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Article
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SIAM Journal on Matrix Analysis and Applications
Article . 1992 . Peer-reviewed
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Article . 2020
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Regularization of Descriptor Systems by Derivative and Proportional State Feedback

Regularization of descriptor systems by derivative and proportional state feedback
Authors: Angelika Bunse-Gerstner; Volker Mehrmann; Nancy K. Nichols;

Regularization of Descriptor Systems by Derivative and Proportional State Feedback

Abstract

Summary: For linear multivariable time-invariant continuous or discrete-time singular systems it is customary to use a proportional feedback control in order to achieve a desired closed loop behaviour. Derivative-feedback is rarely considered. This paper examines how derivative feedback in descriptor systems can be used to alter the structure of the system pencil under various controllability conditions. It is shown that derivative and proportional feedback controls can be constructed such that the closed loop system has a given form and is also regular and has index at most 1. This property ensures the solvability of the resulting system of dynamic-algebraic equations. The constructin procedures used to establish the theory are based only on orthogonal matrix decompositions and can therefore be implemented in a numerically stable way. The problem of pole placement with derivative feedback alone and in combination with proportional state feedback is also investigated. A computational algorithm for improving the ``conditioning'' of the regularized closed loop system is derived.

Keywords

Controllability, linear multivariable time-invariant continuous singular systems, computational algorithm, Canonical structure, Numerical computation of matrix norms, conditioning, scaling, Sensitivity (robustness), closed loop system, Feedback control, Computational methods in systems theory

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
101
Top 10%
Top 1%
Top 10%
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