Uniform global asymptotic stability of adaptively controlled nonlinear systems via strict Lyapunov functions
Abstract
We study a class of adaptive tracking control problems under persistency of excitation that implies both asymptotic tracking and parameter identification. We prove uniform global asymptotic stability of the adaptively controlled dynamics by explicitly constructing a strict Lyapunov function from a nonstrict one. We then allow time varying uncertainty in the unknown parameters, and construct input-to-state stable Lyapunov functions under suitable bounds on the uncertainty and an affine growth assumption on the regressor. This allows us to quantify the effects of uncertainties on both the tracking and parameter estimation errors. We illustrate our results on the Rossler system.