<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Hybrid-fuzzy controller optimization via semi-parallel GA for servomotor control"^^ . "Servomotor uses feedback controller to control either the speed or the position or both. This paper discusses the performance comparisons of a modified genetic algorithm, named as the semi-parallel operation genetic algorithm (SPOGA) and the conventional genetic algorithm (GA), in optimizing the I/O scale factors, membership functions, and rules of a hybrid-fuzzy controller. Singleton fuzzification is used as a fuzzifier with seven membership functions for both input and output of the controller, whilst center of average is used as a defuzzifier. A 21-bit-30-population is used in SPOGA for both I/O scales and for membership functions. Two control modes are applied in cascaded: position and speed. Both the simulation and practical experiment results show that fuzzy-logic parallel integral controller (FLIC) with SPOGA-optimized is better as compared to FLIC with GA-optimized and also the non-optimized FLIC, FLC, and PI in terms of performance and the reduction of the number of test runs for the optimization. © 2011 IEEE."^^ . "2011" . . . "Proceedings of the International Conference on Power Electronics and Drive Systems"^^ . . . . . . . . . . . . . . "O."^^ . "Wahyunggoro"^^ . "O. Wahyunggoro"^^ . . "T."^^ . "Ibrahim"^^ . "T. Ibrahim"^^ . . "N."^^ . "Saad"^^ . "N. Saad"^^ . . . . . "HTML Summary of #1555 \n\nHybrid-fuzzy controller optimization via semi-parallel GA for servomotor control\n\n" . "text/html" . .