Modeling and adaptive tracking for a class of stochastic Lagrangian control systems
Date
2013
Authors
Cui, M.
Wu, Z.
Xie, X.
Shi, P.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Automatica, 2013; 49(3):770-779
Statement of Responsibility
Ming-Yue Cui, Zhao-Jing Wu, Xue-Jun Xie, Peng Shi
Conference Name
Abstract
This paper focuses on the problem of modeling and adaptive tracking for a class of stochastic Lagrangian control systems with unknown parameters. By reasonably introducing random noise, a method to construct stochastic Lagrangian control systems is given. Under some milder assumptions, an adaptive tracking controller is designed such that the mean square of the tracking error converges to an arbitrarily small neighborhood of zero by tuning design parameters. The reasonability of assumptions and the efficiency of the controller are demonstrated by a mechanics model in random vibration environment.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
Copyright © 2012 Elsevier Ltd. All rights reserved.