DocumentCode :
3480702
Title :
Fuzzy logic based improvements in efficiency optimization of induction motor drives
Author :
Moreno, Juan ; Cipolla, Miguel ; Peracaula, Juan ; Branco, Paulo J da Costa
Author_Institution :
Power Electron. Div., Poly. Univ. of Catalonia, Barcelona, Spain
Volume :
1
fYear :
1997
fDate :
1-5 Jul 1997
Firstpage :
219
Abstract :
Induction motors are, without any doubt, the most used in industry. Motor drive efficiency optimization is important for two reasons: economic saving, and reduction of environmental pollution. In this paper, advantages of using fuzzy logic in steady-state efficiency optimization for induction motor drives are described. Experimental results of a fuzzy logic based optimum flux search controller are presented. For transient states a new original idea is introduced: a fuzzy logic based controller actuating as a supervisor is proposed to work with reduced flux levels during transients to optimize efficiency also in dynamic mode. Two different rule tables are designed, for torque transitions and for reference speed changes. With this controller efficiency can be improved in transients, and also search controller convergence speed is increased. Experimental results with a 1.5 kW induction motor drive demonstrate the validity of the proposed methods
Keywords :
fuzzy control; fuzzy logic; induction motor drives; machine control; power consumption; convergence speed; dynamic mode; economic saving; environmental pollution; fuzzy logic; fuzzy logic based optimum flux search controller; induction motor drives; reference speed changes; steady-state efficiency optimization; supervisor; torque transitions; Convergence; Environmental economics; Environmentally friendly manufacturing techniques; Fuzzy logic; Induction motor drives; Induction motors; Industrial pollution; Motor drives; Steady-state; Torque;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7803-3796-4
Type :
conf
DOI :
10.1109/FUZZY.1997.616371
Filename :
616371
Link To Document :
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