Position Sensorless Control System of SRM Based on Improved BP Neural Network

Li Xiao; He Xu Sun; Feng Gao

doi:10.4028/www.scientific.net/AMR.468-471.2187

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Position Sensorless Control System of SRM Based on...

Position Sensorless Control System of SRM Based on Improved BP Neural Network

Abstract:

Due to the shortcomings of long training time and slow convergence of BP neural network, this paper presents a new improved method that weight is no longer a constant but turned into a function of adjustable parameters. After the training of the improved BP neural network is completed, the network can map the nonlinear relationship between motor current, flux and rotor position. Based on the analysis of the unique structural properties of switched reluctance motor, this paper also proposes a method of greatly reducing the sample data to save computing time. Simulation results show that this method simplifies the complexity of the control system and improve detection accuracy, thus realize position sensorless detection of the switched reluctance motor.

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Periodical:

Advanced Materials Research (Volumes 468-471)

Pages:

2187-2192

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.468-471.2187

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Online since:

February 2012

Authors:

Li Xiao, He Xu Sun, Feng Gao

Keywords:

Improved BP Neural Network, Position Sensorless Detection, Switched Reluctance Motor (SRM)

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