Title :
Computer-aided design of fuzzy systems based on generic VHDL specifications
Author :
Hollstein, Thomas ; Halgamuge, Saman K. ; Glesner, Manfred
Author_Institution :
Inst. of Microelectron. Syst., Darmstadt Univ. of Technol., Germany
fDate :
11/1/1996 12:00:00 AM
Abstract :
In this paper, three types of fuzzy systems and related hardware architectures are discussed: standard fuzzy controllers, FuNe I fuzzy systems, and fuzzy classifiers based on a neural network structure. Two computer-aided design (CAD) packages for automatic hardware synthesis of standard fuzzy controllers are presented: a hard-wired implementation of a complete fuzzy system on a single or multiple field programmable gate arrays (FPGA) and a modular toolbox called fuzzyCAD for synthesis of reprogrammable fuzzy controllers with architectures due to specified designer constraints. In the fuzzyCAD system, an efficient design methodology has been implemented which covers a large design space in terms of signal representations and component architectures as well as system architectures. Very high speed integrated-circuits hardware-description language (VHDL) descriptions and usage of powerful synthesis tools allow different technologies to be targeted easily and efficiently. Properties and hardware realizations of fuzzy classifiers based on a neural network are introduced. Finally, future perspectives and possible enhancements of the existing toolkits are outlined
Keywords :
control system CAD; field programmable gate arrays; fuzzy control; fuzzy neural nets; fuzzy systems; hardware description languages; logic CAD; parallel architectures; pattern classification; CAD packages; fuzzy classifiers; fuzzy controllers; fuzzy systems; fuzzyCAD; generic VHDL specifications; hardware architectures; multiple field programmable gate arrays; neural network structure; signal representations; Automatic control; Control system synthesis; Design automation; Field programmable gate arrays; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Network synthesis; Neural network hardware; Neural networks;
Journal_Title :
Fuzzy Systems, IEEE Transactions on