Adaptive Tracking Control of Uncertain Euler-Lagrange Systems with State and Input Constraints

TL;DR

This paper introduces a new control method for uncertain Euler-Lagrange systems that guarantees state and input constraints while achieving asymptotic tracking, verified through simulation.

Contribution

It is the first to ensure asymptotic tracking in E-L systems with explicit state and input constraints using a combined saturated and Barrier Lyapunov Function controller.

Findings

Successfully guarantees constraint satisfaction in simulations.

Ensures all closed-loop signals remain bounded.

Achieves asymptotic tracking despite uncertainties.

Abstract

This paper proposes a novel control architecture for state and input constrained Euler-Lagrange (E-L) systems with parametric uncertainties. A simple saturated controller is strategically coupled with a Barrier Lyapunov Function (BLF) based controller to ensure state and input constraint satisfaction. To the best of the authors' knowledge, this is the first result for E-L systems that guarantee asymptotic tracking with user-specified state and input constraints. The proposed controller also ensures that all the closed-loop signals remain bounded. The efficacy of the proposed controller in terms of constraint satisfaction and tracking performance is verified using simulation on a robot manipulator system.