Nonconvex spectral optimization algorithms for reduced‐order H∞ LPV‐LFT controllers

Summary A novel sequential semi‐definite programming method is developed for optimization subject to rank constraints on matrix‐valued nonlinear functions of matrix decision variables, which arise in reduced‐order linear parameter varying‐linear fractional transformational control synthesis. The glo...

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Vydáno v:	International journal of robust and nonlinear control Ročník 27; číslo 18; s. 4421 - 4442
Hlavní autoři:	Shi, Ye, Tuan, Hoang D., Apkarian, Pierre
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Bognor Regis Wiley Subscription Services, Inc 01.12.2017 Wiley
Témata:	Computer Science Computer simulation Data Structures and Algorithms H-infinity control Matrix methods matrix‐rank constraint Model reduction nonlinear programming Optimization Programmable logic devices reduced‐order LPV‐LFT H∞ control Solvers MATRIX-RANK CONSTRAINT LPV-LFT NONLINEAR PROGRAMMING H INFINI
ISSN:	1049-8923, 1099-1239
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Shrnutí:	Summary A novel sequential semi‐definite programming method is developed for optimization subject to rank constraints on matrix‐valued nonlinear functions of matrix decision variables, which arise in reduced‐order linear parameter varying‐linear fractional transformational control synthesis. The global convergence of the method is easily proven without any step size control. An intensive simulation shows the clear advantage of the proposed method over the state‐of‐the‐art nonlinear matrix inequality solvers. Copyright © 2017 John Wiley & Sons, Ltd.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	1049-8923 1099-1239
DOI:	10.1002/rnc.3805