Extended‐state‐observer‐based dynamic surface control of flexible‐joint robot systems with input saturation

Abstract

Summary This article presents an extended‐state‐observer‐based dynamic surface control approach for flexible‐joint robot systems with asymmetric input saturation and large unknown dynamic knowledge. Traditional controllers for flexible‐joint robot systems usually use approximation technology to deal with unknown dynamics knowledge. Unlike the traditional control algorithm, this article utilizes an extended state observer to estimate the unknown dynamics. For the closed‐loop system, the delay strategy handles the time‐scale separation issue, the filtering system overcomes the “explosion of differentiation” caused by the repeated differentiation of auxiliary control signals, and the mean‐value‐theorem solves the input saturation problem of the actuator. The stability analysis implies that estimation errors of extended state observers (ESOs) and other state variables are semiglobally uniformly ultimately bounded. Compared with fuzzy control algorithms, the novel ESO‐based dynamic surface control approach not only omits online learning time but also uses only a few control parameters to obtain satisfactory tracking performance. Finally, a comparison simulation experiment is provided to illustrate the effectiveness of the gained conclusions.