Digital implementation of fuzzy logic controller for wide range speed control of brushless DC motor

Shanmugasundram, R.; Zakariah, K. Muhammed; Yadaiah, N.

doi:10.1109/icves.2009.5400189

Cited by 27 publications

(6 citation statements)

References 6 publications

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“…FLC is one of the advanced control techniques applied for the nonlinear and complex industrial control systems (Rubaai et al, 2001(Rubaai et al, , 2002(Rubaai et al, , 2008Shanmugasundram et al, 2009a) whose mathematical models are unpredictable. However, it has its own advantages and limitations.…”

Section: Fuzzy Logic Controller For Brushless Direct Current Drivementioning

confidence: 99%

“…A conventional controller like the proportional-integral-derivative (PID) controller requires an accurate mathematical model describing the system, but practically obtaining the exact mathematical model is a cumbersome process (Weerasooriya and El-Sharkavi, 1991). In recent years, many control techniques have been introduced in the modern drive systems using PID controllers (Wu et al, 2005;Bagis, 2007), neural networks (Narendra and Parthasarathy, 1990;Rahman and Hoque, 1997;Lee and Teng, 2000;Rubaai et al, 2000), an adaptive controller using particle swarm optimization algorithm and a neuro-fuzzy controller (Rubaai et al, 2002;Awadallah et al, 2009), a multi-layer artificial neural network (Weerasooriya and El-Sharkavi, 1991;El-Sharkawi et al, 1994), hybrid controllers (Rubaai et al, 2001(Rubaai et al, , 2008, fuzzy logic controller (FLC) (Shanmugasundram et al, 2009a;Rajan et al, 2010) and compensator (Shanmugasundram et al, 2008). These control techniques are usually based on system model parameters.…”

Section: Introductionmentioning

confidence: 99%

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Modeling, simulation and analysis of controllers for brushless direct current motor drives

Shanmugasundram¹,

Zakaraiah

Yadaiah

2012

Journal of Vibration and Control

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Brushless direct current (BLDC) motors are widely used in industrial, aerospace, medical, machine tools, aerospace and control applications. Nowadays they are becoming popular due to their advantages such as reduced maintenance, better speed-torque characteristics, good dynamic performance, noiseless operation, wide speed range, compact size, high torque to volume ratio, low moment of inertia and high efficiency. However, very few control techniques are available for controlling the BLDC drive systems. This paper presents a MATLAB simulation of practically realizable control techniques such as a conventional proportional-integral-derivative (PID) controller, a fuzzy controller, an adaptive artificial neural network proportional-integral-derivative (ANN-PID) controller and a pulse width modulation technique based PID controller for achieving better performance during the operating conditions. The simulation results are presented to highlight the effectiveness of these controllers such as speed of response, overshoot and steady-state error etc.

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Section: Fuzzy Logic Controller For Brushless Direct Current Drivementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling, simulation and analysis of controllers for brushless direct current motor drives

Shanmugasundram¹,

Zakaraiah

Yadaiah

2012

Journal of Vibration and Control

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“…The general fuzzy logic controller consists of four parts as illustrated in Figure 3. They are fuzzification, fuzzy rule-base, fuzzy inference engine and defuzzification [5].…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

Speed Control of Permanent Magnet DC Motor by using Combination of Adaptive Controller and Fuzzy Controller

Moussavi¹,

Alasvandi²,

Javadi³

2012

IJCA

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A novel controller based on adaptive controller and fuzzy controller for Permanent Magnet Direct Current motor is proposed in this paper. The proposed controller is compared with adaptive controller and fuzzy controller for PMDC motor. By means of simulation in MATLAB, we concluded that the proposed controller will be achieved the shorter settling time and also lower overshoot and steady state error. General TermsController, Simulation, MATLAB.

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“…Almost in the system the parameters changes practically for their responses during the operating conditions. In this paper the modeling and controlling of fuzzy logic controller based BLDC motor which compare its performance with the PI controller based BLDC motor drive using TMS320LF2407A digital signal processor (DSP) is described and experimental results are presented [6]. At different operating conditions these controllers is investigated during such as parameter variations and load disturbances are occur.…”

Section: Introductionmentioning

confidence: 97%

Modeling and controlling of BLDC motor based fuzzy logic

Blessy

Murugan

2014

International Conference on Information Communication and Embedded Systems (ICICES2014)

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This paper presents the modeling and controlling of a fuzzy logic controller (FLC) for achieving improved dynamic performance of the Brushless DC (BLDC) motor drive. The performance of fuzzy and the PI controller based BLDC motor drives is investigated under the different operating conditions such as change in reference speed, parameter variations and the load disturbance. BLDC motors are used in industrial control, automation and instrumentation system applications. Based on other applications the conventional controllers like P, PI and PID controllers are used in the BLDC motor drive control systems to achieve the desired level of transient and steady state responses. However, the major problem in the conventional PI controller there is some variations in the parameter and some load disturbances are occur and do not yield the better transient and the steady state responses under the operating conditions. In this paper, the modeling and controlling of fuzzy logic controller is presented its performance and it compared with the PI controller shows the error capability and usefulness of the fuzzy controller in the control applications.

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Digital implementation of fuzzy logic controller for wide range speed control of brushless DC motor

Cited by 27 publications

References 6 publications

Modeling, simulation and analysis of controllers for brushless direct current motor drives

Modeling, simulation and analysis of controllers for brushless direct current motor drives

Speed Control of Permanent Magnet DC Motor by using Combination of Adaptive Controller and Fuzzy Controller

Modeling and controlling of BLDC motor based fuzzy logic

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