Optimized Robust Fuzzy Twisting Sliding Mode Control Design for Fixed Wing UAV

Abstract

This paper introduces an optimized robust Fuzzy Twisting Sliding Mode Control (FTSMC) scheme for a seven-degree-of-freedom (7DOF) Fixed Wing Unmanned Aerial Vehicle (FWUAV) model, addressing model uncertainties, external disturbances, parameter variation, and actuator dynamics. The control model, derived from the kinematics and dynamics of the FWUAV, is divided into three subsystems: position, attitude, and airspeed. The position subsystem employs a Global Positioning System (GPS) guidance method to generate desired inertial position states. The attitude subsystem assumes that all attitude states are measurable, while the airspeed subsystem’s state model incorporates wind disturbances. The proposed control strategy uses Twisting Sliding Mode Control (TSMC) to tackle the FWUAV’s control challenges related to modeling and dynamics, with fuzzy switching employed to reduce chattering in control commands. Optimal SMC gains and fuzzy normalizing gains are determined using the Particle Swarm Optimization (PSO) algorithm. Trajectory planning follows the principle of trajectory segmentation, guiding the FWUAV with minimum snap polynomial trajectories derived from existing GPS data. Extensive simulations are conducted in MATLAB Simulink to validate the effectiveness of the proposed control scheme.