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Journal ArticleDOI

Fuzzy Self-Tuning Speed Control of an Indirect Field-Oriented Control Induction Motor Drive

M. Masiala, +3 more
- Vol. 44, Iss: 6, pp 1732-1740
TLDR
In this article, a self-tuning fuzzy controller is proposed for variable-speed induction machines, which can adjust its parameters online according to the error between actual machine speed and a model reference.
Abstract
The field-oriented control of induction machines is widely used in high-performance applications. However, detuning caused by parameter disturbances still limits the performance of these drives. In order to accomplish variable-speed operation, conventional PID-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field-oriented conditions. An alternate approach is to use the so-called ldquofuzzyrdquo controller. In this paper, a self-tuning fuzzy controller is implemented. The proposed controller has the ability to adjust its parameters online according to the error between actual machine speed and a model reference. The scheme is compared to the conventional proportional-integral control and validated by simulation and experimental tests of both control techniques.

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Citations
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Journal ArticleDOI

Fuzzy Logic and Sliding-Mode Controls Applied to Six-Phase Induction Machine With Open Phases

TL;DR: The application of fuzzy logic and sliding mode controls are presented in order to obtain a high-accuracy positioning of a 6PIM rotor in both healthy and faulted modes.
Journal ArticleDOI

Speed Control of Electrical Drives Using Classical Control Methods

TL;DR: In this article, a classical control approach to the design and analysis of proportional integral (PI) speed controllers for electrical drives is presented, and a well-performing two-degree-of-freedom PI controller with analytical parameter selection is designed, with robustness of the obtained closed-loop system is analyzed and is found to be satisfactory.
Journal ArticleDOI

Hardware/Software Implementation of Fuzzy-Neural-Network Self-Learning Control Methods for Brushless DC Motor Drives

TL;DR: This paper adds a self-learning capability to the initial fuzzy design for operational adaptively and implements the solution on real hardware using a BLDC motor drive system using a dSPACE DSP MATLAB/Simulink environment.
Journal ArticleDOI

On-line Inertia Identification Algorithm for PI Parameters Optimization in Speed Loop

TL;DR: In this article, a novel on-line inertia identification method with a load torque observer is presented to optimize the speed loop PID parameters of a servo system. But, the method of speed loop PI parameters optimization with the identified inertia and load torque is deduced in frequency domain.
Journal ArticleDOI

A Performance Investigation of a Four-Switch Three-Phase Inverter-Fed IM Drives at Low Speeds Using Fuzzy Logic and PI Controllers

TL;DR: In this article, a speed controller using a fuzzy logic controller (FLC) for indirect field-oriented control (IFOC) of induction motor (IM) drives fed by a four-switch three-phase (FSTP) inverter is presented.
References
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Book

Feedback Control of Dynamic Systems

TL;DR: This introductory book provides an in-depth, comprehensive treatment of a collection of classical and state-space approaches to control system design and ties the methods together so that a designer is able to pick the method that best fits the problem at hand.
Book

Modern Power Electronics And Ac Drives

Bimal K. Bose
TL;DR: In this paper, the authors present a simulation of a six-step Thyristor Inverter with three-level Inverters and three-phase Bridge Invergers. And they present a Neural Network in Identification and Control toolbox.
Book

Modern Power Electronics And Ac Drives

Bose
Book

Vector Control and Dynamics of AC Drives

TL;DR: In this article, the authors present a d-q model for solid state power converters and present a complex vector analysis of induction machines and synchronous machines with respect to vector control and field orientation.
Book

Feedback control of dynamic systems

TL;DR: In this paper, the authors provide an in-depth, comprehensive treatment of a collection of classical and state-space approaches to control system design, and tie the methods together so that a designer is able to pick the method that best fits the problem at hand.
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