Recursive Robust Regulator for Discrete-time Markovian Jump Linear Systems: Control of Series Elastic Actuators

Abstract

Impedance control for human-robot interaction allows a more secure and controllable robotic rehabilitation. High-performance force control is required to achieve a more precise impedance-controlled robotic therapy using series elastic actuators. However, the performance of these controllers is sensitive to the highly uncertain and time-varying human dynamics. In this paper, we develop a force controller of a series elastic actuator using a Recursive Robust Regulator for discrete-time Markov jump linear systems subject to parametric uncertainties. We define three Markovian modes of operation depending on the human-robot interaction dynamics. Also, we include an integral action to eliminate steady-state errors, and propose a methodology for robust tracking based on the analysis of the frequency response of the system under parametric uncertainties. Experimental results of the impedance and force controllers for a robotic platform for ankle rehabilitation are presented. These results indicate that the proposed controller maintains similar performance levels despite the transitions between different modes of operation and even subject to the uncertainties introduced by human dynamics.