Optimized Fuzzy Neural Networks Control of a Magnetic Suspension Vibration Isolation System

Abstract:

Active vibration isolation technology can overcome the defects of passive vibration isolation technology that the poor vibration isolation performance in low and resonant frequencies. Compared with other active vibration isolation technologies, magnetic suspension isolation technology has shown useful characteristics, such as wide response frequency range, fast response, high reliability and long-life. However, the control of MSVI is still one of the areas that require further investigation. This paper presents a Fuzzy Neural Networks(FNN) control algorithm for a magnetic suspension isolation vibration system, which is optimized by improved Genetic Algorithm(GA). The output force responses of the FNN and passive vibration isolation system under same excitation are simulated. The simulation results show that the fuzzy control system has much better performance in vibration isolation.

• Periodical: Applied Mechanics and Materials (Volumes 226-228)
• Pages: 328-334
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.226-228.328
• Online since: November 2012
• Authors: Chun Sheng Song, Ye Fa Hu
• Keywords: Electromagnetic Force, Improved GA, Magnetic Suspension Isolator, Optimized FNN Control

References

[1] Y. Liu,H.Matsuhisa,H.Utsuno.Semi-Active Vibration Isolation System with Variable Stiffness And Damping Control.Journal of Sound and Vibration .Vol. 313 (2008).No.2,pp.16-28

DOI: 10.1016/j.jsv.2007.11.045

[2] C. Song, Y. Hu, Z. Zhou, Semi-Active Fuzzy Control for a Floating Raft Isolation System with Magnetic Suspension Supporting, Journal of vibration and shock, Vol. 28 (2009) .No.9,pp.30-32(In Chinese)

DOI: 10.1109/appeec.2009.4918737

[3] C. Song, Z. Zhou, Y. Hu, Semi-active Fuzzy Control for Multi-Dof Floating Raft Isolation System with Magnetic Suspension Isolators.2009 Asia-Pacific Power and Energy Engineering Conference Proceedings. art. no. 4918737

DOI: 10.1109/appeec.2009.4918737

[4] S. N. Sivanandam, S. Sumathi and S. N. Deepa. Introduction to Fuzzy Logic using Matlab. Springer (2007)16-23

DOI: 10.1007/978-3-540-35781-0

[5] K.T. Chen, C.H. Chou, S.H. Chang, Y.H. Liu, et al. Intelligent Active Vibration Control in an Isolation Platform. Applied Acoustics 69 (2008) 1063–1084

DOI: 10.1016/j.apacoust.2007.06.008

[6] A.A. Madkour, M.A. Hossain, K.P. Dahal, H.Yu, Intelligent Learning Algorithms for Active Vibration Control,IEEE Transactions On Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 37(2007)p,1022-1033

DOI: 10.1109/tsmcc.2007.900640

[7] Information on http://www.scholarpedia.org/article/Fuzzy_neural_network#Characteristics (Accessed 1 July 2010)

[8] Information on http://en.wikipedia.org/wiki/Neuro-fuzzy(Accessed 1 July 2010)