Modeling and control of complex industrial processes using artificial intelligence techniques

Wei Li, Yong Wei Li, Qi Shi Wu

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

Abstract

Complex industrial processes possess several critical features, such as uncertainty, nonlinearity, and large delay, which present significant challenges to the construction of real-time control models. This paper proposes a particle filter-based radial basis function (RBF) neural network to model and control complex industrial processes. The proposed method employs the particle filter technique for estimating the system's prior information to improve the RBF neural network's learning speed and expression capability, hence making real-time control possible with satisfactory static and dynamic performances. The proposed modeling method is applied to a real-life synthetic ammonia decarbonization process for performance evaluation. The simulation and experimental results illustrate that the proposed neural network system steadily refines the parameters as this real-life process proceeds and achieves a higher level of modeling accuracy than an existing method using a fuzzy neural network. The proposed method provides an effective approach to model and control similar complex industrial processes.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Machine Learning and Cybernetics
PublisherIEEE Computer Society
Pages1341-1345
Number of pages5
ISBN (Electronic)9781479902576
DOIs
StatePublished - Jan 1 2013
Externally publishedYes
Event12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 - Tianjin, China
Duration: Jul 14 2013Jul 17 2013

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume3
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Other

Other12th International Conference on Machine Learning and Cybernetics, ICMLC 2013
CountryChina
CityTianjin
Period7/14/137/17/13

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction

Keywords

  • Complex industrial process
  • Modeling and optimal control
  • Particle filter
  • RBF neural network
  • Synthetic ammonia decarbonization

Fingerprint Dive into the research topics of 'Modeling and control of complex industrial processes using artificial intelligence techniques'. Together they form a unique fingerprint.

Cite this