Improved Particle Swarm Optimization by Updating Constraints of PID Control for Real Time Linear Motor Positioning

Yi-Cheng Huang, Ying Hao Li

Research output: Contribution to journalArticle

Abstract

This paper proposes an Improved Particle Swarm Optimization (IPSO) technique for adjusting the gains of a Proportional-Integral-Derivative PID controller. The new approach introduces particle space constraints to improve velocity updating performance and position updating capability. This study presents numerical simulations and experimental results based on PID, PSO-PID, and IPSO-PID control systems. Real time experimental results show that the proposed IPSO algorithm has great computational convergence and ensures the stability of the controlled system without strict constraints on updating velocity. Tests on a linear synchronous motor (LSM) using a digital signal Microchip (dsPIC) processor demonstrate the effectiveness and robustness in positioning with disturbance excitation.

Original languageEnglish
Pages (from-to)425-437
Number of pages13
JournalIntelligent Automation and Soft Computing
Volume19
Issue number3
DOIs
Publication statusPublished - 2013 Aug 1

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Linear Motor
PID Control
Linear motors
Three term control systems
Particle swarm optimization (PSO)
Positioning
Particle Swarm Optimization
Updating
PID Controller
Experimental Results
Particle Swarm Optimization Algorithm
Optimization Techniques
Synchronous motors
Excitation
Disturbance
Directly proportional
Control System
Robustness
Derivative
Numerical Simulation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Software
  • Computational Theory and Mathematics
  • Artificial Intelligence

Cite this

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Improved Particle Swarm Optimization by Updating Constraints of PID Control for Real Time Linear Motor Positioning. / Huang, Yi-Cheng; Li, Ying Hao.

In: Intelligent Automation and Soft Computing, Vol. 19, No. 3, 01.08.2013, p. 425-437.

Research output: Contribution to journalArticle

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