Adaptive-Robust Control of a Class of Nonlinear Systems with Unknown Input Delay

TL;DR

This paper introduces an adaptive-robust control method for uncertain nonlinear systems with unknown input delays, enhancing robustness and accuracy without prior delay knowledge, validated through experiments on a mobile robot.

Contribution

The paper proposes a novel delay-dependent control law, AROLC, that handles unknown input delays and disturbances without delay knowledge, using Razumikhin stability analysis.

Findings

AROLC effectively manages unknown input delays within a certain range.

The proposed controller demonstrates superior tracking accuracy in experiments.

System stability is proven as the system is uniformly ultimately bounded.

Abstract

In this paper, the tracking control problem of a class of uncertain Euler-Lagrange systems subjected to unknown input delay and bounded disturbances is addressed. To this front, a novel delay dependent control law, referred as Adaptive Robust Outer Loop Control (AROLC) is proposed. Compared to the conventional predictor based approaches, the proposed controller is capable of negotiating any input delay, within a stipulated range, without knowing the delay or its variation. The maximum allowable input delay is computed through Razumikhin-type stability analysis. AROLC also provides robustness against the disturbances due to input delay, parametric variations and unmodelled dynamics through switching control law. The novel adaptive law allows the switching gain to modify itself online in accordance with the tracking error without any prerequisite of the uncertainties. The uncertain system, employing AROLC, is shown to be Uniformly Ultimately Bounded (UUB). As a proof of concept, experimentation is carried out on a nonholonomic wheeled mobile robot with various time varying as well as fixed input delay, and better tracking accuracy of the proposed controller is noted compared to predictor based methodology.