Robust Adaptive Control for Constrained Dynamical Systems Following Unreliable Reference Signals

Abstract

In this paper, we present robust model reference adaptive control laws that guarantee uniform ultimate boundedness of the trajectory tracking error for nonlinear dynamical systems subject to constraints on the state space and the measured output, and affected by matched, unmatched, and parametric uncertainties, as well as uncertainties in the initial conditions. A common assumption in the design of control laws for trajectory tracking is that the reference model or the reference signal verify the constraints imposed on the closed-loop system's trajectory. The control laws presented in this paper do not rely on this assumption and guarantee satisfactory results also in case the reference trajectory or the reference output signal do not verify the given constraints and hence, may draw the plant's trajectory or measured output outside their constraint sets. A numerical example illustrates the feasibility of the theoretical results presented.