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Distributed control of chemical process networks

Abstract

In this paper, we present a review of the current literature on distributed (or partially decentralized) control of chemical process networks. In particular, we focus on recent developments in distributed model predictive control, in the context of the specific challenges faced in the control of chemical process networks. The paper is concluded with some open problems and some possible future research directions in the area.

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Correspondence to Jie Bao.

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This work was supported by Australian Research Council (ARC) Discovery Project (No.DP130103330)

Recommended by Associate Editor Yi Cao

Michael J. Tippett received the B.Eng. degree (1st Class Honours and University Medal) in industrial chemistry from The University of New South Wales (UNSW), Australia in 2009, and the Ph.D. degree from the same university in 2014. He has held a postdoctoral fellowship at UNSW and is currently an engineer at OSIsoft LLC and an adjunct lecturer in Chemical Engineering at UNSW.

His research interests include distributed control and decision making for plant-wide process control, dissipativity based control, distributed model predictive control, and fault detection and the design of fault tolerant control systems.

Jie Bao received the B. Sc. the andM. Sc. degrees in electrical engineering from Zhejiang University, China in 1990 and 1993, respectively. In 1998, he received the Ph.D. degree in chemical engineering (process control) from The University of Queensland, Australia. He spent one year at University of Alberta as a postdoctoral fellow and then joined the faculty at The University of New South Wales, Australia. He is currently a full professor in the School of Chemical Engineering, UNSW. He is an associate editor of Journal of Process Control.

His research interests include distributed and decentralized control, robust control, fault-tolerant control, dissipativity-based process control and control of industrial processes including aluminium smelting, mineral processing, membrane separation and flow batteries.

ORCID iD: 0000-0002-6774-9863

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Tippett, M.J., Bao, J. Distributed control of chemical process networks. Int. J. Autom. Comput. 12, 368–381 (2015). https://doi.org/10.1007/s11633-015-0895-9

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  • DOI: https://doi.org/10.1007/s11633-015-0895-9

Keywords

  • Distributed process control
  • chemical process systems
  • process networks
  • plantwide control
  • distributed model predictive control