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- W2045184311 abstract "This paper proposes a self-organizing fuzzy controller with a broad generality for minimum phase and stable systems. The controller learns the rules on-line with a minimum knowledge about the process. The rule base is built and permanenetly actualized from input-output real time data and has a fixed maximum number of rules (FMNR). An (on-line) adaptive similarity factor implements a special efficient inference technique. Feedforward and predictive effect is introduced in fuzzification and defuzzification stages. The defuzzification is carried out in such a way that as the learning process progresses the interval of the control becomes more and more accurate. Results are shown concerning simulations for non-linear SISO, MISO and MIMO systems a nd a r eal e xperimental application using a low-cost microcomputer." @default.
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- W2045184311 title "A self-organizing fuzzy controller with a fixed maximum number of rules and an adaptive similarity factor" @default.
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- W2045184311 doi "https://doi.org/10.1016/s0165-0114(97)00192-9" @default.
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