An observer-based decentralized tracker for sampled-data systems: An evolutionary programming approach

S. M. Guo, Z. H. Peng

Research output: Contribution to journalReview article

8 Citations (Scopus)

Abstract

Decentralized control is a practical control methodology for large-scale multivariable systems. This paper presents a LQR design methodology to design a state-feedback decentralized high-gain analog controller, which gives the desired decentralized performance of the controlled analog system. Then, a prediction-based decentralized low-gain digital controller is developed from the decentralized high-gain analog controller for the hybrid controlled system. As a result, the complexity and cost of hardware implementation of the controller can be significantly reduced. In order to improve the performance of the decentralized hybrid system, the evolutionary programming (EP) is employed to tune the observer-based decentralized tracker. Some examples are presented to illustrate the developed design methodology.

Original languageEnglish
Pages (from-to)421-449
Number of pages29
JournalInternational Journal of General Systems
Volume34
Issue number4
DOIs
Publication statusPublished - 2005 Aug 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Computer Science Applications

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