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https://hdl.handle.net/2440/78402
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Type: | Journal article |
Title: | Gain-scheduled worst-case control on nonlinear stochastic systems subject to actuator saturation and unknown information |
Author: | Shi, P. Yin, Y. Liu, F. |
Citation: | Journal of Optimization Theory and Applications, 2013; 156(3):844-858 |
Publisher: | Kluwer Academic/plenum Publ |
Issue Date: | 2013 |
ISSN: | 0022-3239 1573-2878 |
Statement of Responsibility: | Peng Shi, Yanyan Yin, Fei Liu |
Abstract: | In this paper, we propose a method for designing continuous gain-scheduled worst-case controller for a class of stochastic nonlinear systems under actuator saturation and unknown information. The stochastic nonlinear system under study is governed by a finite-state Markov process, but with partially known jump rate from one mode to another. Initially, a gradient linearization procedure is applied to describe such nonlinear systems by several model-based linear systems. Next, by investigating a convex hull set, the actuator saturation is transferred into several linear controllers. Moreover, worst-case controllers are established for each linear model in terms of linear matrix inequalities. Finally, a continuous gain-scheduled approach is employed to design continuous nonlinear controllers for the whole nonlinear jump system. A numerical example is given to illustrate the effectiveness of the developed techniques. |
Keywords: | Continuous gain scheduling Actuator saturation Worst-case control Unknown information Markov jump system Stochastic stability Nonlinear equations and systems Hybrid systems |
Rights: | © Springer Science+Business Media, LLC 2012 |
DOI: | 10.1007/s10957-012-0142-2 |
Published version: | http://dx.doi.org/10.1007/s10957-012-0142-2 |
Appears in Collections: | Aurora harvest Electrical and Electronic Engineering publications |
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