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Implicit Linear Systems

Author: J D Aplevich
Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1991.
Series: Lecture notes in control and information sciences, 152.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
These notes are an introduction to implicit models of linear dynamical systems, with applications to modelling, control system design, and identification, intended for control-system engineers at the beginning graduate level. Because they are non-oriented, the models are particularly useful where causality is unknown or may change. They are implicit in all variables and closed under the algebraic operations, and  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: J D Aplevich
ISBN: 9783540467595 3540467599
OCLC Number: 851775622
Description: 1 online resource (xi, 179 pages).
Contents: System Models --
The Kronecker form --
Analysis of singularities --
Systems of minimal dimension --
Canonical representations --
Algebraic design applications --
Optimization with quadratic cost --
System identification --
Large-scale systems --
Extensions.
Series Title: Lecture notes in control and information sciences, 152.
Responsibility: edited by J.D. Aplevich.

Abstract:

These notes are an introduction to implicit models of linear dynamical systems, with applications to modelling, control system design, and identification, intended for control-system engineers at the beginning graduate level. Because they are non-oriented, the models are particularly useful where causality is unknown or may change. They are implicit in all variables and closed under the algebraic operations, and hence are useful for computer-aided analysis and design. They possess the vector-matrix conceptual simplicity and computational feasibility of state-space equations, together with the generality of matrix-fraction descriptions, and admit of canonical forms for which the joint identification of system parameters and dynamic variables is linear. The notes simplify, generalize, and complement much recent work on "singular" or "descriptor" models, but do not duplicate it. Sections are included on realizations, canonical forms, minimal representations, algebraic design applications, quadratic optimization, identification, large-scale systems, and extensions to multi-dimensional and time-varying systems.

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