Research On Autonomous Obstacle Avoidance Of Quadrotor System Based On ADRC

In recent years,the multi-rotor UAV has been widely used in the inspection,security,mapping and other industries because of its simple mechanical structure and excellent maneuverability.However,its autonomous flight safety,especially under the environment with many obstacles has attracted more and more attention.Therefore,the thesis carries out the research on the autonomous obstacle avoidance and flight control algorithm of quadrotor based on ADRC.The main works and innovation points of this thesis are summarized as follows:Firstly,according to the structure and configuration of the quadrotor,the quadrotor’s mathematical model of six degrees of freedom is presented.Secondly,according to the configuration of airborne sensors,the attitude algorithm based on quaternion algorithm and the integrated navigation algorithm based on extended kalman filter are designed to get accurate and stable aircraft attitude angle,speed,location and other information.Then,using the ADRC control theory,the thesis studies the flight control algorithm of quadrotor based on ADRC.For the control system of quadrotor is easy to appear the course of the channel controller integral saturation problem,the gearshift integral saturation resistance heading control algorithm is proposed to solve this problem.Finally,using laser radar sensor,considering the main constraints in the quadrotor dynamic model,this thesis puts forward the obstacle avoidance algorithm based on improved potential field method.The experimental tests show that the design of the quadrotor flight control algorithm based on ADRC for strong coupling,nonlinear,with unknown disturbance can be implemented without steady-state error posture,trajectory control,and has strong robustness.At the same time,the design based on the variable integral saturation resistance course channels flight control algorithm makes the course to achieve higher steady-state accuracy and has small overshoot and short transition time.The proposed obstacle avoidance algorithm based on improved potential field method can also work normally in outdoor with highlight.