Saha, Nilanjan and Roy, D (2011) Two-Stage Extended Kalman Filters with Derivative-Free Local Linearizations. In: Journal of Engineering Mechanics-ASCE, 137 (8). pp. 537-546.
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This paper proposes a derivative-free two-stage extended Kalman filter (2-EKF) especially suited for state and parameter identification of mechanical oscillators under Gaussian white noise. Two sources of modeling uncertainties are considered: (1) errors in linearization, and (2) an inadequate system model. The state vector is presently composed of the original dynamical/parameter states plus the so-called bias states accounting for the unmodeled dynamics. An extended Kalman estimation concept is applied within a framework predicated on explicit and derivative-free local linearizations (DLL) of nonlinear drift terms in the governing stochastic differential equations (SDEs). The original and bias states are estimated by two separate filters; the bias filter improves the estimates of the original states. Measurements are artificially generated by corrupting the numerical solutions of the SDEs with noise through an implicit form of a higher-order linearization. Numerical illustrations are provided for a few single- and multidegree-of-freedom nonlinear oscillators, demonstrating the remarkable promise that 2-EKF holds over its more conventional EKF-based counterparts. DOI: 10.1061/(ASCE)EM.1943-7889.0000255. (C) 2011 American Society of Civil Engineers.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Asce-Amer Soc Civil Engineers.|
|Keywords:||Two-stage filter;Extended Kalman filters;Model uncertainty; Derivative-free local linearizations;Parameter estimations|
|Department/Centre:||Division of Mechanical Sciences > Civil Engineering|
|Date Deposited:||30 Aug 2011 05:36|
|Last Modified:||30 Aug 2011 05:36|
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