PSO-PCA Optimization Approach for Control Design

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper, an approach for system identification and automatic control systems
design based on a combination of Particle Swarm Optimization (PSO) together with
Principal Components Analysis (PCA) is proposed. This methodology, referred to
as PSO-PCA optimization approach, incorporates the PCA concept on the PSO algorithm, which can be implemented off-line or even on-line. Different variants of the
PSO-PCA algorithm will be presented and compared with the classical PSO, in order
to evaluate the performance of the underlying algorithms, in simulations and in real
experiments.
Original languageEnglish
Title of host publicationFocus on Swarm Intelligence Research and Applications
PublisherNova Science Publishers, Inc.
Pages177-192
Number of pages16
ISBN (Print)978-1-53612-452-1
Publication statusPublished - 2017

Keywords

  • Constrained nonlinear optimization
  • Control design
  • Particle swarm optimization
  • Principal components analysis
  • System identification

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  • Cite this

    Palma, L. B., Antunes, R., Brito, V., & Gil, P. J. C. D. S. (2017). PSO-PCA Optimization Approach for Control Design. In Focus on Swarm Intelligence Research and Applications (pp. 177-192). Nova Science Publishers, Inc..