Design of single neuron PID multi-variable controller based on evolving PSO

  • Guanghui Wang*
  • , Jie Chen
  • , Feng Pan
  • *Corresponding author for this work

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

Abstract

Coupling multi-variable controller contains some problems of complex nonlinear control. Single neuron PID controller has a good capability of self-adapting, self-learning, nonlinear and robustness. This paper uses some single neuron PID controllers to design coupling multi-variable controller, accompanying a large amount of optimization problem of nonlinear multi-dimension complex function. To solve that problem, evolving PSO has been proposed in this paper. To ravel out particle swarm optimization's (PSO) problem of local minima, crossover and mutation operations have been added to it. Simulation experiments of two typical objects have been made, and demonstrate the effectiveness and superiority of the proposed algorithm. This designed controller has a good performance. Evolving PSO can solve the complex problem in this controller design effectively.

Original languageEnglish
Title of host publicationProceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08
Pages8656-8660
Number of pages5
DOIs
Publication statusPublished - 2008
Event7th World Congress on Intelligent Control and Automation, WCICA'08 - Chongqing, China
Duration: 25 Jun 200827 Jun 2008

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference7th World Congress on Intelligent Control and Automation, WCICA'08
Country/TerritoryChina
CityChongqing
Period25/06/0827/06/08

Keywords

  • Coupling multi-variable control
  • PSO
  • Single neuron PID

Fingerprint

Dive into the research topics of 'Design of single neuron PID multi-variable controller based on evolving PSO'. Together they form a unique fingerprint.

Cite this