Multiobjective optimization method based on a genetic algorithm for switched reluctance motor design

2002 ◽  
Vol 38 (3) ◽  
pp. 1524-1527 ◽  
Author(s):  
B. Mirzaeian ◽  
M. Moallem ◽  
V. Tahani ◽  
C. Lucas
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Switched Reluctance Motor ◽  
Optimization Method ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Motor Design

Mitigation of the Torque Ripple of a Switched Reluctance Motor Through a Multiobjective Optimization

2008 ◽  
Vol 44 (6) ◽  
pp. 1018-1021 ◽  
Author(s):  
S.I. Nabeta ◽  
I.E. Chabu ◽  
L. Lebensztajn ◽  
D.A.P. Correa ◽  
W.M. da Silva ◽  
...  
Keyword(s):  
Multiobjective Optimization ◽  
Switched Reluctance Motor ◽  
Torque Ripple ◽  
Switched Reluctance ◽  
Reluctance Motor

Switched Reluctance Motor Design for an EV Propulsion Application

2021 ◽  
Author(s):  
Omar Zayed ◽  
Mohamed Omar ◽  
Mohamed Bakr ◽  
Mehdi Narimani ◽  
Ali Emadi ◽  
...  
Keyword(s):  
Switched Reluctance Motor ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Motor Design

scholarly journals Speed control of switched reluctance motor using genetic algorithm and ant colony based on optimizing PID controller

2018 ◽  
Vol 16 ◽  
pp. 01001 ◽  
Author(s):  
Hassan El-Sayed Ahmed Ibrahim ◽  
Mohamed Said Sayed Ahmed ◽  
Khaled Mohamed Awad
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Switched Reluctance Motor ◽  
Operating Conditions ◽  
Ant Colony ◽  
Proportional Integral Derivative ◽  
Switched Reluctance ◽  
Proportional Integral ◽  
Highly Nonlinear ◽  
Reluctance Motor

Proportional-Integral-Derivative control is the most used kind of control which provides the simplest and most effective solution to different kinds of control engineering applications. But until now PID controller is poorly tuned in real life and online applications. While most of PID tuning is done manually. Switched reluctance motor (SRM) has highly nonlinear characteristics since the developed/produced torque of the motor has a nonlinear function on both phase current and rotor position. These nonlinearities of the SRM drives make the conventional PID (proportional + integral + Derivative) controller a poor choice for application where high dynamic performance is desired under all motor operating conditions. research paper comes up with two artificial and hybrid techniques involving Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Those techniques where used to tune the PID parameters for the switched reluctance motor (SRM) and its performance were compared with the conventional method of “Ziegler Nichols. The results obtained reflects that, the use of those algorithms based controller improves the performance of the whole process in terms of a fast set point tracking and regulatory changes and also provides an optimum stability for the system itself with a minimum overshoot on the output signal.

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