A new particle swarm optimization technique with iterative learning control for high precision motion

Yi Cheng Huang, Ming Chi Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper develops a new Improved Particle Swarm Optimization (IPSO) technique for adjusting the gains of PID controller, Iterative Learning Control (ILC) and the bandwidth of zero-phase Butterworth filter of the ILC. The conventional ILC learning process has the potential to excite rich frequency contents and to learn the error signals. However the learnable and unlearnable error signals should be separated for bettering control process along with the repetitions. Since producing a high frequency error condition should be avoided before the phase margin cause any trouble. Learnable error signals through a bandwidth tuning mechanism should be adaptively injected into learning control laws and thus reduce the tracking error effectively at every repetition. The filter bandwidth should be changed at every repetition for the shape of errors at frequency response thinking. Thus adaptive bandwidth in the ILC controller with the aid of IPSO tuning is proposed here. Simulation results show the new controller can cancel the errors efficiently as the process is repeated. Simulation results validate the effectiveness of the new IPSO-ILC for precision motion control.

Original languageEnglish
Title of host publicationApplied System Innovation - Proceedings of the International Conference on Applied System Innovation, ICASI 2015
EditorsArtde Donald Kin-Tak Lam, Stephen D. Prior, Teen-Hang Meen
PublisherCRC Press/Balkema
Pages1081-1086
Number of pages6
ISBN (Print)9781138028937
Publication statusPublished - 2016 Jan 1
EventInternational Conference on Applied System Innovation, ICASI 2015 - Osaka, Japan
Duration: 2015 May 222015 May 27

Publication series

NameApplied System Innovation - Proceedings of the International Conference on Applied System Innovation, ICASI 2015

Other

OtherInternational Conference on Applied System Innovation, ICASI 2015
CountryJapan
CityOsaka
Period15-05-2215-05-27

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All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Optimization
  • Control and Systems Engineering
  • Social Sciences (miscellaneous)
  • Electrical and Electronic Engineering

Cite this

Huang, Y. C., & Hsu, M. C. (2016). A new particle swarm optimization technique with iterative learning control for high precision motion. In A. D. K-T. Lam, S. D. Prior, & T-H. Meen (Eds.), Applied System Innovation - Proceedings of the International Conference on Applied System Innovation, ICASI 2015 (pp. 1081-1086). (Applied System Innovation - Proceedings of the International Conference on Applied System Innovation, ICASI 2015). CRC Press/Balkema.