Gain-Scheduled Worst-Case Control on Nonlinear Stochastic Systems Subject to Actuator Saturation and Unknown Information

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Shi, Peng, Yin, Yanyan and Liu, Fei (2013) Gain-Scheduled Worst-Case Control on Nonlinear Stochastic Systems Subject to Actuator Saturation and Unknown Information. Journal of Optimization Theory and Applications, 156 (3). pp. 844-858. ISSN 1573-2878

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

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/23268
DOI https://doi.org/10.1007/s10957-012-0142-2
Subjects Historical > FOR Classification > 1106 Human Movement and Sports Science
Historical > Faculty/School/Research Centre/Department > College of Business
Keywords ResPubID25694, Continuous gain scheduling, actuator saturation, worst-case control, unknown information, Markov jump system, stochastic stability, nonlinear equations and systems, hybrid systems
Citations in Scopus 40 - View on Scopus
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