A torque ripple suppression technique for brushless DC motor based on PFC buck converter

Jing, Jianli

doi:10.1587/elex.15.20180145

Cited by 4 publications

(5 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Secondly to constitute a control table and stored it in the computer through reasoning and composition operation. Finally to obtain the control output by comparing the actual measured data with the control table to achieve real time control of the manufacturing process [42]- [44].…”

Section: Extended Fuzzy Controller With Modifiable Factorsmentioning

confidence: 99%

A Fuzzy Neural Network Controller Using Compromise Features for Timeliness Problem

Wang¹,

Dong

Huangfu

et al. 2023

IEEE Access

View full text Add to dashboard Cite

W HEN the control rules of traditional fuzzy controller are determined, it comes to be time-consuming and laborious to adjust for different usage conditions. Therefore, the timeliness cannot be guaranteed to solve the timeliness problem, and a fuzzy controller with modifiable factors is designed. While the entire control table is affected by the modifiable factors selection table, all previous control parameters need to be reset. In light of above problems, this paper firstly proposes new fuzzy controller design methods, which retain strengths of traditional controller and controller with modifiable factors. It effectively overcomes the shortcomings of the two controllers mentioned above, and only need to adjust the compromise factor for different working conditions of proposed controller, which is more convenient and efficient. Secondly, the proposed fuzzy controller also adopts a four-layer neural network to optimize the control rules of compromise to improve control precision and system robustness. Finally, the excellent characteristics of proposed controller are verified through simulation research, and the simulation result proves the proposed fuzzy controller has the advantages of higher control precision and smaller transition.

show abstract

Section: Extended Fuzzy Controller With Modifiable Factorsmentioning

confidence: 99%

A Fuzzy Neural Network Controller Using Compromise Features for Timeliness Problem

Wang¹,

Dong

Huangfu

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In each conduction period, only two of the six switches in the inverter are activated [1,10,11,12]. However, the current ripple at the commutation instant between two normal conduction periods is unignorable [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28].…”

Section: Introductionmentioning

confidence: 99%

“…Several researches are proposed to solve this problem and can be roughly divided into two methods. One is to temporarily increase the DC link voltage of the threephase inverter with auxiliary circuits to force the two commutation phase currents to rise and fall with same rate [13,14,15,16,17,18,19,20]. Another method is to adjust the duty cycle of the switches in the three-phase inverter during the commutation period [21,22,23,24,25,26,27,28,29].…”

Section: Introductionmentioning

confidence: 99%

“…An integrated topology derived from a Cuk dc converter and a three-phase inverter is used for driving the motor. Compared with the topologies proposed in [13,14,15,16,17,18,19,20,30], there are only an inductor, a capacitor and an active switch added in this study apart from the three-phase inverter. The three-phase inverter and motor inductances are utilized as the diode and output inductor in the conventional Cuk DC converter.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An integrated permanent magnet brushless motor driver with commutation current ripple reduction

Chen

Juan

et al. 2021

IEICE Electron. Express

View full text Add to dashboard Cite

“…Since nonlinear FLC outdoes the performance of conventional linear PID controllers due to dealing with uncertainties, the combination of both types of controllers can comprehensively improve the performance of PID controller as FLC will be performing the tuning of PID coefficients (11)(12)(13)(14)(15)(16)(17) . Many schemes are developed using fuzzy controllers for the Speed control of DC motors (18)(19)(20)(21)(22)(23)(24)(25) . In this work, these three types of controllers i.e.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-PID based control scheme for PMDC series motor speed control

Kaloi¹

2020

IJST

View full text Add to dashboard Cite

Background/Objectives: PID controllers are widely used in different industrial appliations especially in achieving stable speed control of DC motors. Hower, due to their limitations, most often other methods like Sliding Mode controller, or fuzzy based controller are used. Since the Fuzzy controlers are more adaptive to non-linearity. This study is to analyse a fuzzy-based speed control scheme for tuning/adusting the performance of PID controller for the purpose of speed control of DC motor under the load condition. Methods/Statistical Analysis: Because of low precision and slow response in different control schemes, a performance comparison is shown between three different control approaches for the DC motor speed control. MATLAB's Simulink platform is used to realize DC Motor and to implement the PID, Fuzzy and Fuzzy-based PID controllers to run the DC motor on the desired speed. Fuzzy controller is based on very few rule & performance is analyzed considering the load. Findings: The performance of three controllers is evaluated in terms of transient domain characteristics like Percentage overshoot, settling and rise times and percentage error under load (2000 rpm). The PID controller has the highest overshoot and hence a faster rise time while FLC has significantly reduced the overshoot, therefore causing rise time to increase. For the Fuzzy-PID controller the percentage overshoot has almost vanished. The rise time also decreased as compared to the FLC. The simulated controller's responses confirm that Fuzzy-based PID controller has better performance comparing to independent PID and FLC controllers. Novel/Applications: In this work, the design of an intelligent Fuzzy-PID controller for the speed control of the DC motor with reduced complexity and a faster response using with minimum number of Fuzzy rules producing more optimized performance is presented. The design of a control strategy that has capability to control nonlinear behaviors and to stabilize the performance of linear systems specially to provide optimized performance for speed tracking system which is an important aspect in real time system design.

show abstract

A torque ripple suppression technique for brushless DC motor based on PFC buck converter

Cited by 4 publications

References 19 publications

A Fuzzy Neural Network Controller Using Compromise Features for Timeliness Problem

A Fuzzy Neural Network Controller Using Compromise Features for Timeliness Problem

An integrated permanent magnet brushless motor driver with commutation current ripple reduction

Fuzzy-PID based control scheme for PMDC series motor speed control

Contact Info

Product

Resources

About