Research on Direct Torque Control of Induction Motor Based on Genetic Algorithm and Fuzzy Adaptive PI Controller

2010 ◽  
Author(s):  
Hao Li ◽  
Qiuyun Mo ◽  
Zhilin Zhao
Keyword(s):  
Genetic Algorithm ◽  
Induction Motor ◽  
Direct Torque Control ◽  
Pi Controller ◽  
Torque Control ◽  
Fuzzy Adaptive

Induction Motor Direct Torque Control Based on Multiple Neural Networks Optimized by Genetic Algorithm

2012 ◽  
Vol 482-484 ◽  
pp. 1985-1989
Author(s):  
Gan Zou ◽  
Tao Li ◽  
Ren Xin Xiao
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Simulation Model ◽  
Induction Motor ◽  
Direct Torque Control ◽  
Torque Control ◽  
Speed Sensor ◽  
Multiple Neural Networks ◽  
The Neural Networks ◽  
Simulation Results

Conventional direct torque control(DTC) of induction motor has the problem of large torque ripple.In addition,the speed sensor has its deficiency.A novel DTC system based on multiple neural networks optimized by Genetic Algorithm is proposed and the structures of the proposed system are designed.Genetic algorithm was used to optimize the initial weights and thresholds of the neural networks,All parameters of the neural networks were obtained by offline training.A simulation model of induction motor DTC system was developed in Matlab／Simulink,the simulation results show the feasibility and effectiveness of the scheme

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 Direct Torque Control of Doubly Star Induction Motor Using Fuzzy Logic Speed Controller

2018 ◽  
Vol 7 (1) ◽  
pp. 42
Author(s):  
Lallouani Hellali ◽  
Saad Belhamdi
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Direct Torque Control ◽  
Pi Controller ◽  
General Purpose ◽  
Torque Control ◽  
Speed Controller ◽  
Wide Range ◽  
Time Required

<p>This paper presents the simulation of the control of doubly star induction<br />motor using Direct Torque Control (DTC) based on Proportional and Integral<br />controller (PI) and Fuzzy Logic Controller (FLC). In addition, the work<br />describes a model of doubly star induction motor in α-β reference frame<br />theory and its computer simulation in MATLAB/SIMULINK®.The structure<br />of the DTC has several advantages such as the short sampling time required<br />by the TC schemes makes them suited to a very fast flux and torque<br />controlled drives as well as the simplicity of the control algorithm.the<br />general- purpose induction drives in very wide range using DTC because it is<br />the excellent solution. The performances of the DTC with a PI controller and<br />FLC are tested under differents speeds command values and load torque.</p>

scholarly journals Direct Torque Control System for a Three Phase Induction Motor With Fuzzy Logic Based Speed Controller

2010 ◽  
Vol 6 (2) ◽  
pp. 131-138
Author(s):  
Turki Abdalla ◽  
Haroution Hairik ◽  
Adel Dakhil
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Direct Torque Control ◽  
Speed Control ◽  
Pi Controller ◽  
Torque Control ◽  
Speed Controller ◽  
Three Phase

This paper presents a method for improving the speed profile of a three phase induction motor in direct torque control (DTC) drive system using a proposed fuzzy logic based speed controller. A complete simulation of the conventional DTC and closed-loop for speed control of three phase induction motor was tested using well known Matlab/Simulink software package. The speed control of the induction motor is done by using the conventional proportional integral (PI) controller and the proposed fuzzy logic based controller. The proposed fuzzy logic controller has a nature of (PI) to determine the torque reference for the motor. The dynamic response has been clearly tested for both conventional and the proposed fuzzy logic based speed controllers. The simulation results showed a better dynamic performance of the induction motor when using the proposed fuzzy logic based speed controller compared with the conventional type with a fixed (PI) controller.

scholarly journals High-performance adaptive intelligent Direct Torque Control schemes for induction motor drives

2005 ◽  
Vol 2 (1) ◽  
pp. 93-116 ◽  
Author(s):  
M. Vasudevan ◽  
R. Arumugam ◽  
S. Paramasivam
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Induction Motor ◽  
High Performance ◽  
Fuzzy Controller ◽  
Linear Time ◽  
Direct Torque Control ◽  
Torque Control ◽  
Advantages And Disadvantages ◽  
State Selection

This paper presents a detailed comparison between viable adaptive intelligent torque control strategies of induction motor, emphasizing advantages and disadvantages. The scope of this paper is to choose an adaptive intelligent controller for induction motor drive proposed for high performance applications. Induction motors are characterized by complex, highly non-linear, time varying dynamics, inaccessibility of some states and output for measurements and hence can be considered as a challenging engineering problem. The advent of torque and flux control techniques have partially solved induction motor control problems, because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Intelligent controllers are considered as potential candidates for such an application. In this paper, the performance of the various sensor less intelligent Direct Torque Control (DTC) techniques of Induction motor such as neural network, fuzzy and genetic algorithm based torque controllers are evaluated. Adaptive intelligent techniques are applied to achieve high performance decoupled flux and torque control. This paper contributes: i) Development of Neural network algorithm for state selection in DTC; ii) Development of new algorithm for state selection using Genetic algorithm principle; and iii) Development of Fuzzy based DTC. Simulations have been performed using the trained state selector neural network instead of conventional DTC and Fuzzy controller instead of conventional DTC controller. The results show agreement with those of the conventional DTC.

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