Improvement Of Parameter Estimation for Non-Linear Hysteretic Systems With Slip By A Fast Bayesian Bootstrap FilterInternational Journal of Non-Linear Mechanics
AbstractModeling 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.
Citation InformationS. J. Li, Yoshiyuki Suzuki and Mohammad N. Noori. "Improvement Of Parameter Estimation for Non-Linear Hysteretic Systems With Slip By A Fast Bayesian Bootstrap Filter" International Journal of Non-Linear Mechanics Vol. 39 Iss. 9 (2004) p. 1435 - 1445
Available at: http://works.bepress.com/mnoori/21/