Abstract—This paper presents a novel space vector pulse-width modulated vector controlled induction motor drive with adaptive neuro-fuzzy based speed controller. SVPWM is superior to other PWM schemes from the view point of dc-link voltage utilization and current harmonics. The proposed neuro-fuzzy controller incorporates fuzzy logic algorithm with a five-layer artificial neural network (ANN) structure. The conventional PI controller is replaced by Adaptive Neuro-Fuzzy Inference System (ANFIS), which tunes the fuzzy inference system with hybrid learning algorithm. This makes fuzzy system to learn. The performance of the proposed neuro-fuzzy based SVPWM-VCIM drive is investigated at different operating conditions. The results of the proposed controller are also compared to those obtained by a conventional PI controller. The simulation study indicates robustness and suitability of drive for high performance drive applications.

Index Terms—Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), Space Vector Pulse-Width Modulation (SVPWM), hybrid learning algorithm, Vector Controlled Induction Motor (VCIM).

Rajesh Kumar is Reader with the Department of Electrical Engineering, Malaviya National Institute of Technology (MNIT), Jaipur, India. Email: rkumar.ee@gmail.com.
R. A. Gupta is Professor with the Department of Electrical Engineering, Malaviya National Institute of Technology (MNIT), Jaipur, India. Email: rag_mnit@rediffmail.com.
Rajesh S. Surjuse is Research Scholar with the Department of Electrical Engineering, Malaviya National Institute of Technology (MNIT), Jaipur, India. Phone: 91-09887807122, Email: surjusemnit@rediffmail.com.

Cite: Rajesh Kumar, R. A. Gupta and Rajesh S. Surjuse, "High-Performance SVPWM-VCIM Drive with Adaptive Neuro-Fuzzy Speed Controller," International Journal of Computer and Electrical Engineering vol. 2, no. 1, pp. 162-169, 2010.