Input-output and state-space representations of finite-dimensional linear time-invariant systems
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Various representations for systems described by aset of high-order differential equations of the form R0w + R1w + … + Rsw(s) = 0, with R0, R1,…, Rs not necessarily square matrices are developed.About:
This article is published in Linear Algebra and its Applications.The article was published on 1983-04-01 and is currently open access. It has received 119 citations till now. The article focuses on the topics: State space & Square matrix.read more
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Journal ArticleDOI
From time series to linear system-part I. Finite dimensional linear time invariant systems
TL;DR: The structural indices of such systems are introduced and it is shown how an (AR) representation of a system having a given behaviour can be constructed.
Book ChapterDOI
Models for Dynamics
TL;DR: The purpose of this paper is to give a tutorial exposition of what the authors consider to be the basic mathematical concepts in the theory of dynamical systems.
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Some basic structural properties of generalized linear systems
TL;DR: In this paper, simple characterizations of controllability, observability, of their duality and of a minimal realization of a Kalman state variable realization for generalized linear systems are proposed.
Journal ArticleDOI
Automatique et corps différentiels.
TL;DR: Differential algebra permits a straightforward and clear-cut understanding of many specific questions in control theory, such as input-output Inversion, feedback decoupling, and realization as discussed by the authors.
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Elimination in control theory
TL;DR: It is shown that the application of differential algebraic elimination theory leads to an effective method for deriving the equivalent representation of the state variables in nonlinear systems described by algebraic differential equations.
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Book
Linear Multivariable Control: A Geometric Approach
TL;DR: In this article, the authors present an approach to controlability, feedback assignment, and pole shifting in a single linear functional model, where the observer is assumed to be a dynamic observer.