2018
DOI: 10.1177/0020294018786753
|View full text |Cite
|
Sign up to set email alerts
|

Hybrid control technique for minimizing the torque ripple of brushless direct current motor

Abstract: This paper presented the brushless direct current motor torque ripple reduction based on the speed and torque control using hybrid technique. The dynamic behavior of the brushless direct current motor is analyzed in terms of the parameters such as the speed, current, back electromotive force and torque. Based on the parameters, the motor speed is controlled and minimized the torque ripples. For controlling the speed of the brushless direct current motor is utilized the fractional-order proportional-integral-de… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
8
0
1

Year Published

2019
2019
2024
2024

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 23 publications
(9 citation statements)
references
References 42 publications
0
8
0
1
Order By: Relevance
“…Hybrid techniques [17] involve adaptive Neuro-Fuzzy and firefly algorithm to reduce the computation time, harmonics, and torque ripple. The finite algorithm method is used to analyze the change in functions to acquire the maximum gain value.…”
Section: Goswami and Joshimentioning
confidence: 99%
“…Hybrid techniques [17] involve adaptive Neuro-Fuzzy and firefly algorithm to reduce the computation time, harmonics, and torque ripple. The finite algorithm method is used to analyze the change in functions to acquire the maximum gain value.…”
Section: Goswami and Joshimentioning
confidence: 99%
“…With the develop rapidly of electric power electronic technology, modern sensor technology, advanced manufacturing technology, and automatic control technology in recent years, the brushless DC motor (BLDCM) has been widely applied to servo, actuation, positioning, and variable speed applications for its many advantages such as high efficiency, high dynamic response, high reliability and low maintenance [1][2][3]. Moreover, speed regulation is a vital part of BLDCM drive for accurate speed and position control applications, which requires the design of a high-efficiency controller to achieve continuous control performance under diverse working conditions [4][5][6][7][8]. In recent decades, scholars have proposed many speed control methods to improve the operation performance of BLDCM.…”
Section: Introductionmentioning
confidence: 99%
“…Due to various uncertainties and nonlinearity exist in the PID structure, which makes it difficult to determine the PID gain, thus reducing the control system's performance [11]. Therefore, scholars have proposed a large number of intelligent algorithms such as metaheuristic optimization algorithm, fuzzy logic, differential evolution algorithm and deep neural network to improve the robustness of the control system [4][5][6][7][8][12][13][14][15][16][17][18][19][20]. Moreover, fuzzy logic-based methods provide better results than neural network and sliding mode control algorithms most of the time due to their offline training and chattering phenomenon [16,[21][22][23].…”
Section: Introductionmentioning
confidence: 99%
“…Chen et al (2017) presented a new method which depends on Genetic Algorithms to search for the Fourier coefficients of three-phase stator currents for a given back electromotive force (back EMF) waveforms. Prathibanandhi and Ramesh (2018) proposed a strategy which combined the adaptive neuro-fuzzy inference system with firefly algorithm. Based on a novel fuzzy adaptive speed controller and an adaptive weighting factor, Zhang et al (2021) proposed an improved Finite control set-model predictive torque control (FCS-MPTC) strategy to reduce the speed, torque and flux ripples.…”
Section: Introductionmentioning
confidence: 99%