Research And Optimization Of Flight Control Strategy For Four Rotor UAV

Four rotor UAV(Unmanned Aerial Vehicle)has been widely used in aerial monitoring,forest fire fighting,power inspection,security monitoring agricultural pesticides and other fields,which involves machinery,electronics,communication,navigation and control theory and many other disciplines related to technology,more and more universities and research institutions concerned.Four rotor UAV is a multi variables,strong coupling and interference of sensitive nonlinear underactuated system.It is very important to the study modeling and intelligent control of four rotor UAV.It is found that most of the intelligent control strategies of four rotor UAV remain in the theoretical research.In the practical four rotor UAV control system design and flight,most of the use of the classic PID control.However,the intelligent control strategy still exist many problems in the actual four rotor UAV flight process.In this thesis,the experimental platform of the four rotor UAV built by the laboratory is taken as the research object,the flight control system of the four rotor UAV is systematically researched and explored.First of all,based on the familiar four rotor UAV flight mechanism and principle,we establish an inertia coordinate system and body coordinate system.By stress analysis,a nonlinear model by Newton Euler method is established for four rotor UAV,equations of motor and brushless DC motor is given,the system parameters of four rotor are determined.Secondly,a double loop cascaded PID controller is designed to solve the problem of strong coupling and underactuated in the linear model of four rotor UAV.However,the parameters of the PID controller is mainly manual adjusted,which is not only time-consuming,but also cannot guarantee the best performance of the control system.To result the problem,we introduces the particle swarm optimization algorithm(PSO),a PSO-PID controller is designed.Furthermore,the four rotor UAV is a nonlinear system,with many uncertainties,so we can further analyze the control of the four rotor unmanned aerial vehicle(UAV).Based on the combination of adaptive control,sliding mode control,fuzzy control and particle swarm optimization(PSO)algorithm,an adaptive fuzzy sliding mode control(PSO-AFSMC)is proposed.Sliding mode control is one of the effective means to deal with the nonlinear system,and the approximation method of fuzzy reasoning system to achieve the ideal control law,the design and stability analysis of the controller in order to meet the conditions of the Lyapunov stability lyapunov,and MATLAB simulation.The simulation results show that the PSO-AFSMC controller has good dynamic performance and anti-interference ability compared with PID controller,PSO-PID controller and AFSMC controller.Finally,the experiment platform of four rotor unmanned aerial vehicle(UAV)is built.The actual flight test results show that the PSO-PID control strategy and PSO-AFSMC control strategy can change the attitude and position of good tracking,robustness and better control quality of UAV Based on PSO-AFSMC has better control of the four rotor.To some extent,the effectiveness and reliability of the proposed intelligent control strategy are demonstrated.