Intelligent Control Theory and Technologies

Intelligent Control Theory and Technologies

Zude Zhou (Wuhan University of Technology, China), Huaiqing Wang (City University of Hong Kong, Hong Kong) and Ping Lou (Wuhan University of Technology, China)
DOI: 10.4018/978-1-60566-864-2.ch009
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Abstract

In the previous chapters, the theoretical and technological foundations of MI have been investigated, they include, knowledge-based system, multi-agent system, data mining and knowledge discovery, computing intelligence, process and system modeling, sensor integration and data fusion, and group technologies. As another very important branch of MI, intelligent control theory and technology will be discussed in this chapter. The chapter should be viewed as a resource for those in the early stages of considering the development and implementation of intelligent controllers for industrial applications. It is impossible to provide the full details of a field as large and diverse as intelligent control in a single chapter. Hence, the focus is placed on the fundamental ideas that have been found most useful in industry.
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Foundations Of Intelligent Control

The term “intelligent control” has come to mean, particularly to those outside the control area, some form of control using fuzzy and/or neural network methodologies (White & Sofge 1992). Intelligent control, however does not restrict itself only to those methodologies. In fact, according to some definitions of intelligent control not all neural/fuzzy controllers would be considered intelligent. The fact is that there are problems of control today that cannot be formulated and studied using conventional differential/difference equation mathematical framework and “conventional control” methodologies; these methodologies were developed in the past decades to control dynamical systems (Albus 1991). To address these problems in a systematic way, a number of methods have been developed in recent years that are known as “intelligent control” methodologies. There are significant differences between conventional and intelligent control. It is worth remembering at this point that intelligent control uses conventional control methods to solve “lower level” control problems, and conventional control is included in the area of intelligent control. In summary, intelligent control attempts to build upon and enhance the conventional control methodologies to solve new challenging control problems.

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