Comparative analysis of PID and neural network controllers for improving starting torque of wound rotor induction motor

Received Nov 11, 2019 Revised Jun 21, 2020 Accepted Jul 9, 2020 Keywords: External resistance (R^sub ext^) NARMA-L2 PID controller Starting torque (T^sub s^) Wound rotor induction motor ABSTRACT Unlike 3-phase squirrel cage induction motor, starting-up of 3-phase wound rotor counterpart can be impro...

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Published in:Telkomnika Vol. 18; no. 6; pp. 3142 - 3154
Main Authors: Dakheel, Hashmia Sh, Abdulla, Zainab B., Jawad, Helen Jasim, Mohammed, Ali Jasim
Format: Journal Article
Language:English
Published: Yogyakarta Ahmad Dahlan University 01.12.2020
Subjects:
Artificial neural networks
Circuits
Controllers
Data processing
Evolutionary algorithms
Induction motors
Learning
Learning theory
Load
Neural networks
Nonlinear control
Nonlinear systems
Parameters
Proportional integral derivative
Rotors
Squirrel cage motors
Torque
ISSN:1693-6930, 2302-9293
Online Access:Get full text
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Summary:Received Nov 11, 2019 Revised Jun 21, 2020 Accepted Jul 9, 2020 Keywords: External resistance (R^sub ext^) NARMA-L2 PID controller Starting torque (T^sub s^) Wound rotor induction motor ABSTRACT Unlike 3-phase squirrel cage induction motor, starting-up of 3-phase wound rotor counterpart can be improved by adding an external resistance to the rotor circuit. [...]leads to reduce starting current and increase starting torque. [...]the gain parameters of PID can be obtained by evolutionary algorithms [12]. Because of parameters and non-linear behavior of IM, the process of control convergence has many problems at different conditions of operating, thus chooses artificial intelligent controller (AIC) that represents the best one for IM control, the use of artificial neural networks (ANN) for nonlinear system modeling and control has demonstrated to be extremely successful because of their ability to learn the dynamics of the plant, robustness, inherent approximation capability and a high degree of tolerance [13]. The main advantage of ANN based techniques over conventional techniques is non-algorithmic parallel-distributed architecture for information processing that allows it to learn any complex input-output mapping, ANN is extremely useful in the area of learning control and capability of learning by training data under diverse operations conditions [14], therefore this paper includes study the effect of adding R^sub ext^ to the rotor circuit of WRIM in order to improve T^sub s^ that is represented one of the most characteristics of IM at starting operation condition, as well as comparison between PID controller and ANN (NARMA-L2) at different values of these resistance in order to improve and obtain the maximum and best T^sub s^ to develop performance of WRIM. 2. [...]it is required to a starter in the circuit of motor and reduced the applied voltage to the motor at starting condition [9].
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ISSN:1693-6930
2302-9293
DOI:10.12928/telkomnika.v18i6.14571