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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Mini R
Amrita University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Low Speed Estimation of Sensorless DTC Induction Motor Drive Using MRAS with Neuro Fuzzy Adaptive Controller Mini R; Shabana Backer P.; B. Hariram Satheesh; Dinesh M. N
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (963.94 KB) | DOI: 10.11591/ijece.v8i5.pp2691-2702

Abstract

This paper presents a closed loop Model Reference Adaptive system (MRAS) observer with artificial intelligent Nuero fuzzy controller (NFC) as the adaptation technique to mitigate the low speed estimation issues and to improvise the performance of the Sensorless Direct Torque Controlled (DTC) Induction Motor Drives (IMD). Rotor flux MRAS and reactive power MRAS with NFC is explored and detailed analysis is carried out for low speed estimation. Comparative analysis between rotor flux MRAS and reactive power MRAS with PI as well as NFC as adaptive controller is performed and results are presented in this paper. The comparative analysis among these four speed estimation methods shows that reactive power MRAS with NFC as adaptation mechanism shows reduced speed estimation error and actual speed error at steady state operating conditions when the drive is subjected to low speed operation. Simulation carried out using MATLAB-Simulink software to validate the performance of the drive especially at low speeds with rated and variable load conditions.
Real Time Validation of EKF Estimator for Low Speed Estimation in DTC IMD Mini R; Binoj P.V.; B. Hariram Satheesh; Dinesh M.N.
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (981.008 KB) | DOI: 10.11591/ijpeds.v9.i1.pp433-442

Abstract

Low speed estimation in DTC IMD is not accurate due to the presence of transient offset, drift and domination of ohmic voltage drop in the measured stator voltages and currents used for estimating the stator flux required for accurate estimation of speed. EKF is a nonlinear, recursive adaptive algorithm capable of estimating speed ranging from very low speed to rated speed using equation of motion from noisy measured currents and voltages based on state space technique. In the previous work a new state space model of IM was developed for estimation in EKF by feeding load torque profile as an input variable instead of estimating it by considering load torque as constant, validated using MATLAB-Simulink software. In this paper real time validation of the EKF controller with load profile fed as input for speed estimation in DTC IMD is carried out using OPAL-RT simulator and real time results validates the simulation results and proves the effectives of the new EKF for low speed estimation in DTC IMD
Co-Authors B. Hariram Satheesh B. Hariram Satheesh Binoj P.V. Dinesh M. N Dinesh M.N. Shabana Backer P.