Adaptive-Robust Control of a Class of Uncertain Nonlinear Systems Utilizing Time-Delayed Input and Position Feedback

摘要

In this paper, the tracking control problem of a class of Euler-Lagrangesystems subjected to unknown uncertainties is addressed and an adaptive-robustcontrol strategy, christened as Time-Delayed Adaptive Robust Control (TARC) ispresented. The proposed control strategy approximates the unknown dynamicsthrough time-delayed logic, and the switching logic provides robustness againstthe approximation error. The novel adaptation law for the switching gain, incontrast to the conventional adaptive-robust control methodologies, does notrequire either nominal modelling or predefined bounds of the uncertainties.Also, the proposed adaptive law circumvents the overestimation-underestimationproblem of switching gain. The state derivatives in the proposed control law isestimated from past data of the state to alleviate the measurement error whenstate derivatives are not available directly. Moreover, a new stability notionfor time-delayed control is proposed which in turn provides a selectioncriterion for controller gain and sampling interval. Experimental result of theproposed methodology using a nonholonomic wheeled mobile robot (WMR) ispresented and improved tracking accuracy of the proposed control law is notedcompared to time-delayed control and adaptive sliding mode control.