Unscented Kalman Filter for Non-Linear Identification of a New Prototype of Bidirectional Tuned Vibration Absorber: A Numerical Investigation

Article Preview

Abstract:

Several nonlinear system identification methods have been presented in the past, such as the Extended Kalman Filter, the H filter and the Sequential Monte Carlo methods. One of the most promising ones is the Unscented Kalman Filter (UKF) recently proposed for the on-line identification of structural parameters. In the present study the UKF is proposed to the purpose of the nonlinear identification of a new prototype of rolling-pendulum tuned vibration absorber which, relying on an optimal three-dimensional guiding receptacle, can simultaneously control the response of the supporting structure along two orthogonal horizontal directions. Unlike existing ball vibration absorbers, mounted on spherical recesses and used in axial-symmetrical structures, the new device can be bidirectionally tuned to both fundamental structural modes even when the corresponding natural frequencies are different, by virtue of the optimum shape of the rolling cavity. Based on preliminary numerical simulations, the UKF is shown to be effective in identifying the structural parameters of the new device and particularly the nonlinear rolling friction dissipation mechanism at the interface between the ball bearing and the rolling surface.

You might also be interested in these eBooks

Info:

Periodical:

Key Engineering Materials (Volumes 569-570)

Pages:

948-955

Citation:

Online since:

July 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] G. Kerschen, K. Worden, A.F. Vakakis, J.C. Golinval, Past, present and future of nonlinear system identification in structural dynamics, Mechanical Systems and Signal Processing 20 (2006) 505-592.

DOI: 10.1016/j.ymssp.2005.04.008

Google Scholar

[2] O.S. Bursi, R. Ceravolo, S. Erlicher, L. Zanotti Fragonara, Identification of the hysteretic behaviour of a partial-strength steel-concrete moment-resisting frame structure subject to pseudodynamic tests, Earthquake Engineering & Structural Dynamics 41 (2012).

DOI: 10.1002/eqe.2163

Google Scholar

[3] R.E. Kalman, A New Approach to Linear Filtering and Prediction Problems, ASME Journal of Basic Engineering 82 (1960) 35-45.

DOI: 10.1115/1.3662552

Google Scholar

[4] A.H. Jazwinski, Filtering for nonlinear dynamical systems, IEEE Transactions on Automatic Control 11 (1966) 765-766.

DOI: 10.1109/tac.1966.1098431

Google Scholar

[5] R.F. Stengel, Optimal Control and Estimation, Dover Publications, (1994).

Google Scholar

[6] S.F. Julier, J.K. Uhlmann, H.F. Durrant-Whyte, A new method for the nonlinear transformation of means and covariances in filters and estimators, IEEE Trans. Automat. Control 45(3) (2000) 477-482.

DOI: 10.1109/9.847726

Google Scholar

[7] M. Wu, A.W. Smyth, Real-time parameter estimation for degrading and pinching hysteretic models, International Journal of Non-Linear Mechanics 43 (2008) 822-833.

DOI: 10.1016/j.ijnonlinmec.2008.05.010

Google Scholar

[8] R. Ceravolo, E. Matta, A. Quattrone, C. Surace, L. Zanotti Fragonara, On-line identification of time-varying systems equipped with adaptive control, Journal of Physics: Conference Series 382 (2012).

DOI: 10.1088/1742-6596/382/1/012038

Google Scholar

[9] E. Matta, A. De Stefano, B.F. Jr. Spencer, A new passive rolling-pendulum vibration absorber using a non-axial-symmetrical guide to achieve bidirectional tuning, Earthquake Engineering and Structural Dynamics 38 (2009) 1729-1750.

DOI: 10.1002/eqe.929

Google Scholar

[10] G.B. Warburton, E.O. Ayorinde, Optimum absorber parameters for simple systems, Engineering and Structural Dynamics 8 (1980) 197-217.

DOI: 10.1002/eqe.4290080302

Google Scholar

[11] E. Matta, A. De Stefano, Seismic performance of pendulum and translational roof-garden TMDs, Mechanical Systems and Signal Processing 23 (2009) 908–921.

DOI: 10.1016/j.ymssp.2008.07.007

Google Scholar

[12] V.P. Legeza, Analytic determination of the amplitude-frequency characteristic of a nonlinear vibroprotective system with roller damper, Strength of Materials 37/2 (2005) 214-224.

DOI: 10.1007/s11223-005-0033-y

Google Scholar

[13] M. Pirner, Actual behaviour of a ball vibration absorber, Journal of Wind Engineering and Industrial Aerodynamics 90 (2002) 987-1005.

DOI: 10.1016/s0167-6105(02)00215-5

Google Scholar

[14] S. Kolas, B.A. Foss, T.S. Schei, Constrained nonlinear state estimation based on the UKF approach, Computers and Chemical Engineering 33 (2009) 1386-1401.

DOI: 10.1016/j.compchemeng.2009.01.012

Google Scholar

[15] B.O.S. Teixera, L.A.B. Torres, L.A. Aguirre, D.S. Bernstein, On unscented Kalman filtering with state interval constraint, J. of Process Control 20 (2010) 45-57.

DOI: 10.1016/j.jprocont.2009.10.007

Google Scholar

[16] P. Vachani, S. Narasimhan, R. Rengaswamy, Robust and reliable estimation via Unscented Recursive Nonlinear Dynamic Data Reconciliation, J. of Process Control 16 (2006) 1075-1086.

DOI: 10.1016/j.jprocont.2006.07.002

Google Scholar