Uncertainty in Artificial Intelligence
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Compiling Fuzzy Logic Control Rules to Hardware Implementations
Stephen Chiu, Masaki Togai
Abstract:
A major aspect of human reasoning involves the use of approximations. Particularly in situations where the decision-making process is under stringent time constraints, decisions are based largely on approximate, qualitative assessments of the situations. Our work is concerned with the application of approximate reasoning to real-time control. Because of the stringent processing speed requirements in such applications, hardware implementations of fuzzy logic inferencing are being pursued. We describe a programming environment for translating fuzzy control rules into hardware realizations. Two methods of hardware realizations are possible. The First is based on a special purpose chip for fuzzy inferencing. The second is based on a simple memory chip. The ability to directly translate a set of decision rules into hardware implementations is expected to make fuzzy control an increasingly practical approach to the control of complex systems.
Keywords:
Pages: 363-371
PS Link:
PDF Link: /papers/87/p363-chiu.pdf
BibTex:
@INPROCEEDINGS{Chiu87,
AUTHOR = "Stephen Chiu and Masaki Togai",
TITLE = "Compiling Fuzzy Logic Control Rules to Hardware Implementations",
BOOKTITLE = "Proceedings of the Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-87)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1987",
PAGES = "363--371"
}


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