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

Xinyi Le, Zheng Yan, Jun Wang

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

1 Citation (Scopus)

Abstract

This paper presents a neurodynamic optimization approach to robust pole assignment for synthesis of piecewise linear control systems via state feedback. The robust pole assignment is formulated as a pseudoconvex optimization problem with linear equality constraints where a robustness measure is considered as the objective function. The robustness is achieved by means of minimizing the spectral condition number of the closed-loop eigensystem. Two recurrent neural networks with guaranteed global convergence are applied for solving the optimization problem in real time. Simulation results are included to substantiate the effectiveness and demonstrate the characteristics of the proposed approach.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Information and Automation, ICIA 2013
Pages1334-1339
Number of pages6
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Information and Automation, ICIA 2013 - Yinchuan, China
Duration: 26 Aug 201328 Aug 2013

Publication series

Name2013 IEEE International Conference on Information and Automation, ICIA 2013

Conference

Conference2013 IEEE International Conference on Information and Automation, ICIA 2013
Country/TerritoryChina
CityYinchuan
Period26/08/1328/08/13

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