Extended state observer‐based sliding mode fault‐tolerant control for unmanned autonomous helicopter with wind gusts

Abstract

This study proposes a sliding mode fault-tolerant control (FTC) scheme for the medium-scale unmanned autonomous helicopter with rotor flapping dynamics in the presence of wind gusts and actuator faults using extended state observer technique. The radial basis function neural networks are employed to tackle the unknown non-linear interaction functions and adaptive neural network extended state observers are constructed to estimate the unknown wind gusts. Meanwhile, the adaptive fault observers are developed to estimate the fault parameters in position, attitude and flapping motion subsystems. With the aim of obtaining satisfactory trajectory tracking performance, a robust adaptive sliding mode FTC scheme is presented based on the backstepping sliding mode control technique and the closed-loop system stability is rigorously proved via Lyapunov analysis. Simulation results are carried out to validate the effectiveness of the proposed control method.