Universal Adaptive Control of Nonlinear Systems
This work addresses the problem of stable adaptive control for general nonlinear systems with unmatched uncertainties, which is an incremental improvement for control engineers.
This paper introduces a direct adaptive control framework for nonlinear systems with unmatched model uncertainties. The method adjusts the adaptation rate online to mitigate the impact of parameter estimation transients on stability, and simulation results on various nonlinear systems demonstrate its effectiveness.
This work develops a new direct adaptive control framework that extends the certainty equivalence principle to general nonlinear systems with unmatched model uncertainties. The approach adjusts the rate of adaptation online to eliminate the effects of parameter estimation transients on closed-loop stability. The method can be immediately combined with a previously designed or learned feedback policy if a corresponding model-parameterized Lyapunov function or contraction metric is known. Simulation results of various nonlinear systems with unmatched uncertainties demonstrates the approach.