A regularized on-line sequential extreme learning machine with forgetting property for fast dynamic hysteresis modeling

Zelong Wu, Hui Tang, Sifeng He, Jian Gao, Xin Chen, Chengqiang Cui, Yunbo He, Kai Zhang, Huawei Li, Yangmin Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Piezoelectric ceramics(PZT)actuator has been widely used in flexure-guided nanopositioning stage because of their high resolution. However, it is quite hard to achieve high-rate precision positioning control because of the complex hysteresis nonlinearity effect of PZT actuator. Thus, an online RELM algorithm with forgetting property(FReOS-ELM) is proposed to handle this issue. Firstly, we adopt regularized extreme learning machine(RELM)to build an intelligent hysteresis model. The training of the algorithm is completed only in one step, which avoids the shortcomings of the traditional hysteresis model based on artificial neural network(ANN) that slow training speed and easy to fall into the local minimum. Then, based on the regularized on-line sequential extreme learning machine(ReOS-ELM), an on-line RELM algorithm with forgetting property(FReOS-ELM) is designed, which can avoid the computational load of ReOS-ELM in the process of adding new data for learning on-line. In the experiment, a real-time voltage signal with varying frequencies and amplitudes is adopted, and the output displacement data of the nanopositioning stage is also acquired and analyzed. The results powerfully verify that the performance of the established hysteresis model based on the proposed FReOS-ELM is satisfactory, which can be used to improve the practical positioning performance for flexure nanopositioning stage.
Original languageEnglish
Title of host publicationIROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
Pages383-388
Number of pages6
Volume2017-September
ISBN (Electronic)9781538626825
DOIs
Publication statusPublished - 13 Dec 2017
Event2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 - Vancouver, Canada
Duration: 24 Sept 201728 Sept 2017

Conference

Conference2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
Country/TerritoryCanada
CityVancouver
Period24/09/1728/09/17

Keywords

  • flexure
  • FReOS-ELM
  • hysteresis nonlinearity
  • nanopositioning stage
  • Piezoelectric ceramics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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