A two-time-scale neurodynamic approach to robust pole assignment

Xinyi Le, Jun Wang

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

2 Citations (Scopus)

Abstract

This paper presents a two-time-scale neurodynamic optimization approach to robust pole assignment for synthesizing linear control systems. The problem is formulated as a bi-convex optimization problem with spectral or Frobenious condition number as robustness measure. Coupled recurrent neural networks are applied for solving the formulated problem in different time scales. Simulation results of the proposed neurodynamic approach for benchmark problems and control of autonomous underwater gliders are reported to demonstrate its superiority.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Advanced Computational Intelligence, ICACI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages60-67
Number of pages8
ISBN (Electronic)9781467377829
DOIs
Publication statusPublished - 7 Apr 2016
Externally publishedYes
Event8th International Conference on Advanced Computational Intelligence, ICACI 2016 - Chiang Mai, Thailand
Duration: 14 Feb 201616 Feb 2016

Publication series

NameProceedings of the 8th International Conference on Advanced Computational Intelligence, ICACI 2016

Conference

Conference8th International Conference on Advanced Computational Intelligence, ICACI 2016
Country/TerritoryThailand
CityChiang Mai
Period14/02/1616/02/16

Keywords

  • Frobenious condition number
  • robust pole assignment
  • spectral condition number
  • two-time-scale neural network
  • underwater vehicle control

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