Robust adaptive finite-time parameter estimation and control of nonlinear systems

Abstract

This paper exploits an alternative adaptive parameter estimation and control approach for nonlinear systems. An auxiliary filter is developed to derive a representation of the parameter estimation error, which is combined with an adaptive law to guarantee the exponential convergence of the control error as well as the estimation error. The proposed method is further improved via a sliding mode technique to achieve the finite-time (FT) error convergence. The traditional persistent excitation (PE) is simplified as an a priori verifiable sufficiently rich (SR) requirements on the demand signal. The robustness of the control schemes with bounded disturbances is also investigated. The developed methods are finally tested via simulations.