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Volume 41 Issue 2
Feb.  2015
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Journal of Beijing University of Aeronautics and Astronautics  > 2015  >  41(2): 259-266.
LI Yunlong, WANG Xiaojun, HUANG Renet al. Non-probabilistic reliability analysis of active control system for structural vibration[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(2): 259-266. doi: 10.13700/j.bh.1001-5965.2014.0133(in Chinese)
Citation: LI Yunlong, WANG Xiaojun, HUANG Renet al. Non-probabilistic reliability analysis of active control system for structural vibration[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(2): 259-266. doi: 10.13700/j.bh.1001-5965.2014.0133(in Chinese)
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Non-probabilistic reliability analysis of active control system for structural vibration

doi: 10.13700/j.bh.1001-5965.2014.0133

  • School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 20 Mar 2014
  • Publish Date: 20 Feb 2015
    Abstract
  • To solve the reliability problem of active control system of structural vibration, considering the uncertainties in controlled structure, reliability analysis of the active control system for structural vibration based on non-probabilistic reliability model was studied. The uncertain parameters were expressed in the form of interval number or vector. Calculation method of responses of the closed-loop system with interval parameters was proposed based on interval mathematics. Combined with the non-probabilistic reliability model, non-probabilistic reliability analysis method, which requires the bounds of the uncertainties rather than the probability density function, was established for active vibration control systems. This reliability analysis approach had certain theoretical significance for reliability analysis of open-loop system, closed-loop control system and reliability-based controller design. The results of numerical examples demonstrate the effectiveness of the proposed method and the applicability for complex structures compared with the Monte Carlo method that can be taken as the benchmark of accuracy for judgment.

     

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