期刊
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
卷 55, 期 7, 页码 1710-1715出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2010.2046935
关键词
Asymptotic convergence; nonparametric uncertainty; Nussbaum gain; repetitive learning control (RLC); universal adaptive stabilization
资金
- Hong Kong Polytechnic University [A-PC0D, A-SA63, 1-ZV0H]
We propose a continuous universal repetitive learning control to track periodic trajectory for a class of nonlinear dynamical systems with nonparametric uncertainty and unknown state-dependent control direction matrix. The proposed controller is an integration of high-gain feedback, repetitive learning and Nussbaum gain matrix selector. The control signal is always continuous, thus it avoids the potential chattering effect caused by discontinuity. Asymptotic convergence of the tracking error is achieved by the controller, and the control performance is illustrated by simulation. Although the proposed method is derived for input-state systems, it can be readily extended to multi-input-multi-output systems under appropriate assumption.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据