Izvorni znanstveni članak
https://doi.org/10.7305/automatika.2017.02.1330
Efficient speed control of induction motor using RBF based model reference adaptive control method
Erdal Kilic
; Engineering and Architecture Faculty, Electrical and Electronics Engineering Department, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
Hasan Riza Ozcalik
; Engineering and Architecture Faculty, Electrical and Electronics Engineering Department, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
Saban Yilmaz
; Engineering and Architecture Faculty, Electrical and Electronics Engineering Department, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
Sažetak
This paper proposes a model reference adaptive speed controller based on artificial neural network for induction motor drives. The performance of traditional feedback controllers has been insufficient in speed control of induction motors due to nonlinear structure of the system, changing environmental conditions, and disturbance input effects. A successful speed control of induction motor requires a nonlinear control system. On the other hand, in recent years, it has been demonstrated that artificial intelligence based control methods were much more successful in the nonlinear system control applications. In this work, it has been developed an intelligent controller for induction motor speed control with combination of radial basis function type neural network (RBF) and model reference adaptive control (MRAC) strategy. RBF is utilized to adaptively compensate the unknown nonlinearity in the control system. The indirect field-oriented control (IFOC) technique and space vector pulse width modulation (SVPWM) methods which are widespread used in high performance induction motor drives has been preferred for drive method. In order to demonstrate the reliability of the control technique, the proposed adaptive controller has been tested under different operating conditions and compared performance of conventional PI controller. The results show that the proposed controller has got a clear superiority to the conventional linear controllers.
Ključne riječi
Induction motor; neural network; model reference adaptive control; vector control
Hrčak ID:
180702
URI
Datum izdavanja:
23.3.2017.
Posjeta: 1.377 *