Open AccessTorque and Flux Ripple Minimization of Induction Motor Using Hybrid Neuro Fuzzy Controller
Author(s) -
V. Sakthi,
A. Sivasubramanian
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.6.28445
Subject(s) - control theory (sociology) , direct torque control , stall torque , torque , vector control , torque ripple , stator , damping torque , induction motor , controller (irrigation) , torque motor , computer science , engineering , voltage , physics , control (management) , agronomy , artificial intelligence , biology , electrical engineering , thermodynamics , mechanical engineering
This paper proposed to design, implementation and simulation of Direct Torque Control of Induction Motor drive system is to minimize stator current distortion, electromagnetic torque and flux ripples. In this paper, Hybrid Neuro-Fuzzy Controller is proposed to replace the conventional PI torque and flux controller to achieve desired torque and flux with zero steady state error and also with good dynamic fast response. Neuro-Fuzzy based torque and flux controllers are designed to optimize the stator voltages in d-q reference frame that applied to Direct Torque Control. Simulation and the performance of the proposed Hybrid NFC are analyzed. Simulation results showed that a significant improvement in dynamic torque and speed response in both steady and transient states and also a considerable reduction in torque and flux minimization compared to the other AI techniques.