Title :
Study on optimal driving condition of SRM using GA-neural network
Author :
Oh, Seok-Gyu ; Ahn, Jin-Woo ; Lee, Young-Jin ; Lee, Man-Hyung
Author_Institution :
Dept. of IA, Chinju Nat. Univ., South Korea
Abstract :
The torque of SRM depends on phase current and the derivative of inductance. But the inductance of SRM is nonlinearly changed according to rotor position angle and phase current because of saturation in magnetic circuit. Therefore this has a concern in torque ripple and speed variation, and it is difficult to control the desired torque. This paper proposes an optimization control scheme by adjusting both the turn-on and turn-off angle according to high efficiency points which are simulated by GA-neural network, which is used to simulate the reasonable switching angle which is nonlinearly varied with rotor speed and load
Keywords :
angular velocity control; genetic algorithms; inductance; machine control; magnetic circuits; neural nets; reluctance motor drives; rotors; torque control; GA-neural network; SRM; high efficiency points; load; magnetic circuit saturation; optimal driving condition; optimization control; phase current; reasonable switching angle simulation; rotor position angle; rotor speed; speed control; speed variation; switched reluctance motor drive; torque; torque ripple; turn-off angle; turn-on angle; Circuit simulation; Inductance; Magnetic circuits; Reluctance machines; Reluctance motors; Rotors; Shape; Switches; Torque control; Voltage control;
Conference_Titel :
Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on
Conference_Location :
Pusan
Print_ISBN :
0-7803-7090-2
DOI :
10.1109/ISIE.2001.931684