Acta Mechanica Solida Sinica

, Volume 26, Issue 3, pp 255–262 | Cite as

Dynamic Modeling and Active Control of Flexible Plate Based on the Input-Output Data

  • Yong Xie
  • Tong Zhao
  • Guoping Cai


This paper studies the low-order dynamic modeling and active control of a flexible plate and provides experimental verification. First based on the input-output data of the system, the Markov parameters of the system are identified using the method of observer/Kalman filter identification (OKID). Then a low-order state-space model is built using the eigensystem realization algorithm (ERA). Finally, a linear quadratic Gaussian (LQG) controller is designed based on the low-order state-space model. Experimental results have proved the effectiveness and feasibility of the research.

Key Words

flexible plate OKID ERA active control experiment 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Miao, B.Q., Qu, G.J., Xia, S.Q. and Cheng, D.S., On the order reduction of dynamics models of flexible spacecraft. Engineering Science, 2001, 3(11): 60–64 (in Chinese).Google Scholar
  2. 2.
    Zhao, Y.Q., Chen, S.H., Chai, S. and Qu, Q.W., An improved modal truncation method for responses to harmonic excitation. Computers and Structures, 2002, 80(1): 99–103.CrossRefGoogle Scholar
  3. 3.
    Suarez, L.E. and Singh, M.P., Modal synthesis method for general dynamic systems. Journal of Engineering Mechanics, 1992, 118(7): 1488–1503.CrossRefGoogle Scholar
  4. 4.
    Hughes, P.C., Modal identities for elastic bodies with application to vehicle dynamics and control. Journal of Applied Mechanics, 1980, 47: 177–184.MathSciNetCrossRefGoogle Scholar
  5. 5.
    Skelton, R.E. and Yousuff, A., Component cost analysis of large-scale systems. International Journal of Control, 1983, 37(2): 285–304.MathSciNetCrossRefGoogle Scholar
  6. 6.
    Moore, B.C., Principal component analysis in linear system: controllability, observability and model reduction. IEEE Transaction on Automatic Control, 1981, 26(1): 17–31.MathSciNetCrossRefGoogle Scholar
  7. 7.
    Park, J., Transfer function methods to measure dynamic mechanical properties of complex structures. Journal of Sound and Vibration, 2005, 288(1–2): 57–79.MathSciNetCrossRefGoogle Scholar
  8. 8.
    Juang, J.N., Phan, M., Horta, L.G. and Longman, R.W., Identification of observer/Kalman filter Markov parameters: theory and experiments. Journal of Guidance, Control and Dynamics, 1993, 16: 320–329.CrossRefGoogle Scholar
  9. 9.
    Dong, X.J., Meng, G. and Peng, J.C., Vibration control of piezoelectric smart structures based on system identification technique: numerical simulation and experimental study. Journal of Sound and Vibration, 2006, 297(3–5): 680–693.MathSciNetCrossRefGoogle Scholar
  10. 10.
    Juang, J.N. and Phan, M., Identification and Control of Mechanical Systems. New York: Cambridge University Press, 2001.CrossRefGoogle Scholar
  11. 11.
    Li, D.B., Experimental Modal Analysis and Application. Beijing: Science Press, 2001 (in Chinese).Google Scholar
  12. 12.
    Chen, L.X., Cai, G.P. and Pan, J., Experimental study of delayed feedback control for a flexible plate. Journal of Sound and Vibration, 2009, 322: 629–651.CrossRefGoogle Scholar

Copyright information

© The Chinese Society of Theoretical and Applied Mechanics and Technology 2013

Authors and Affiliations

  1. 1.Department of Engineering Mechanics, State Key Laboratory of Ocean EngineeringShanghai Jiaotong UniversityShanghaiChina

Personalised recommendations