Research On Trajectory Tracking Optimization Based On Quadrotor UAV Control

The quadrotor UAV(Unmanned Aerial Vehicles)is a common rotorcraft.Because the quadrotor UAV has the advantages of takeoff,landing,maneuverability,operation and cost,it is popular in military and civilian use.Also,quadrotor UAV has been studied by many researchers and engineers.Moreover,quadrotor is a nonlinear,strong coupling and underactivity system,which brings difficulty to the establishment of the dynamic model,the acquisition of the flight attitude information,the design of the control algorithm and the controller.In order to solve the above problems,the paper designs the attitude controller and height controller based on the backstepping method after analyzing the danamic performance of the quadrotor,and carries on the trajectory tracking test to the aircraft.For the error based on the backstepping trajectory tracking simulation,the tracking algorithm based on iterative learning control is designed.The main work and contributions of this paper are as follows:First,the ground coordinate system and the body coordinate system are selected and the conversion relation between them is derived.The UAV is described using Euler angle by the paper.The paper also analyzes the basic flight principle.According to the momentum-leaf law and Newton Euler equation,a six-DOF(Degree of Freedom)nonlinear dynamics models are successfully established.Secondly,due to the non-deterministic error of the gyroscope,magnetometer and accelerometer on the quadrotor,a multi-sensor data fusion algorithm based on quaternion and extended Kalman filter is designed to estimate the attitude of the aircraft.The simulation results show the effectiveness of the algorithm.Thirdly,the attitude and height controller based on the backstepping method is designed to deal with the underactivity of the quadrotor.Lyapunov method is used to prove the stability of the algorithm.The effectiveness of the algorithm is verified by experimental simulation.Finally,the tracking algorithm based on iterative learning control is optimized for the error of tracking trajectory based on backstepping.The simulation results show that the error is gradually reduced and the preset trajectory can be well tracked with the increase of the number of iterations.