## This paper deals with the problem of continuous learning in process control. Conventional machine learning applied to process control tries to obtain control rules from an historic data file or a model. However, these learned rules may be useless if the real process changes, and this is not unus
A framework for fuzzy knowledge based control
β Scribed by N. Gaertner; B. Thirion
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 238 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0038-0644
No coin nor oath required. For personal study only.
β¦ Synopsis
Two major problems appear during the design of a framework. The first is related to synthesizing generic elements for a family of applications and connecting them to an integrated control flow. The second lies in the design of a powerful, modular, reliable architecture that is easy to (re)use and understand. The fact of including design patterns in the architecture of frameworks minimizes the second problem. Indeed, design patterns provide proven, flexible, well-engineered design solutions at a higher abstraction level than classes. Their associated documentation records information from experienced object-oriented designers about solutions to recurrent problems, about contexts in which the patterns are applicable, about forces involved and consequences related to their use. This paper presents a number of the benefits of integrating design patterns in the development of an object-oriented framework related to fuzzy logic control. It also reports on an object-oriented design for Fuzzy Knowledge Based Control (FKBC) that includes design patterns to facilitate the development, maintenance and documentation of the FKBC framework.
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This paper was also published in German in Chem. Ing. Tech. 72 (2000) No. 5, pp. 477Β±483.