Position Constrained, Adaptive Control of Robotic Manipulators without Velocity Measurements

TL;DR

This paper introduces a novel adaptive output feedback control method for robotic manipulators that maintains joint position tracking within constraints and guarantees convergence without requiring joint velocity measurements.

Contribution

It proposes a velocity-free adaptive control scheme with position constraints, using a surrogate filter and barrier Lyapunov functions for stability analysis.

Findings

Ensures joint tracking error remains within a predefined region

Achieves asymptotic convergence of tracking error to zero

Validated effectiveness through simulation on a two-link robot

Abstract

This work presents the design and the corresponding stability analysis of a model based, joint position tracking error constrained, adaptive output feedback controller for robot manipulators. Specifically, provided that the initial joint position tracking error starts within a predefined region, the proposed controller algorithm ensures that the joint tracking error remains inside this region and asymptotically approaches to zero, despite the lack of joint velocity measurements and uncertainties associated with the system dynamics. The need for the joint velocity measurements are removed via the use of a surrogate filter formulation in conjunction with the use of desired model compensation. The stability and the convergence of the closed loop system are proved via a barrier Lyapunov function based argument. A simulation performed on a two-link robotic manipulator is provided in order to illustrate the feasibility and effectiveness of the proposed method.