Precision motion of iterative learning controller using adaptive filter bandwidth tuning by improved particle swarm optimization technique

Yi-Cheng Huang, Shu Ting Li, Kuan Heng Peng

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

Abstract

This paper utilized the Improved Particle Swarm Optimization (IPSO) technique for adjusting the gains of PID and the bandwidth of zero-phase Butterworth Filter of an Iterative Learning Controller (ILC) for precision motion. Simulation results show that IPSO-ILC-PID controller without adaptive bandwidth filter tuning have the chance of producing high frequencies in the error signals when the filter bandwidth is fixed for every repetition. However the learnable and unlearnable error signals should b e separated for bettering control process. Thus the adaptive bandwidth of a zero phase filter in ILC-PID controller with IPSO tuning is applied to one single motion axis of a CNC tab le machine. Simulation results show that the developed controller can cancel the errors efficiently as repetition goes. The frequency response of the error signals is analyzed by the empirical mode decomposition (EMD) and the Hilbert-Huang Transform (HHT) method. Errors are reduced and validated by ILC with adaptive bandwidth filtering design.

Original languageEnglish
Title of host publicationMaterials and Diverse Technologies in Industry and Manufacture
Pages349-353
Number of pages5
DOIs
Publication statusPublished - 2013 Oct 22
Event2013 International Conference on Mechanical, Automotive and Materials Engineering, CMAME 2013 - , Hong Kong
Duration: 2013 Jul 262013 Jul 27

Publication series

NameApplied Mechanics and Materials
Volume376
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

Other2013 International Conference on Mechanical, Automotive and Materials Engineering, CMAME 2013
CountryHong Kong
Period13-07-2613-07-27

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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    Huang, Y-C., Li, S. T., & Peng, K. H. (2013). Precision motion of iterative learning controller using adaptive filter bandwidth tuning by improved particle swarm optimization technique. In Materials and Diverse Technologies in Industry and Manufacture (pp. 349-353). (Applied Mechanics and Materials; Vol. 376). https://doi.org/10.4028/www.scientific.net/AMM.376.349