Robust Command-Filtered Control With Prescribed Performance for Flexible-Joint Robots
Yang Zhang, Yanqiang Lei, Tichong Zhang, Rui Song, Yibin Li, Fuxin Du
Abstract
This article proposes a robust command-filtered control method with prescribed performance for flexible-joint robots (FJRs) wherein matched and mismatched disturbances are compensated by designing generalized proportional integral disturbance observers (GPIOs). The contributions are threefold. Firstly, a prescribed performance function (PPF), compared with that of the previous schemes, frees the assumption that the initial value of tracking errors within a predetermined region and thus is global, which brings dynamic response and steady-state precision benefits. Secondly, unlike most existing backstepping controllers that handle only internal uncertainties, the method presented here also considers time-varying external disturbances which may affect the tracking performance of the FJRs. Thirdly, a second-order command filter and a filter error compensation method are designed to avoid the ”complexity explosion” problem encountered in the traditional backstepping scheme. Analysis with the Lyapunov function proves the asymptotical stability of the closed-loop system. Simulation and experiments are performed to validate the feasibility and fine performance of the recommended control strategy.