A MRAC Principle for a Single-Link Electrically Driven Robot with Parameter Uncertainties

Abstract

In this paper, a model reference adaptive control (MRAC) principle for a one-degree-of-freedom rigid-link electrically driven robot is presented. The proposed control methodology addresses the problem of trajectory tracking with parameter uncertainties in the dynamic model of the system and proposes adaptation laws for the electrical and mechanical parameters. Closed-loop stability is rigorously discussed, proving that the tracking error trajectories converge to the origin exponentially. With the aim of performing experimental comparisons, two control schemes are also revisited theoretically and experimentally: one is an algorithm previously reported in the literature and the other is an adaptive controller derived under the assumption that the electrical dynamics of the actuator are negligible. All the discussed controllers have been implemented in an experimental setup consisting in a rigid-link robot actuated with brushed DC motor. The comparison indicates that better results are obtained with the new MRAC scheme.

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

“…However, it is important to highlight that the exclusion of this dynamics can cause degradation in the performance of a robot [81] and even can produce system instability [82][83][84]. Few papers have incorporated such dynamics into the control algorithms when the kinematic or dynamic model of the WMR is considered.…”

Control of Unknown (Linear) Systems with Receding Horizon Learning

“…In the following, we show the performance of the proposed algorithm for a single-link robot arm with a DC motor [34].…”