Research On Adaptive Anti-interference System Of Rotorcraft In Windy Environment

The rotorcraft in the outdoor windy environment has higher requirements for the wind resistance of its system due to the obvious disturbance of the wind field.Because rotorcraft is difficult to carry wind speed sensors due to the interference of its own rotors,the current research on anti-wind disturbance of UAVs starting from control algorithms only compensates for wind disturbance effects by improving the robustness of the algorithm or adding disturbance observers,without considering the specifics.Because of the influence of wind model,the combination of wind model and controller design is the current research hotspot and difficulty.Starting from the atmospheric wind field model,this paper introduces wind speed estimation and wind disturbance compensation into the rotor flight control system,which improves the response speed and accuracy of the aircraft against wind disturbance.The main contents of this paper are as follows:1.Proposed Wind Speed Extended Kalman Filter(WS-EKF)estimation algorithmIn view of the problem that the rotorcraft itself cannot be equipped with wind measuring components,a low-and medium-altitude wind field model corresponding to wind shear and atmospheric turbulence is established according to the actual working environment and altitude of the aircraft,and this model is introduced into the state estimation module;design wind speed state EKF estimation The controller estimates the real-time wind speed to calculate the wind disturbance factor in the controller.The advantage of this method is that only the rotorcraft attitude estimation sensor is needed to estimate the wind disturbance information.2.Propose Double Cascade Wind Disturbance Calculation PID(DC-WDC-PID)control algorithmIn order to solve the problem of insufficient state variables of the classical PID algorithm participating in the control feedback of the nonlinear system,this paper proposes a positionvelocity and angle-angular velocity dual cascade PID control algorithm.The algorithm uses all the pose state variables to participate in the control feedback,which improves the controller.Response speed and accuracy.The solution module is designed at the output of the controller,and the wind disturbance factor is added to the control quantity model,so that the wind model estimation is combined with the controller design.In this paper,the controlled system model of the aircraft is used as the inverse solution module,and the output of the controller is used to obtain the solution value of the current pose state of the aircraft as the reference value of the pose sensor measurement.3.Design Unified State Vector Multi-point Fusion Extended Kalman Filter(USV-MFEKF)algorithmDue to the deviation of the single sensor unit itself,this paper designs a unified state vector to establish a state equation for each sensor in order to solve the problem of the inconsistency of the measured values of each sensor;adopts multiple sensors to measure the aircraft state,implements the separation of estimation and observation in the EKF algorithm,and measures the IMU The value is used as the state value for one-step prediction,and the measured values of other sensors are used as observation values for prediction and update.