Attitude stabilization of quadrotor UAV using Backstepping Fuzzy Logic & Backstepping Least-Mean-Square controllers

Inspired by advantages of backstepping control theory combined with rule-based control technique and with least-mean-square algorithm, this paper introduces the Backstepping Fuzzy Logic controller (BFL) and Backstepping Least Mean Square controller (BLMS) as new approaches to control the attitude stabilization of quadrotor UAV. In this paper a recursive Lyapunov function is introduced to ensure the stability around a fixed set-point using backstepping control algorithm. The BFL controller utilizes the advantage of fuzzy logic to schedule the backstepping controller parameters. This resulted in improved performance compeered with that achieved by backstepping controller alone. On the other hand, the BLMS controller is used to minimize the control efforts by finding the parameters of backstepping controller which provide minimum control efforts to the system. Finally, a comparison between Backstepping, BFL and BLMS controllers are presented. BLMS controller suffered from a slow time response while having reduced control effort when compared with the BFL controller. Combined performance of the BFL controller was superior to the backstepping or BLMS controller.