ADAPTIVE SLIDING MODE CONTROL FOR THE LONGGITUDIAL OF FIXED- WING UAV

Abstract

The paper presents a method for synthesizing an adaptive sliding mode control system for the longitudinal of a fixed-wing unmanned aerial vehicle (UAV). In this method, the dynamic model of the fixed-wing UAV takes into account model uncertainties and state-dependent disturbances. The controller is synthesized based on modern control theory, including sliding mode control, adaptive control, and the Radial Basis Function (RBF) artificial neural network. The obtained results include the identification laws for adjusting the uncertain components and the sliding mode controller for the desired altitude of the fixed-wing UAV. The research results are demonstrated through rigorous mathematical proofs and simulated using Matlab Simulink software to confirm the accuracy and effectiveness of the proposed control method. The proposed control law exhibits high control quality, adaptability, and robustness against uncertainties. The research results can be applied to design the vertical channel control system for a fixed-wing UAV in practical applications.