AFAN, a tool for the automatic design of fuzzy and neural controllers
In the recent years, the number of ASIC designs which include a fuzzy or neural controllers inside, has increased. The basic structure of these controllers is usually repeated; therefore, it seems reasonable to create a tool to automate the development of these controllers. This paper presents a software tool called AFAN, designed to generate fuzzy and neural controllers. AFAN accounts for resolution, speed and area consumption in order to select the architecture of the controller that best accommodates to a set of user specifications. The result is a file containing a VHDL code of a directly synthesizable fuzzy or neural controller. A set of examples is provided in order to show the solutions produced by AFAN with different specifications.
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- 1.C.C.Lee. “Fuzzy logic in control systems: Fuzzy logic controller, Part I”. IEEE Trans. Syst., Man, and Cybern., vol. 20, no. 2, pp. 404–418, 1990.Google Scholar
- 2.C.C.Lee. “Fuzzy logic in control systems: Fuzzy logic controller, Part II”. IEEE Trans. Syst., Man, and Cybern., vol. 20, no. 2, pp. 419–435, 1990.Google Scholar
- 3.P.Wasserman. Neurocomputing: Theory and Practice, New York: Van Nostrand Reinhold, 1990.Google Scholar
- 4.M.Sasaki, F.Ueno and T.Inoue. “A 7.5 MFLIPS fuzzy microprocessor using SIMD and logic-in memory structure”. Proc. 2nd. IEEE Int. Conf. on Fuzzy Systems, San Francisco, CA, pp. 527–534, 1993.Google Scholar
- 5.J.-S.R.Jang. “ANFIS: Adaptive-network-based fuzzy inference systems”. IEEE Trans. Syst., Man, and Cybern., vol. 23, pp. 665–685, May 1993.Google Scholar