Genetic Algorithm Based On-line Tuning of a PI Controller for a Switched Reluctance Motor Drive

Abstract

A switched reluctance motor (SRM) is suitable for many variable-speed and servo-type applications, and is getting increasing attention in the motor drive industry. However, the SRM has highly nonlinear characteristics since the developed torque of the SRM is a nonlinear function of both phase current and rotor position, and the SRM always operates with magnetic saturation to maximize torque/mass ratio. These nonlinearities of the SRM drives make the conventional PI (proportional + integral) controller a poor choice for application where high dynamic performance is desired under all motor operating conditions. The genetic algorithm (GA) can give robust adaptive response of a drive with nonlinearity, parameter variation and load disturbance effect. In this article, the genetic PI speed controller was applied to the speed loop of the SRM by replacing the conventional PI speed controller. The genetic PI controller software was implemented using C+ + Builder on a PC. Both the conventional and the genetic PI controller for the SRM are implemented by using a TMS320F240 digital signal processor. The results show that the genetic PI controller is less sensitive to the parameter variations and disturbances.