Pneumatic Artificial Muscle Antagonistic Joint Trajectory Tracking Using Adaptive Explicit Model Predictive Control

Abstract

In this paper, we present an explicit solution to adaptive model predictive control for a pneumatic artificial muscle (PAM) antagonistic joint trajectory tracking. Compared with the traditional model predictive control, the explicit model predictive control may pre-calculate the form of optimization solution offline, which saves the computation cost and reduce the time performance of the system. Meanwhile, we utilize an adaptive method to estimate the disturbance arbitrarily, instead of maximizing the disturbance directly. Finally, the simulation results and running time of the explicit adaptive model predictive control (EAMPC) method and the min-max model predictive control method are compared, which shows the efficiency of the proposed algorithm.