Model reference neural adaptive control based BLDC motor speed control

Abstract

Brushless DC (BLDC) motor control system is consisted of a multi-variable, non-linear, strong-coupling system, which is used to present robust and adaptive abilities. The interest in emerging intelligent controller for BLDC motor has been increased significantly. Neural Control is an ANN (Artificial Neural Network) based control method whereby the available data is the result of measuring the dynamic behavior of the system. This capability is well suited to be applied to adaptive control systems where the controller requires adaptation due to changes in system behavior. ANN was used to build the inverse model of BLDC motor speed. This model was then used as controller. In order to obtain control schemes that have good dynamic responses, MRAC concept was applied.