期刊
JOURNAL OF VIBRATION AND CONTROL
卷 19, 期 6, 页码 847-856出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/1077546311433608
关键词
Artificial neural network; dynamic modeling; magnetic suspension isolator; modified genetic algorithm
资金
- National Natural Science Foundation of China [50935005, 51175390]
- Hubei Province Natural Science Fund Key Projects [2009CDA028]
- Wuhan University Innovation Fund Research Project [2011-IV-121]
Active vibration isolation technology has been widely used to reduce vibration transmission in many different engineering systems. Magnetic suspension isolator (MSI), as an active isolation actuator, has shown advantages including non-contact, high response frequency, high reliability and long life-span. However, its potential has not been fully explored due to the nonlinear and hysteretic behavior in a dynamic environment, and there is limited research work in the area. This paper proposes a new artificial neural network (ANN)-based approach to model the dynamics of MSI. A modified genetic algorithm (MGA) is developed to train the ANN to improve the model accuracy. Results clearly show that the ANN model with the MGA approach outperforms the back propagation (BP) approach and the analytic method based on the least squares fitting method.
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