Three-level Inverter-fed Induction Motor Drive Performance Improvement with Neuro-fuzzy Space Vector Modulation

Abstract

—The space vector modulation technique is an optimal pulse-width modulation technique used for inverter control. This article presents a neuro-fuzzy-based space vector modulation technique for a three-level inverter fed induction motor. It uses a hybrid learning algorithm (combination of back-propagation and least-squares methods) for training the input–output data pattern. The training data for neuro-fuzzy-based space vector modulation are generated from the conventional simplified space vector modulation method. The proposed scheme uses the space vector rotation angle and change of rotation angle information as input and generated duty ratios as output. The dynamic and steady-state performance of a neuro-fuzzy-controlled induction motor drive is compared with the conventional space vector modulation and neural network-based space vector modulation methods. The simulation results obtained are verified experimentally using a dSPACE kit (DS1104). The performance measure in terms of the total harmonic distortion of inverter line–line voltage of the neuro-fuzzy-based system is compared with the neural network-based space vector modulation and conventional space vector modulation methods.

Keywords:

• neuro-fuzzy inference system
• space vector modulation
• three-level inverter
• two-level inverter
• induction motor
• voltage source inverter
• neural network
• total harmonic distortion

Additional information

Notes on contributors

Durga Sukumar

Durga Sukumar received Bachelor's and Master's degrees in Electrical Engineering from J.N.T.U, Hyderabad (India) and Ph.D in Electrical Engineering from Indian Institute of Technology, Roorkee, India. Presently he is working as Associate Professor in School of Electrical Engineering, Vignan University, Guntur, A.P, India. His research interests include power electronics, AC drives and soft computing techniques.

Jayachandranath Jithendranath

Jayachandranath Jithendranath completed his B.Tech in Electrical Engineering from JNTU, Hyderabad and M.Tech with specialization in Power Engineering from JNTU, Ananthapur in 2005 and 2010 respectively. He is currently working as Assistant Professor in School of Electrical Engineering, Vignan University, Guntur, A.P, India. His research interests are in Artificial Intelligence applications in Electrical Engineering problems, with emphasis on Power Electronic AC and DC Drives.

Suman Saranu

Suman Saranu obtained B.Tech from JNTU, Hyderabad and M.S. from University of Edinburgh, U.K. She is presently working as Assistant Professor in School of Electrical Engineering, Vignan's University, Guntur, A.P, India. Her areas of interest are artificial intelligence application in areas of renewable sources of energy, power electronics and drives.