Genetic Algorithm‐Based Non‐Singular Fast Terminal Sliding Mode Control of a Quadrotor With Thrust and Mechanical Link Deflection Fault

ABSTRACT In this article, a novel mathematical model of a quadrotor UAV (Unmanned Aerial Vehicle) suffering from one type of structural fault, angle deflection in a motor and the corresponding mechanical link, has been derived. Such faults add additional nonlinear terms to the differential equations of motion and change the 3D configuration of the UAV. These nonlinear terms rely significantly on the unknown fault angles, which are estimated via a Radial Basis Function Neural Network (RBFNN). Moreover, a Non‐singular Fast Terminal Sliding Mode Control (NFTSMC) scheme optimized by a Genetic Algorithm (GANFTSMC) has been designed for trajectory tracking and reduction of control effort. Simulation results for the entire closed‐loop system, using three different types of reference signals and fault angles, demonstrate the significant performance of the proposed controller in the presence of structural faults and external disturbances. Furthermore, the settling time of error dynamics of the system states to the origin has been finite, and the superior performance of our proposed control strategy has been validated via comparison with other robust nonlinear control techniques implemented in the literature.