Abstract

A distributed, scalable and flexible fuzzy logic controller (FLC) without increasing additional hardware cost by fuzzy accuracy factor is proposed. In order to improve fuzzy logic operation speed, multi-input/multi-output (MIMO) fuzzy system is decomposed into several independent two-input/single-output (TISO) subsystems in parallel. The decomposed TISO FLC can deal with scalable requirements in terms of number of input language variables, output language variables, data accuracy types and fuzzy rules. In this paper, the systematic design methods are presented in detail, and the scalable TISO FLC architectures are addressed with fuzzification of fuzzy accuracy factor and analog-to-digital conversion (ADC) quantizer, fuzzy rules and fuzzy inference engine, and the defuzzification by a scalable divider. At last, A JTAG-TCL tool is developed to compare the scalable TISO FLC with other FLCs in resource, accuracy, and speed. The experiment results of photovoltaic (PV) system indicate that the proposed FLC has flexible control accuracy, fast response and better tracking performance.

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