| After two decades of vigorous development,quadrotor drones have been widely used in photography,agriculture,electric power and other industries due to their low cost and high flexibility.There are many control algorithms,such as PID control,backstepping control,robust control,sliding mode control,etc.,which have their own shortcomings and advantages.This topic studies the attitude control methods of quadrotor UAVs,combined with the research results of other scholars on quadrotor UAVs in recent years,and compares the advantages and disadvantages of the above control theories.In order to improve the system’s immunity to disturbances based on the PID algorithm,A new control strategy is designed by adopting an auto-disturbance rejection control algorithm,and then combining fuzzy control and Kalman filtering.First,cascade the fuzzy controller and the NLSFE,use simple fuzzy control to tune the parameters to be adjusted in the NLSEF,reduce the number of parameters to be adjusted in the entire control system,and increase the amount of calculation to improve the adaptive ability of the system.Then,based on the design principle of the ESO in the active disturbance rejection control,the Kalman filter and the ESO are compared.Update the state estimation of Kalman filter according to the error compensation rule in ESO.The combined observer combines the advantages of Kalman filter to observe the system state and the total disturbance of the ESO compensation system,but when the error signal is relatively large,it is easy to cause the observer flutter,Therefore,this article chooses the tanh function to improve the ESO and limit the magnitude of the error compensation.The simulation experiments show that the ADRC＿FI controller can increase the control speed of the system.The ADRC＿FI reduces the flutter phenomenon of the system while ensuring the state observation and uncertainty compensation of the original observer.The application of the control system to a quadrotor UAV platform verifies its feasibility. |
