Asymptotic Tracking Control for a More Representative Class of Uncertain Nonlinear Systems With Mismatched Uncertainties

Abstract

This paper is mainly focusing on the problem of high-accuracy tracking control design for a class of nonlinear systems subject to mismatched uncertainties. A novel asymptotic control framework is presented. This is achieved by developing an estimator-based controller with an observer-based estimator, which is applied to precisely estimate all the system uncertainties. It is proved that the overall tracking system can be asymptotically stabilized. The estimation error of the system uncertainties is also ensured to be asymptotically stable. The main contribution of this paper is that the proposed solution can control a more representative class of nonlinear systems. Another key feature of this control framework is that the incorporated observer-based estimator can eliminate the assumption that system uncertainties should vary slowly or even have no variation in the existing estimators for uncertainties. This superior tracking control property of the scheme is validated by a robotic manipulator example.