State and Input Constrained Adaptive Tracking Control of Uncertain Euler-Lagrange Systems with Robustness and Feasibility Analysis

TL;DR

This paper introduces a novel adaptive tracking control method for uncertain Euler-Lagrange systems that guarantees state and input constraints are satisfied despite disturbances, with proven feasibility conditions and demonstrated effectiveness.

Contribution

It presents the first verifiable conditions for feasible control of constrained uncertain E-L systems, integrating barrier Lyapunov functions with saturated control.

Findings

Controller ensures state and input constraints are maintained.

Simulation confirms effective tracking and constraint satisfaction.

Feasibility conditions are practically verifiable.

Abstract

This paper proposes an adaptive tracking controller for uncertain Euler-Lagrange (E-L) systems with user-defined state and input constraints in presence of bounded external disturbances. A barrier Lyapunov function (BLF) is employed for state constraint satisfaction, integrated with a saturated controller that ensures the control input remains within pre-specified bounds. To the best of the authors' knowledge, this is the first result on tracking control of state and input-constrained uncertain E-L systems that provides verifiable conditions for the existence of a feasible control policy. The efficacy of the proposed controller in terms of constraint satisfaction and tracking performance is demonstrated through simulation on a robotic manipulator system.