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https://hdl.handle.net/10316/4116
Title: | A self-organizing fuzzy controller with a fixed maximum number of rules and an adaptive similarity factor | Authors: | Dias, Joana Matos Dourado, António |
Keywords: | Empirical research; Control theory; Process control; Self-organizing fuzzy control; On-line learning; Applications | Issue Date: | 1999 | Citation: | Fuzzy Sets and Systems. 103:1 (1999) 27-48 | 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. | URI: | https://hdl.handle.net/10316/4116 | Rights: | openAccess |
Appears in Collections: | FCTUC Eng.Informática - Artigos em Revistas Internacionais |
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filee5036559fba6462ca11061a93016b9a1.pdf | 1.31 MB | Adobe PDF | View/Open |
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