Iterative learning control of polyhydroxybutyrate production in a sequencing batch reactor

Seyong Jung, Jie Zhang, Rui Oliveira

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

2 Citations (Scopus)

Abstract

This study investigates the iterative learning control of a sequencing batch reactor for the production of polyhydroxybutyrate (PHB). In order to overcome the effect of model plant mismatches and unknown disturbances, a batch to batch iterative learning control strategy with incrementally updated models is developed. The reference batch is taken as the immediate previous batch in order to cope with nonlinearities and process variations. After each batch, the newly obtained process operation data is added to the historical process data base and an updated linearised model is re-identified. To cope with colinearity in the modeling data, principal component regression and partial least squares regression are used in identifying batch-wise linearised models. The proposed technique has been successfully applied to a sequencing batch reactor for the production of PHB.

Original languageEnglish
Title of host publication2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages459-464
Number of pages6
ISBN (Electronic)9781479987016
DOIs
Publication statusPublished - 29 Sep 2015
Event20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 - Miedzyzdroje, Poland
Duration: 24 Aug 201527 Aug 2015

Conference

Conference20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
CountryPoland
CityMiedzyzdroje
Period24/08/1527/08/15

Keywords

  • batch processes
  • iterative learning control
  • linearised models
  • PHB
  • sequencing batch reactor

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  • Cite this

    Jung, S., Zhang, J., & Oliveira, R. (2015). Iterative learning control of polyhydroxybutyrate production in a sequencing batch reactor. In 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 (pp. 459-464). [7283919] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MMAR.2015.7283919