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Author

K. S. Rangasamy

Bio: K. S. Rangasamy is an academic researcher. The author has contributed to research in topics: Thyristor drive & Vector control. The author has an hindex of 1, co-authored 2 publications receiving 7 citations.

Papers
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01 Jan 2013
TL;DR: In this paper, a brushless DC motor drive system with input shaping using classical control theory is analyzed using time response analysis and the relative stability of this drive system is determined by Bode Plot.
Abstract: The main objective of this work is to analyze the brushless DC (BLDC) motor drive system with input shaping using classical control theory. In this paper, different values of damping ratio are used to understand the generalized drive performance. The transient response of the BLDC motor drive system is analyzed using time response analysis. The dynamic behaviour and steady state performance of the BLDC motor drive system is judged and compared by its steady state error to various standard test signals. The relative stability of this drive system is determined by Bode Plot. These analysis spotlights that it is possible to obtain a finite-time setting response without oscillation in BLDC motor drive by applying input in four steps of different amplitude to the drive system. These analyses are helpful to design a precise speed control system and current control system for BLDC motor drive with fast response. The Matlab/Simulink software is used to perform the simulation. V : q-axis equivalent stator voltage in volts r qs i : q-axis equivalent stator current in amps s L : Equivalent stator self-inductance in henry s R : Equivalent stator winding resistance in ohms P : Number of poles of motor L T : Load torque of motor in N-m m B : Motor viscous friction coefficient in N-m/rad/sec m J : Rotor inertia of motor in Kg-m 2

6 citations

01 Jan 2015
TL;DR: In this paper, a new technique is implemented with direct back emf detection for sensorless BLDC motor drives, where there is no need of motor neutral voltage and attenuation filtering.
Abstract: In recent years BLDC Motor and their drives are becoming a major market trend in home appliances, automotive applications and in HVAC industry for their better reliability, silent operation and high efficiency with low maintenance. For a traditional BLDC Motor, a six step commutated pattern with position sensors are provided which increases the cost of the BLDC Motor. Hence the preference is switch over to the sensorless drive to reduce the cost and complexity. The existing conventional sensorless scheme which has its own limit for the applications which is the major drawback of back emf sensing based on motor neutral voltage. In this paper a new technique is implemented with direct back emf detection for sensorless BLDC Motor drives. To measure the back emf, there is no need of motor neutral voltage. During the Off time of the PWM, the terminal voltage of the motor is directly proportional to the phase back emf. For the back emf sensing, there is no need of attenuation filtering. At low cost, the wider motor speed range had achieved with superior performance which shows with the help of MATLAB/ SIMULINK Software.

1 citations


Cited by
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Book ChapterDOI
13 Aug 2010
TL;DR: All rights reserved.
Abstract: All rights reserved. No part of the publication may be reproduced in any form by print, photoprint, microfilm or any other means without written permission from the publisher.

430 citations

Journal ArticleDOI
01 Jul 2020
TL;DR: Stability analysis and performance characteristics of brushless direct current motor are studied and implemented with a new deep learning neural network—fuzzy-tuned proportional integral derivative (PID) speed controller, showing that the design methodologies outperform other controller designs from the literature.
Abstract: Speed regulation is one of the significant characteristics to be adopted in the field of brushless DC motor drive for effective and accurate speed and position control operations. In this paper, stability analysis and performance characteristics of brushless direct current motor are studied and implemented with a new deep learning neural network—fuzzy-tuned proportional integral derivative (PID) speed controller. Deep learning architecture is designed for the multi-layer perceptron network, and the output from the neural module fires the rules of the fuzzy inference system mechanism. The parameters of deep perceptron neural network (DPNN) are tuned for near optimal solutions using the unified multi-swarm particle swarm optimization, and in turn the optimized DPNN selects the parameters of the fuzzy inference system. Deep learning neural network with the fuzzy inference system tunes the gain values of the PID controller and performs an effective speed regulation. The performance characteristics of the designed speed controller are tested for a step change in input speed and also for impulsive load disturbances. Further, the stability analysis of the new proposed controller is investigated with Lyapunov stability criterion by deriving the positive definite functions. The weight parameters of DPNN model and the number of rules of fuzzy system are tuned for their near optimal solutions using multi-swarm particle swarm optimization. From the results, it is well proven that the proposed controller is more stable and guarantees consistent performance than other considered controllers in all aspects. Simulation-based comparisons illustrate that the design methodologies outperform other controller designs from the literature.

39 citations

Journal ArticleDOI
TL;DR: In this paper, a bridgeless single-ended primary-inductance converter (BLSEPIC) based power factor rectification with output voltage regulation and high frequency isolation working in discontinuous conduction mode is presented.
Abstract: This paper presents the analysis and design of on front end bridgeless single-ended primary-inductance converter (BLSEPIC) based power factor rectification, with output voltage regulation and high frequency isolation working in discontinuous conduction mode. The switching loss in VSI is minimized by an electronic commutation of Brushless DC motor (BLDCM) is used to operate in a low-frequency operation. To improve the efficiency, the diode bridge rectifier is replaced with the alternate bridgeless topologies which offers less conduction losses, advised by the international power quality standards, a wide range of speed control is obtained with improved power quality BLDC motor drive is proposed and simulated in MATLAB/SIMULINK. DOI: http://dx.doi.org/10.11591/telkomnika.v14i2.7404

4 citations

Journal ArticleDOI
TL;DR: In this paper, an improved back emf detection method is proposed, in which the motor neutral voltage is elemenated and the phase zero crossing point can be directly extracted by detecting voltage difference between the phase terminal and the midpoint of the dc link.
Abstract: In this paper an improved back emf detection method is proposed. The motor neutral voltage is elemenated and the phase back emf zero crossing point can be directly extracted by detecting voltage difference between the phase terminal and the midpoint of the dc link. Here filtering circuit is not needed and the BLDC motor is provided with PWM control of 100% duty ratio which is presented in this paper. To perform the inverter commutation, there is a need of six commutation signals which is obtained by sensing only one of the three phase terminals that reduces the cost of the sensing circuit. The reduction of the imbalance in the six commutation signals which are caused by the asymmetrical behavior of the three phase windings in BLDC motor had been reduced in a varied speed range. It simplifies the starting procedure and achieve the motor performance over a wide speed range. This proposed method is analyzed through the simulation results using MATLAB Simulink. DOI: http://dx.doi.org/10.11591/telkomnika.v14i2.7423

4 citations

Journal Article
TL;DR: In this article, a sensorless startup of a brushless motor using third harmonic back EMF and motor startup using microcontroller for pulse width modulation, power switch control and motor output analysis is presented which renders RPM control and high speed achievement for motor.
Abstract: In this paper the method of sensorless startup of direct current brushless motor using third harmonic back Electromotive Force (EMF) and motor startup using microcontroller for pulse width modulation, power switch control and motor output analysis is presented which renders RPM control and high speed achievement for motor. The microcontroller is used for processor and MOSFETs are used for power circuit. Besides, the motor does not have any sensors to detect rotor position. Furthermore, the microcontroller modulates pulse width, controls power circuit and analyses motor output. The innovation in this research is that the third harmonic function is used for motor control and is compared with the Back-EMF force to recognize zero crossing. Moreover, N-type MOSFETs are used in power circuit high side and low side which are useful in the current rate of MOSFETs due to their similarities. Also, the IR2101 MOSFET drive is utilized for startup which improves the firing time of MOSFETs. Besides, using tantalum capacitors and putting resistor by the gate route of MOSFETs is efficient. Finally, experimental results are given to verify the validation of the proposed method.