate simulation, stable structure, and suitability for long-term unattended field experiments, effectively solving the technical problems of traditional forest gap simulation devices, such as static fixation, poor dynamic effects, low intelligence level, and insufficient field adaptability.

The application discloses a kind of dual unmanned aerial vehicle anti-interference cooperative hoisting control method, system, equipment and medium, comprising: obtaining the actual state information of dual unmanned aerial vehicle and the desired state information of virtual leader;According to desired state information, the desired position information of dual unmanned aerial vehicle is calculated according to pre-set dual-machine cooperative decoupling control rule;With desired position information as input, based on the extended state observer and nonlinear anti-interference controller constructed in advance, the control input information of each unmanned aerial vehicle is output, so that the power system controls dual unmanned aerial vehicle anti-interference cooperative hoisting load according to control input information.The application introduces virtual leader, solves the problem of sling tension imbalance caused by independent trajectory planning;Based on dual-machine cooperative decoupling control rule, the problem of unmeasurable load pose caused by flexible sling is solved, and the extended state observer and nonlinear anti-interference controller are used to realize real-time estimation and active compensation for compound disturbance such as wind disturbance and sudden load.

The application discloses an anti-disturbance unmanned aerial vehicle flight control method and belongs to the technical field of unmanned aerial vehicle flight control. Firstly, the environment wind speed, vibration signal and the instantaneous error between the actual control quantity and the output target control quantity of the flight control system of the unmanned aerial vehicle in the current time period are collected; then, the wind speed-trend disturbance value is calculated based on the environment wind speed, the vibration-trend disturbance value is calculated based on the vibration signal, and proportional coefficients are set for the two types of disturbance values to obtain a disturbance compensation term; meanwhile, a dynamic correction parameter PID model is established according to the deterioration coefficient and error sign change rate of the instantaneous error; finally, the output of the dynamic correction parameter PID model is superposed with the disturbance compensation term to obtain the target control quantity of the unmanned aerial vehicle at the next moment. The application realizes the rapid suppression of external wind disturbance and vibration disturbance, improves the stability and response speed of the unmanned aerial vehicle flight control, and effectively solves the control response lag problem.

The application discloses a fixed-wing unmanned aerial vehicle wind disturbance observation and dynamic gain attitude control method, through a lightweight disturbance observer (LDO) with a calculation complexity of O(1), real-time estimation of wind disturbance is realized, and a compound dynamic gain adjustment law driven by a sliding mode surface, modulated by a single-parameter membership function and having an exponential attenuation characteristic is adopted, so that fast response and low overshoot control are realized under the condition that a wind speed sensor is not needed. The method can be embedded into a PX4 control framework and is suitable for attitude stabilization control tasks of various fixed-wing unmanned aerial vehicles. The method does not contain an augmented state structure of an ESO and does not depend on high-order terms of a sliding mode control, and belongs to a lightweight disturbance observation and dynamic gain fusion method of different technical paths.

The application belongs to the technical field of flying wing unmanned aerial vehicle control, and discloses a flying wing unmanned aerial vehicle dynamic inverse glide control method based on cascade observation. First, a flying wing unmanned aerial vehicle dynamics model is established, a nonlinear dynamic inverse method is adopted to design attitude loop and angular velocity loop control law respectively, and unmanned aerial vehicle three-channel dynamic decoupling control is realized. In view of the problem that traditional dynamic inverse control is sensitive to model accuracy and weak in anti-interference ability, a cascade extended state observer is introduced to realize real-time estimation and dynamic compensation of model uncertainty and wind disturbance. Meanwhile, a control distribution strategy based on weighted pseudo-inverse is designed to realize high-precision distribution of control moment. The simulation result shows that the method can effectively inhibit the three-channel coupling effect in the glide process of the unmanned aerial vehicle, significantly improve the trajectory tracking accuracy, attitude stability and system robustness, and adapt to the high-precision glide control requirement of the flying wing unmanned aerial vehicle.

The application relates to the technical field of unmanned plane control, and discloses a wind-resistant control method and system for a flying robot. According to the application, multi-dimensional sensing detection data are acquired in real time and combined with a state prediction equation, so that a deviation caused by external wind disturbance can be accurately separated; secondly, an adaptive law is used to estimate the prediction error, and a wind disturbance torque matched with the current wind disturbance is generated; thirdly, a filtering operation and a feedforward compensation calculation are performed on the wind disturbance torque, so that the compensation amount is converted into accurate target feedforward compensation amount, and the interference of measurement noise and estimation error is effectively inhibited; finally, the target feedforward compensation amount is fused with a baseline control amount and converted into a motor speed instruction, feedforward-feedback compound control of wind disturbance is realized, the effectiveness of original trajectory and attitude correction functions is maintained, the active inhibition capability of wind disturbance is increased, and the flight stability and wind resistance of the robot are improved.

This invention discloses a method and apparatus for guiding and safely landing an unmanned aerial vehicle (UAV) at ground facilities, comprising the following steps: Step 1, pre-landing status verification and target locking; Step 2, remote guidance during the UAV approach phase; Step 3, visual and signal fusion guidance during the precise positioning phase; Step 4, full-process safety monitoring and attitude correction during landing; and Step 5, touchdown buffering and landing lock control. All modules of this invention are implemented using existing airborne computing platforms, without requiring ultra-large models or cloud inference. State estimation, residual calculation, phase switching, and control laws are all executed in real time. Anchor point geometry, marker geometry, and safety domain are uniformly described through ground facility parameter packages. The same UAV can quickly switch between different take-off and landing stations without manual reconfiguration each time. Wind disturbance estimation is directly incorporated into the touchdown point determination, rather than being temporarily corrected outside the controller, which helps reduce the risk of lateral drift and boundary collision.

The application belongs to a kind of inspection robot operation control method, for the low degree of autonomy of existing overhead transmission line inspection robot, poor operation positioning accuracy and control stability in disturbance environment such as wind disturbance and line vibration, and lack of efficient approach and soft operation ability for loose damper bolt, provide a kind of transmission line inspection robot anti-interference servo control operation method and related device, through bolt pose acquisition and operation arm rough positioning, realize the end tool fast approach;Again based on bolt point feature deviation, combined with disturbance observer and adaptive nonlinear model predictive control to complete anti-interference visual servo alignment;After alignment, along the Z axis linear approach of end tool coordinate system, and compensate the small pose deviation through flexible device, cooperate with torque feedback control screwing end, so as to improve the degree of automation, alignment stability and screwing reliability of bolt operation in disturbance environment.

This invention discloses a hovering control method for unmanned aerial vehicles (UAVs) used for sampling in outdoor waters. The method includes: based on flight inertial data and motor telemetry signals, using a physical information neural network to prospectively estimate wind speed and generate feedforward wind-resistant commands; constructing a nonlinear disturbance observer to reconstruct the total external disturbance torque and differentially separating it from the wind disturbance torque to extract the pure water flow equivalent torque; using the pseudo-inverse of the kinematic Jacobian matrix to inversely map the water flow torque into the actual three-dimensional drag force at the end of the sampling tube; constructing a second-order adaptive impedance control model with this drag force as excitation, adjusting the control stiffness in real time according to the magnitude of the drag force, generating compliant attitude commands, and coupling them with the wind-resistant commands to generate the final control law. This invention achieves sensorless decoupling of wind and water disturbances and adaptive control combining stiffness and flexibility, improving the hovering stability and operational safety of UAVs in complex water environments.

The application discloses a kind of adaptive teleoperation control methods based on reinforcement learning.The motion state parameters and environmental contact force parameters of the end of manipulator are collected to calculate position error and contact force error, and state vector is constructed;According to the state vector, a teleoperation reinforcement learning model is constructed, the teleoperation reinforcement learning model is interactively trained with the teleoperation environment, and a trained teleoperation reinforcement learning model is obtained;The current state vector is constructed and input into the trained teleoperation reinforcement learning model, and the adjustment amount of impedance control parameter is output, and then the control parameters of the impedance controller are updated, and the joint control torque is calculated by combining the preset expected trajectory, motion state parameter and environmental contact force parameter, to drive the manipulator to perform work.The application enables the robot to automatically adjust its dynamic characteristics when facing dynamic uncertain environments such as wind disturbance and wire swing, to realize stable, accurate and compliant operation, and significantly improves the autonomy and safety of the live-line working robot.

The present application relates to the technical field of control adjustment system, and more particularly to a photovoltaic module abnormality identification method based on laser detection, which generates a clock signal synchronized with the timing of laser scanning through a hardware synchronous trigger, drives a temperature and humidity sensor, a salt spray sensor and an illumination intensity sensor to collect environmental parameters, and constructs a multi-source data set containing salt crystallization trend and environmental interference level. Based on the temperature and humidity segmented compensation reflectivity baseline, the salt spray mode switching optimizes the dust accumulation determination threshold, and the light correlation sensitivity adjusts the hot spot detection parameters, the model dynamic correction is realized. Matching the fault database triggers the hierarchical alarm mechanism, and combining the decision tree classifier verifies the time continuity to generate a diagnosis report. Through spiral path planning, multi-machine contract network protocol and wind disturbance trajectory correction, a dynamic detection path is constructed, a closed-loop control logic is formed by executing data feedback, and the misjudgment and missed detection problems in high-salt fog, temperature variation and light fluctuation environments are effectively solved.

The application discloses a multi-unmanned ship longitudinal formation control method based on a nonlinear extended state observer, which comprises the following steps: establishing a kinematics model, a dynamics model and a wind disturbance model, and analyzing the boundedness of the wind disturbance; designing a time corresponding distance increment rule, generating a reference signal, constructing a longitudinal scheduling mixer and a double closed-loop control framework; establishing a kinematics error system, and deducing an error dynamics equation; designing a backstepping controller with a geometric compensation term, and outputting an expected speed; establishing an extended state system, and introducing equivalent external disturbances as extended states; designing a nonlinear extended state observer, outputting disturbance estimation values as disturbance compensation signals, and deducing a nonlinear error system; designing an integral sliding mode surface with a continuous nonlinear function; establishing a speed error system, and designing an integral sliding mode controller with a saturation function and disturbance feedforward compensation. The application designs a robust control and collaborative compensation mechanism for the working condition of narrow channel and superimposed wind disturbance, so as to guarantee the safe and reliable operation of the multi-ship longitudinal formation.

The application relates to a two-stage robust trajectory optimization method for unmanned aerial vehicles (UAVs) facing complex low-altitude wind disturbance, which comprises the following steps: step S1: constructing a composite wind disturbance model and a UAV dynamics model; step S2: initializing and setting parameters of a main loop generated by columns and constraints; step S3: entering the main loop generated by columns and constraints of the composite wind disturbance model and the UAV dynamics model, and executing S4; step S4: obtaining the worst wind condition under the current strategy based on solving an inner-layer sub-problem; step S5: solving an outer-layer main problem; step S6: judging the convergence of a new reference trajectory and wind-disturbance-resistant control gain, and executing S7 if the convergence is achieved, otherwise executing S4; and step S7: loading the obtained optimal trajectory and control gain to a UAV flight control system. Compared with the prior art, the application has the advantages of considering conservativeness and efficiency.

The application discloses a full-body control method for unmanned aerial vehicles in a strong wind disturbance environment, and relates to the technical field of unmanned aerial vehicle control.The method comprises the following steps: selecting a corresponding target decision variable according to different wind disturbances; converting a nonlinear dynamics model of an unmanned aerial vehicle air operation system into a linear dynamics model; the unmanned aerial vehicle air operation system comprises an unmanned aerial vehicle and a mechanical arm connected with the unmanned aerial vehicle; updating a wind disturbance estimation value on line according to on-line state data of the unmanned aerial vehicle air operation system; solving a model predictive control optimization problem corresponding to the linear dynamics model according to a decision variable and the wind disturbance estimation value to obtain a control input; and controlling the unmanned aerial vehicle air operation system according to the control input.The application selects a target decision variable corresponding to wind disturbance and updates a wind disturbance estimation value on line, and then solves a suitable control input to control the system, so that the unmanned aerial vehicle air operation system can adapt to various scenes under strong wind disturbance, and the robustness and agility are improved.

The present application relates to the field of unmanned aerial vehicle control, in particular to a rotor unmanned aerial vehicle control method based on lift feedback, the rotor unmanned aerial vehicle control method based on lift feedback includes designing unmanned aerial vehicle control framework with lift feedback power system and lift closed loop controller based on rotor lift model and motor electric governor model. First, remove the motor speed inverse solution module in the traditional power system in the unmanned aerial vehicle control framework, increase the lift feedback control module, use the sensor to measure the lift generated by the rotor, realize closed loop control;Second, the power system model of multi-rotor unmanned aerial vehicle is established, the motor throttle is taken as the input, and the rotor lift is taken as the output;Finally, based on this model, the input-output linearization force closed loop controller is designed to accurately control the lift output. The method solves the problems of low control accuracy and poor flight stability of the rotor unmanned aerial vehicle in the wind disturbance environment operation or maneuvering flight process. By applying this control method to the rotor unmanned aerial vehicle to ensure its high precision control and stable flight in the wind disturbance environment and maneuvering flight process.

The present application relates to the technical field of unmanned aerial vehicle control, and particularly relates to a dynamic hovering anti-disturbance control method for unmanned aerial vehicles based on a neural network, comprising: constructing a time series convolution network as a disturbance observer to estimate total disturbance according to unmanned aerial vehicle state quantities and wind speed measurement values within a historical time window; constructing a deep deterministic policy gradient network as a controller to generate motor speed instructions according to state errors and total disturbance; jointly training the two networks through domain randomization in a simulation environment; deploying the trained networks to a flight controller, estimating total disturbance by the time series convolution network and generating speed instructions by the deep deterministic policy gradient network to drive the motor in real-time flight; and setting a safety constraint layer to perform amplitude limiting on the speed instructions or switch to a backup controller when state parameters exceed a threshold. The present application realizes high-precision hovering control under strong wind disturbance and guarantees safety and real-time performance.

The application discloses a kind of multi-rotor unmanned aerial vehicle master control in loop simulation method, system and storage medium, it is related to unmanned aerial vehicle in loop simulation technical field.Under the master control in loop simulation architecture, the virtual total thrust and virtual total torque are generated after the propulsion control instruction of master control output is modeled after propulsion chain pure lag and first-order inertia response, and virtual flight state is solved after wind disturbance is introduced into flight dynamics model;For the multi-source delay and dynamic distortion of propulsion side, dynamics calculation side, platform execution side and platform mechanism side, respectively, compensation is carried out, and the compensated predicted virtual flight state is mapped as Stewart platform reference instruction, and the inertial measurement unit is excited by platform motion, and the master control is fed back to form a closed loop.The application can restore the time sequence relationship between control instruction, propulsion response and body motion, improve the overall consistency and platform reference tracking accuracy of master control in loop simulation under wind disturbance.