Adaptive Control Allocation for Uncertain Systems with Unknown Effector Degradation

Unknown effector degradation and model uncertainties risk weakening the performance of any system. Model reference adaptive control and adaptive control allocation methods are effective solutions for over-actuated uncertain vehicles to overcome these phenomena because of their ability to estimate unknown effects. Thus, this work proposes a joint structure of adaptive control allocation and model reference adaptive control solutions for compensating the effects of unknown effector degradation and model uncertainties on attitude performance, respectfully. Specifically, Lyapunov stability analysis is provided to prove closed-loop system stability, and simulation results are presented on a multi-rotor to show that the proposed adaptive method improves command tracking performance on attitude dynamics in the presence of unknown effector degradation and uncertain center of gravity location.