Improvement Of Parameter Estimation for Non-Linear Hysteretic Systems With Slip By A Fast Bayesian Bootstrap Filter

S. J. Li, Wuhan University of Technology
Yoshiyuki Suzuki, Kyoto University
Mohammad N. Noori, North Carolina State University at Raleigh

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The definitive version can be found online at: http://dx.doi.org/10.1016/j.ijnonlinmec.2004.02.005. © 2004 Elsevier Ltd.

NOTE: At the time of publication, the author Mohammad N.Noori was affiliated with North Carolina State University. Currently, August 2008, he is the Dean of the College of Engineering at California Polytechnic State University - San Luis Obispo.

Abstract

Modeling and identification of non-linear hysteretic systems are widely encountered in the structural dynamics field, especially for the hysteresis with slip. A model, called SL model, which can describe the pinching of most practical hysteresis loops perfectly was proposed by Baber and Noori (J. Eng. Mech. 111 (1985) 1010). A method of estimating the parameters of SL model on the basis of input–output data based on bootstrap filter was proposed by the writers. Bootstrap filter is a filtering method based on Bayesian state estimation and Monte Carlo method, which has the great advantage of being able to handle any functional non-linearity and system and/or measurement noise of any distribution. The standard bootstrap filter, however, is not time efficient, i.e., it is very time consuming and is not suitable for real-time applications. In this paper, previous work by the writers is extended to do the parameter estimation of SL model by a fast Bayesian bootstrap filtering technique. Simulation results are presented to demonstrate the performance of the algorithm.