A neurodynamic optimization approach to robust pole assignment for synthesizing linear state feedback control systems

Xinyi Le, Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

This paper presents a neurodynamic optimization approach to robust pole assignment for synthesizing linear control systems via state feedback. A pseudoconvex objective function is minimized as a robustness measure. A neurodynamic model is applied whose global convergence was theoretically proved for constrained pseudoconvex optimization. Compared with existing approaches on benchmark problems, the convergence of proposed neurodynamic approach to global optimal solutions can be guaranteed. Simulation results of the proposed neurodynamic approach is reported to demonstrate its superiority.

Original languageEnglish
Title of host publication2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6806-6811
Number of pages6
ISBN (Print)9781467357173
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
Duration: 10 Dec 201313 Dec 2013

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Conference

Conference52nd IEEE Conference on Decision and Control, CDC 2013
Country/TerritoryItaly
CityFlorence
Period10/12/1313/12/13

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