Robust fuzzy controller for helicopter through extended state observer under external perturbation

This article investigated the positional and attitude stability of a helicopter under external interference and parametric uncertainties. Based on Euler-Newton’s theorem, the mathematical model of the system is established, which contains four inputs and six outputs. The input is the speed of the motor, and the output is the attitude and position of the drone. The design of the controller is achieved based on nonlinear fuzzy control and PID control. Due to the coupling between the pitch and the roll angle of the attitude subsystem, the system is divided into two parts, an inner ring and an outer ring. The outer ring realizes the control of altitude and yaw angle, which is independent. The inner loop produces two desired values of the angle as the input to the outer loop. At the same time, this article assumes that there is an upper bound on the disturbance and uncertainty. The extended state observer compensates for the disturbance and uncertainty of the system. Fuzzy inference rules and Radial Basis Function (RBF) functions estimate the parameters of the controller to achieve adaptive adjustment of the system states. Finally, various simulations were carried out in the MATLAB in order to verify the effectiveness of the designed controller. The performance of the proposed controller is examined by simulation, which highlightes the reliability of the controller.