TY  - CONF
Y1  - 2017///
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9781509008452
A1  - Magzoub, M.
A1  - Saad, N.
A1  - Ibrahim, R.
A1  - Irfan, M.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012031707&doi=10.1109%2fICIAS.2016.7824078&partnerID=40&md5=354019fed5e8e007a8e674d23d67c4ef
AV  - none
N1  - cited By 4; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970
N2  - This paper discusses speed control performance of a proposed hybrid fuzzy-fuzzy controller (HFFC) in a variable speed induction motor (IM) drive system. With respect to finding the rule base of the fuzzy controller, a simple genetic algorithm (GA) is employed to resolve the problem of optimization to diminish an objective function, i.e., the Integrated Absolute Error (IAE) criterion. The principle of HFFC is established with the aim of overcoming the shortcoming of the field oriented control (FOC) technique. Simulation results show that HFFC with GA-optimized is the better strategy as compared to HFFC without GA, and conventional hybrid fuzzy-PI controller (HFPIC) for the speed control of IM. © 2016 IEEE.
TI  - A genetic algorithm optimization of hybrid fuzzy-fuzzy rules in induction motor control
ID  - scholars8917
KW  - Fuzzy inference; Fuzzy logic; Genetic algorithms; Induction motors; Optimization; Speed control; Variable speed drives; Vector control (Electric machinery); Water craft
KW  -  Control performance; Fuzzy logic control; Genetic-algorithm optimizations; Hybrid fuzzy-pi controllers; Induction motor control; Integral absolute errors; Integrated absolute errors; Simple genetic algorithm
KW  -  Controllers
ER  -