Extremum Seeking for Model Reference Adaptive Control

Adaptive control with predictable parameter convergence has remained a challenge for several decades. In the special case of set point adaptation, extremum seeking permits predictable parameter convergence by design. This is because persistency of excitation requirements are met by the sinusoidal perturbation that is part of the basic control design. Here we present results of extremum seeking based adaptation of model reference control of a simple roll rate model of a fixed wing aircraft. We show simulation results where adaptive tracking is achieved, and the convergence of parameters conforms to predictions from the theory of extremum seeking. In the case of actuator failure, we show that the parameter convergence proofs of extremum seeking are directly applicable.