Fuzzy Neural Network Applied in Sensorless BLDC Motor Control Based on MC56F8013

Li Huo Wang; Wei Yao; Ke Wei Hu; Wei Zhang

doi:10.4028/www.scientific.net/AMM.63-64.841

Paper Titles

Integrated Scheduling of Container Terminal Process Based on CIMS
p.822

Research on Motion Analysis and Embedded Control System of Search-Rescue Robot
p.827

Research on Walking Stability of Quadruped Search-Rescue Robot
p.831

The Viterbi Decoding Scheme for FPGA
p.835

Fuzzy Neural Network Applied in Sensorless BLDC Motor Control Based on MC56F8013
p.841

Research of Face Identification Method Based on Geometric Feature Extraction and the Enlargement of Image Interpolation with Scientific Image Materials
p.846

Intermittent Fault Diagnosis Method of Power System Based on HMM-SVM Characteristics
p.850

Extended Web Services Model Design for Non-Functional Requirements
p.855

Classification of Knowledge Discovery Methods
p.859

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 63-64Fuzzy Neural Network Applied in Sensorless BLDC...

Fuzzy Neural Network Applied in Sensorless BLDC Motor Control Based on MC56F8013

Abstract:

This paper describes Freescale company’s DSP device MC56F8013 implementation of a control method for sensorless BLDC motor, which is according to fuzzy neural network. The inductance of stator core varies according to the variation of rotor position, and the rotor position can be estimated with the variation of current response caused by six direction voltage vectors. Then use fuzzy neural network PI control method to optimize the dynamic performance, accelerate the rotor to a certain speed, and switch to EMF mode. The experiment results show that the proposed method can have fast response, strong robustness and superior performances.

You might also be interested in these eBooks

Advanced Research on Mechanical Engineering, Industry and Manufacturing Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 63-64)

Pages:

841-845

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.63-64.841

Citation:

Cite this paper

Online since:

June 2011

Authors:

Li Huo Wang, Wei Yao, Ke Wei Hu, Wei Zhang

Keywords:

Brushless Direct Current Motor (BLDCM), EMF, Fuzzy Neural Network (FNN), PI, Sensorless

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Kwang-Woon Lee, Dae-Kyong Kim, Byung-Taek Kim, and Byung-Il Kwon: A novel starting method of the surface permanent-magnet BLDC motors without position sensor for reciprocating compressor, IEEE Trans. Ind. Appl., vol.44, no.1(2008).

DOI: 10.1109/icems12746.2007.4412176

Google Scholar

[2] Shao JW, Nolan D, Hopkins T: A novel direct back EMF detection for sensorless brushless DC (BLDC) motor drives, IEEE Appl. Power Electron. Conf. Expo., vol.1+23(2002).

DOI: 10.1109/apec.2002.989224

Google Scholar

[3] Mirtalaei S.M.M., Moghani J.S., Malekian K., Abdi B.: A novel sensorless control strategy for BLDC motor drives using a fuzzy logic-based neural network observer, International Power Electronics Electrical Drives Automation and Motion SPEEDAM, vol.1491-1496(2008).

DOI: 10.1109/speedham.2008.4581091

Google Scholar

[4] Rubaai Ahmed, Young Paul: DSP-based fuzzy neural network PI/PD-like fuzzy controller for motion controls and drives, IEEE Industry Applications Society Annual Meeting (2010).

DOI: 10.1109/ias.2010.5614081

Google Scholar

[5] Freescale: DSP56F8013 Data Sheet(2005).

Google Scholar