標題: On the equivalence of a table lookup (TL) technique and fuzzy neural network (FNN) with block pulse membership functions (BPMFs) and its application to water injection control of an automobile
作者: Wang, Chi-Hsu
Wen, Jung-Sheng
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: fuzzy neural network (FNN);membership functions (MFs);optimal training;table lookup (TL) controller
公開日期: 1-Jul-2008
摘要: This paper presents an alternative method to design a fuzzy neural network (FNN) using a set of nonoverlapped block pulse membership functions (BMPFs), and this FNN with nonoverlapped BPMFs will be shown to be equivalent to the conventional table lookup (TL) technique. Therefore, the hidden links between TL and FNN techniques are revealed in this paper that provides a methodology to design a TL controller based on the FNN design concept. In order to do so, a new direct formula is first developed to generate the fuzzy rules from the premise part in FNN. This direct formula not only guarantees a one-to-one mapping that maps the fuzzy membership functions onto the fuzzy rules, but also alleviates the coding effort during hardware implementation. It is further elaborated that the FNN with nonoverlapped BPMFs has the advantage of faster online training that requires less computation time, but at the cost of more memory requirement to store the fuzzy rules. The application of this new approach has been applied successfully in the water injection control of a turbo-charged automobile with excellent results.
URI: http://dx.doi.org/10.1109/TSMCC.2008.923869
http://hdl.handle.net/11536/8625
ISSN: 1094-6977
DOI: 10.1109/TSMCC.2008.923869
期刊: IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS
Volume: 38
Issue: 4
起始頁: 574
結束頁: 580
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