Research On Control System Of Quadrotor UAV Based Active Disturbance Rejection Control

Quadrotor unmanned air vehicle(UAV)is often used to substitute manual to complete some dangerous and difficult tasks,benefit from its many advantages such as high degree of freedom,strong flexibility,strong adaptability to complex terrain and low cost.However,due to the physical structure limitations of the quadrotor,how to design a high stability and strong robustness controller based on the system characteristics of the quadrotor UAV is always a research difficulty.Aiming at the control problem of quadrotor UAV,firstly,the dynamic model of UAV is analyzed.Considering the internal disturbance and external disturbance of the control system,the attitude control strategy based on active disturbance rejection controller(ADRC)is designed.In view of the interference of turbulent wind field in actual flight,a Dryden turbulent wind field model is established to simulate the interference of wind field encountered when the quadrotor is flying.Secondly,in view of the problem that the ADRC has many parameters and it is difficult to achieve the optimum by manual adjustment,and considering that the traditional particle swarm optimization algorithm is not strong in exploring ability and easy to fall into local optimal value,a quadrotor ADRC parameters optimization algorithm based on fractionalorder fuzzy particle swarm optimization(FOFPSO)is proposed in this paper.The algorithm adds the characteristics of fuzzy logic and fractional order to the particle swarm algorithm,thereby enhancing the ability of particles to jump out of local minima and explore the search space more deeply.It has the advantages of fast convergence,avoiding particles from falling into the local optimal value and improving the accuracy of the solution.Finally,a physical experiment platform of quadrotor UAV based on Pixhawk flight controller is built for controller verification.To verify the feasibility of the designed controller running on the actual embedded platform,the model-based design method is adopted to deploy the controller model to the Pixhawk hardware platform,and the attitude tracking performance and anti-interference performance of the controller are verified.Then,considering that the UAV can’t use tools such as GPS to get its own position in the indoor environment,an indoor positioning system of UAV based on UWB is designed,which uses the Kalman filter method to fuse the obtained UWB data with the UAV attitude data to reduce the measurement uncertainty and improve the positioning accuracy.