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New Results in Control of Steady-State Large-Scale Systems

Bai-Wu WAN
The State Key Laboratory for Manufacturing Systems
Xi’an Jiaotong University, P. R. China

Xiao-E RUAN
Department of Mathematics, Faculty of Science
Xi’an Jiaotong University, P. R. China

Ding LIU
School of Automation
Xi’an University of Technology, P. R. China

Abstract: This paper reviews what the first Author and his Group have been investigating for the past fifteen years in the on-line steady-state hierarchical intelligent control and optimization of large-scale industrial processes (LSIP), or large-scale systems (LSS), viz., the use of neural networks for identification and optimization, the use of expert system to solve some kind of hierarchical multi-objective optimization problems, the use of the fuzzy logic control, and the use of the iterative learning control. Several implementation examples and the product quality control for LSS are introduced too. Finally the paper suggests the new stage of development.

Keywords: Large-scale systems, industrial control, intelligent control, optimization, quality control.

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CITE THIS PAPER AS:
Bai-Wu WAN,  Xiao-E RUAN, Ding LIU, New Results in Control of Steady-State Large-Scale Systems, Studies in Informatics and Control, ISSN 1220-1766, vol. 17 (2), pp. 123-134, 2008.

1. Introduction

In the 7-th IFAC/IFORS/IMACS Symposium on Large Scale Systems Theory and Application, Beijing, China, Roberts, the first Author of this paper and Lin (1992) gave a plenary report entitled “Steady-state Hierarchical Control of Large-scale Industrial Processes: A Survey”. It considered the development of hierarchical control of LSIP in three stages: static multilevel optimization stage, steady-state hierarchical optimization stage and integrated system optimization and parameter estimation (ISOPE) stage . Fifteen years and more have passed by since then. What has been emerging in this field? And what is the fourth stage if existed?

For the past decade, the intelligent control has been a very important research direction and pushing the control science and technology forward. So do the large-scale systems theory and applications. The steady-state intelligent control of industrial processes means the application of ideas and methodologies of artificial intelligence to steady-state hierarchical control of LSIP and LSS based on human experience and knowledge in control and decision. In other words the neural networks, the expert systems (the intelligent decision unit), the fuzzy logic control, the iterative learning control, the genetic algorithms etc. and their combinations are integrated with traditional analytical approach for solving the identification, control, optimization, coordination and fault diagnosis of LSIP and LSS (Wan, 1994). Since the beginning of 1990’s the first Author and his Large-scale Systems Research Group have devoted themselves to the study of steady-state hierarchical intelligent optimizing control of LSIP and LSS for fifteen years. A brief summary of the main research results including the implementation examples in process industry and the conclusions is as follows.

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