A convex optimization approach to adaptive stabilization of discrete-time LTI systems with polytopic uncertainties

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Summary This paper suggests a simple convex optimization approach to state-feedback adaptive stabilization problem for a class of discrete-time LTI systems subject to polytopic uncertainties. The proposed method relies on estimating the uncertain parameters by solving an online optimization at each time step, such as a linear or quadratic programming, and then, on tuning the control law with that information, which can be conceptually viewed as a kind of gain-scheduling or indirect adaptive control. Specifically, an admissible domain of stabilizing state-feedback gain matrices is designed offline by means of linear matrix inequality problems, and based on the online estimation of the uncertain parameters, the state-feedback gain matrix is calculated over the set of stabilizing feedback gains. The proposed stabilization algorithm guarantees the asymptotic stability of the overall closed-loop control system. An example is given to show the effectiveness of the proposed approach
Publisher
WILEY
Issue Date
2015-09
Language
English
Article Type
Article
Citation

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, v.29, no.9, pp.1116 - 1134

ISSN
0890-6327
DOI
10.1002/acs.2525
URI
http://hdl.handle.net/10203/286064
Appears in Collection
EE-Journal Papers(저널논문)
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