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Toward Stochastic Realization Theory for Generalized Linear Switched Systems With Inputs: Decomposition Into Stochastic and Deterministic Components and Existence and Uniqueness of Innovation Form

We study a class of stochastic Generalized Linear Switched System (GLSS), which includes subclasses of jump-Markov, piecewise-linear and Linear Parameter-Varying (LPV) systems. We prove that the output of such systems can be decomposed into deterministic and stochastic components. Using this decompo...

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Published in:IEEE control systems letters 2024-01, Vol.8, p.1841-1846
Main Authors: Rouphael, Elie, Mejari, Manas, Petreczky, Mihaly, Belkoura, Lotfi
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Petreczky, Mihaly
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description We study a class of stochastic Generalized Linear Switched System (GLSS), which includes subclasses of jump-Markov, piecewise-linear and Linear Parameter-Varying (LPV) systems. We prove that the output of such systems can be decomposed into deterministic and stochastic components. Using this decomposition, we show existence of state-space representation in innovation form, and we provide sufficient conditions for such representations to be minimal and unique up to isomorphism.
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subjects Automatic
Engineering Sciences
innovation representation
Linear systems
Stochastic processes
stochastic realization theory
Switched systems
Switches
System identification
Technological innovation
White noise
title Toward Stochastic Realization Theory for Generalized Linear Switched Systems With Inputs: Decomposition Into Stochastic and Deterministic Components and Existence and Uniqueness of Innovation Form
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