Reduced neural model predictive control strategies for a class of chemical reactors

Wei Wu, Jun Xian Chang, Chia Ju Wu, Wei Ching Hsu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

A simple model predictive control strategy based on reduced feedforward neural network (FNN) models is proposed. Under some physical constraint conditions, the short-prediction-horizon predictive control algorithm can carry out the offset-free performance for a class of nonlinear systems with input/output multiplicities. The main issue is to specify the input/output patterns for neural network architecture, and a stable, minimum-phase mode is added to reduce control structures that involve off-line identification algorithms and graphic-based determination. Finally, three examples of chemical reactors exhibiting unstable or nonminimum-phase dynamic behaviors are demonstrated to verify the proposed control scheme.

Original languageEnglish
Pages (from-to)422-431
Number of pages10
JournalJOURNAL of CHEMICAL ENGINEERING of JAPAN
Volume40
Issue number5
DOIs
Publication statusPublished - 2007 May 18

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)

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