Distributed control and optimization of process system networks: A review and perspective

Wentao Tang; Prodromos Daoutidis

doi:10.1016/j.cjche.2018.08.027

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Distributed control and optimization of process system networks: A review and perspective

Selected Papers on Sustainable Chemical Process Systems | Updated：2026-01-06

- Distributed control and optimization of process system networks: A review and perspective
- Distributed control and optimization of process system networks: A review and perspective
- 中国化学工程学报（英文版） 2019年27卷第7期页码：1461-1473
- Affiliations：
  
  Department of Chemical Engineering and Materials Science, University of Minnesota,MN,Minneapolis,USA,55455
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2018.08.027
  中图分类号：
- 纸质出版：2019
- Accepted：
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Wentao Tang, Prodromos Daoutidis. Distributed control and optimization of process system networks: A review and perspective[J]. 中国化学工程学报（英文版）, 2019,27(7):1461-1473.

Wentao Tang, Prodromos Daoutidis. Distributed control and optimization of process system networks: A review and perspective[J]. Chinese Journal of Chemical Engineering, 2019, 27(7): 1461-1473.
Wentao Tang, Prodromos Daoutidis. Distributed control and optimization of process system networks: A review and perspective[J]. 中国化学工程学报（英文版）, 2019,27(7):1461-1473. DOI： 10.1016/j.cjche.2018.08.027.

Wentao Tang, Prodromos Daoutidis. Distributed control and optimization of process system networks: A review and perspective[J]. Chinese Journal of Chemical Engineering, 2019, 27(7): 1461-1473. DOI： 10.1016/j.cjche.2018.08.027.

摘要

Abstract

Large-scale and complex process systems are essentially interconnected networks. The automated operation of such process networks requires the solution of control and optimization problems in a

distributed

manner. In this approach

the network is decomposed into several subsystems

each of which is under the supervision of a corresponding computing agent (controller

optimizer). The agents coordinate their control and optimization decisions based on information communication among them. In recent years

algorithms and methods for distributed control and optimization are undergoing rapid development. In this paper

we provide a comprehensive

up-to-date review with perspectives and discussions on possible future directions.

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