On computation of optimal controllers subject to quadratically invariant sparsity constraints

We consider the problem of constructing optimal sparse controllers. It is known that a property called quadratic invariance of the constraint set is important, and results in the constrained minimum-norm problem being soluble via convex programming. We provide an explicit method of computing H/sub 2...

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Bibliographic Details
Published in2004 American Control Conference Proceedings; Volume 6 of 6 Vol. 6; pp. 5659 - 5664 vol.6
Main Authors Rotkowitz, M., Lall, S.
Format Conference Proceeding Journal Article
LanguageEnglish
Published Piscataway NJ IEEE 01.01.2004
Evanston IL American Automatic Control Council
Subjects
Applied sciences
Automobiles
Computer science; control theory; systems
Constraint optimization
Control systems
Control theory. Systems
Distributed control
Exact sciences and technology
Linear systems
Nonlinear control systems
Optimal control
Quadratic programming
Space vehicles
Testing
Invariant
Diagonal matrix
optimization
Optimal control
H
Invariant set
Convex programming
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Summary:We consider the problem of constructing optimal sparse controllers. It is known that a property called quadratic invariance of the constraint set is important, and results in the constrained minimum-norm problem being soluble via convex programming. We provide an explicit method of computing H/sub 2/-optimal controllers subject to quadratically invariant sparsity constraints, along with a computational test for quadratic invariance. As a consequence, we show that block diagonal constraints are never quadratically invariant unless the plant is block diagonal as well.
Bibliography:SourceType-Scholarly Journals-2
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ISBN:9780780383357
0780383354
ISSN:0743-1619
DOI:10.23919/ACC.2004.1384756