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Finite-Time Control of Uncertain Linear Systems Using Statistical Learning Methods

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/20438

Finite-Time Control of Uncertain Linear Systems Using Statistical Learning Methods

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Title: Finite-Time Control of Uncertain Linear Systems Using Statistical Learning Methods
Author: Abdallah, Chaouki T.
Subject(s): Finite-Time Stability
LMIs
Disturbance Rejection
Statistical Learning Control
Abstract: In this paper we show how some difficult linear algebra problems can be “approximately” solved using statistical learning methods. We illustrate our results by considering the state and output feedback, finite-time robust stabilization problems for linear systems subject to time-varying norm-bounded uncertainties and to unknown disturbances. In the state feedback case, we have obtained in an earlier paper, a sufficient condition for finite-time stabilization in the presence of time-varying disturbances; such condition requires the solution of a Linear Matrix Inequality (LMI) feasibility problem, which is by now a standard application of linear algebraic methods. In the output feedback case, however, we end up with a Bilinear Matrix Inequality (BMI) problem which we attack by resorting to a statistical approach.
Date: 2012-04-26
URI: http://hdl.handle.net/1928/20438

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