Identification and control of Hammerstein systems with dead-zone input

Linwei Li, Xuemei Ren, Yongfeng Lv

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

2 Citations (Scopus)

Abstract

In this paper, a model predictive control (MPC) scheme based on the result of the parameter estimation is presented for Hammerstein systems with dead-zone nonlinearity. Some proper piecewise linear functions are utilized to describe the multi-value mapping characteristic of dead-zone non-linearity and then a piecewise linear parametric expression (for short, PLPE) approach is used to approximate the dead-zone function. Based on the results of PLPE approach, Hammerstein systems with dead-zone can be converted into a classical regression form which is easily estimated by using the recursive least square method. A model predictive control scheme is then developed by using the deadzone compensation for dead-zone principle and model predictive control technology. Numerical simulation results show that the system output not only tracks the reference signal with a small tracking error, but also indicates a good dynamic response.

Original languageEnglish
Title of host publicationProceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages163-168
Number of pages6
ISBN (Electronic)9781509065738
DOIs
Publication statusPublished - 2 Jul 2017
Event9th International Conference on Modelling, Identification and Control, ICMIC 2017 - Kunming, China
Duration: 10 Jul 201712 Jul 2017

Publication series

NameProceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
Volume2018-March

Conference

Conference9th International Conference on Modelling, Identification and Control, ICMIC 2017
Country/TerritoryChina
CityKunming
Period10/07/1712/07/17

Keywords

  • Hammerstien systems
  • dead-zone
  • model predictive control
  • piecewise linear parametric expression identification

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