scholarly journals Latest Advances in DTC Control of Induction Motors

2020 ◽  
Vol 8 (6S) ◽  
pp. 120-123
Keyword(s):  
Induction Motor ◽  
Predictive Control ◽  
Induction Motors ◽  
Adaptive System ◽  
Sliding Mode ◽  
Direct Torque Control ◽  
Torque Ripple ◽  
Torque Control ◽  
Model Reference Adaptive System ◽  
Model Reference Adaptive

In these days, developments in the area of Induction Motor control is increasing significantly. Considerable advancements have been taken place in the area of Direct Torque Control (DTC), which is capable of providing quick dynamic response with respect to torque and flux. This paper presents a detailed survey on various latest techniques of DTC control of Induction Motor such as DTC-SVM with hysteresis band, DTCSVM with Model Predictive Control, DTC with sliding mode control, DTC with Model reference adaptive system (MRAS) et cetera. The simulation results are discussed for DTC-SVPWM topology and results obtained proves that this method has reduced torque ripple

Sensorless direct torque control based on nonlinear integral sliding mode controllers for an induction motor drive: Experimental verification

2020 ◽  
pp. 095965182093373
Author(s):  
Saber Krim ◽  
Youssef Krim ◽  
Mohamed Faouzi Mimouni
Keyword(s):  
Adaptive System ◽  
Sliding Mode ◽  
Direct Torque Control ◽  
Torque Control ◽  
Adaptation Mechanism ◽  
Model Reference ◽  
Speed Controller ◽  
Model Reference Adaptive System ◽  
Speed Estimator ◽  
Model Reference Adaptive

In this article, a novel sliding mode adaptation mechanism of a model reference adaptive system speed estimator and a modified sliding mode speed controller are proposed to replace the proportional-integral controller used in the adaptation mechanism of the model reference adaptive system and the proportional-integral speed controller, respectively. The suggested control strategy is designed by sensorless direct torque control with space vector modulation based on a sliding mode speed controller and a model reference adaptive system sliding mode speed estimator. The contribution of this work is the development of one control law based on a modified nonlinear component to overcome the first-order sliding mode control limitations, such as the chattering phenomenon. The performance of the suggested controller-based direct torque control with space vector modulation is verified by digital simulation with different operation conditions, like the abrupt variations in the load torque and the reference speed, using the MATLAB/SIMULINK environment. In fact, such simulation results are experimentally checked utilizing a dSPACE-1104.

Second-order sliding mode-direct torque control and load torque estimation for sensorless model reference adaptive system–based induction machine

2020 ◽  
Vol 235 (1) ◽  
pp. 15-29 ◽  
Author(s):  
Abdelkarim Ammar
Keyword(s):  
Adaptive System ◽  
Sliding Mode ◽  
Direct Torque Control ◽  
Second Order ◽  
Torque Control ◽  
Load Torque ◽  
Model Reference ◽  
Model Reference Adaptive System ◽  
Model Reference Adaptive ◽  
Second Order Sliding Mode

In this article, an improved sensorless direct flux and torque control is presented for high-performance induction motor drive. This algorithm integrates the super twisting control approach with direct torque control and model reference adaptive system. The super twisting algorithm is a second-order sliding mode approach that uses a continuous control law in order solves the problems of chattering and enhances control robustness against various uncertainties. Besides, a load torque observer design bed on super twisting–based design is presented to improve the speed regulation loop and to increase its rejection ability of load disturbances. Furthermore, the stator flux model reference adaptive system is used as a sensorless algorithm for rotor speed reconstruction. The association of dual estimators can increase the control system’s reliability and reduce its cost. The effectiveness of the proposed control algorithm has been verified through simulation and experimental work using MATLAB/Simulink software and dSpace 1104 implementation board, respectively.

scholarly journals Comparative Analysis of Control Methods with Model Reference Adaptive System Estimators of a Seven-Phase Induction Motor with Encoder Failure

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1147 ◽  
Author(s):  
Jacek Listwan ◽  
Krzysztof Pieńkowski
Keyword(s):  
Induction Motor ◽  
Adaptive System ◽  
Direct Torque Control ◽  
Torque Control ◽  
Space Vector Modulation ◽  
Space Vector ◽  
Model Reference ◽  
Model Reference Adaptive System ◽  
Vector Modulation ◽  
Model Reference Adaptive

This article presents a comparative analysis of the direct torque control with space vector modulation method for seven-phase squirrel-cage induction motor during the encoder failure. The direct torque control with space vector modulation method with model reference adaptive system with current model and current estimator and model reference adaptive system—flux based estimator applied in the control loop of the motor speed have been analyzed. The mathematical model of the seven-phase induction motor and model reference adaptive system-type estimators have been described. The method of space vector modulation applied to the seven-phase voltage source inverter, controlled seven-phase induction motor, has been described. The operation of direct torque control with space vector modulation has been verified via simulation tests, and the results of performed simulation studies have been analyzed and presented. The authors’ original contribution and work novelty includes comparison studies of the performance of the direct torque control method with space vector modulation of a seven-phase induction motor with two estimators: model reference adaptive system—flux based estimator and the novel model reference adaptive system with current model and current estimator.

scholarly journals Performance Analysis of DTC-SVM Sliding Mode Controllers-Based Parameters Estimator of Electric Motor Speed Drive

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Fatma Ben Salem ◽  
Nabil Derbel
Keyword(s):  
Induction Motor ◽  
Controller Design ◽  
Sliding Mode ◽  
Direct Torque Control ◽  
Torque Ripple ◽  
Mutual Inductance ◽  
Torque Control ◽  
Motor Speed ◽  
Rotor Resistance ◽  
Stator Resistance

This paper is concerned with a framework which unifies direct torque control space vector modulation (DTC-SVM) and variable structure control (VSC). The result is a hybrid VSC-DTC-SVM controller design which eliminates several major limitations of the two individual controls and retains merits of both controllers. It has been shown that obtained control laws are very sensitive to variations of the stator resistance, the rotor resistance, and the mutual inductance. This paper discusses the performances of adaptive controllers of VSC-DTC-SVM monitored induction motor drive in a wide speed range and even in the presence of parameters uncertainties and mismatching disturbances. Better estimations of the stator resistance, the rotor resistance, and the mutual inductance yield improvements of induction motor performances using VSC-DTC-SVM, thereby facilitating torque ripple minimization. Simulation results verified the performances of the proposed approach.

Weighted Tuning PI Controller for MRAS Sensorless Induction Motor Drive

2012 ◽  
Vol 220-223 ◽  
pp. 1066-1070
Author(s):  
Hsiu Ping Wang ◽  
Yu Feng Chang
Keyword(s):  
Induction Motor ◽  
Direct Torque Control ◽  
Pi Controller ◽  
Torque Control ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Speed Controller ◽  
Model Reference Adaptive System ◽  
Structure Scheme ◽  
Model Reference Adaptive

The paper presents a weighted tuning PI controller for speed estimating of induction motor using model reference adaptive system (MRAS) approach in a direct torque control system. The performance of speed controller affects the performance of sensorless each other. The objective of presented weighted tuning PI controller is to improve the performance of induction motor drive and enhance the performance of speed estimation. The presented controller is based on Ziegler-Nichols (Z-N) tuning formula with weighted tuning. The method improves the problem of parameter choice, reduces the over shoot and is simple as Z-N without system model. The availability of the proposed structure scheme is verified by through simulation results.

scholarly journals Neural Network-Based Model Reference Adaptive System for Torque Ripple Reduction in Sensorless Poly Phase Induction Motor Drive

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 920 ◽  
Author(s):  
S. Usha ◽  
C. Subramani ◽  
Sanjeevikumar Padmanaban
Keyword(s):  
Neural Network ◽  
Induction Motor ◽  
Adaptive System ◽  
Direct Synthesis ◽  
Synthesis Method ◽  
Time Domain Analysis ◽  
Torque Ripple ◽  
Model Reference ◽  
Model Reference Adaptive System ◽  
Model Reference Adaptive

This paper proposes the modified, extended Kalman filter, neural network-based model reference adaptive system and the modified observer technique to estimate the speed of a five-phase induction motor for sensorless drive. The proposed method is generated to achieve reduced speed deviation and reduced torque ripple efficiently. In inclusion, the result of speed performance and torque ripple under parameter variations were analysed and compared with the conventional direct synthesis method. The speed estimation of a five-phase motor in the four methods is analysed using MATLAB Simulink platform, and the optimum method is recognized using time domain analysis. It is observed that speed error is minimized by 60% and torque ripple is reduced by 75% in the proposed method. The hardware setup is carried out for the optimized method identified.

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