Reinforcing Transient Response of Adaptive Control Systems Using Modified Command and Reference Model

Although adaptive control has been explored for various aerospace applications, there exists an inherent tradeoff between the convergence of the tracking error and the robustness by using high-gain learning to improve the transient behavior and operation safety. This paper studies novel strategies to enhance the transient response of model reference adaptive control (MRAC) for nonlinear aircraft systems with unmatched dynamics. We first develop a new compensator containing the undesired transient residual error to modify the external command. This can tune the command signal to be tracked to reshape the closed-loop system dynamics, whilst the original tracking objective is retained. Moreover, to diminish the potential high-frequency oscillations induced by the high-gain learning in the adaptive law, we resort to an error feedback term in the reference model to accelerate the convergence of the tracking error. In this new MRAC framework, a higher learning gain could be used to improve the tracking error convergence without triggering oscillations. We prove the closed-loop system stability, analyze the enhanced transient performance and examplify the robustness of the proposed adaptive control system. Two numerical examples with benchmark aircraft models are used to show the effectiveness of the proposed strategies.