ADRC Controller Design Dased On Particle Swarm Optimization Algorithm For Quadrotor

The structure and layout of quadrotors are simple,and their movement modes are diverse.Both cost and maintenance are better than fixed-wing aircraft.In the military and civilian fields,quadrotors have begun to perform tasks to make up for the deficiencies of fixed-wing aircraft.However,as an under-actuated complex system,the use of a reliable controller to control the quadrotor is also the focus of the design.Considering that the quadrotor needs to have a strong anti-disturbance ability when working,this paper adopts the active disturbance rejection control technology to design its controller,specifically the following research contents:Firstly,the structure of the quadrotor is introduced,and the principle of the quadrotor to achieve six degrees of freedom by adjusting the speed of the four propellers is analyzed in detail.Newton's law describes the translational motion of the quadrotor,Euler's equation describes the rotational motion of the quadrotor,and the mathematical model of the quadrotor is derived.Secondly,analyze and summarize the deficiencies of the PID controller,and then lead to the auto disturbance rejection controller.The principle of active disturbance rejection controller is analyzed in detail.An active disturbance rejection controller is designed for the attitude channel and height channel of the quadrotor.According to the general rules of active disturbance rejection controller parameter tuning,the controller parameters are tuned.The simulation results show that the controller parameters obtained through the parameter tuning rules cause the system to have problems of large overshoot and obvious oscillation during the response process.Thirdly,as the particle swarm algorithm is easy to converge prematurely,and the later the algorithm is iterated,the easier it is to converge prematurely.Based on the standard particle swarm algorithm,the adaptive weight method is used to adjust the inertia weight,and the learning factor adopts the form of synchronous learning factor,and Introduce natural selection mechanism and get improved particle swarm algorithm.Finally,in order to solve the difficult problem of auto disturbance rejection controller parameter tuning,this paper applies the improved particle swarm optimization algorithm to the auto disturbance rejection controller parameter tuning.The simulation results show that the improved particle swarm optimization algorithm has fewer iterations and higher accuracy.Compared with the cascade PID control,the auto disturbance rejection control is better than the cascade PID control in attitude tracking and disturbance rejection ability.It also shows that the improved particle swarm algorithm is effective for the parameter tuning of the auto disturbance rejection controller.