Improved EKF Algorithms for Nonlinear Time-varying System Identification Based on Feed Forward Neural Network

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Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (8) : 5-8.

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Improved EKF Algorithms for Nonlinear Time-varying System Identification Based on Feed Forward Neural Network

Kai-ping Yu1;Xiao-ming Mou2

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Abstract

In order to overcome the drawback of traditional extended Kalman filter (EKF) procedure, the improved EKF scheme,was proposed and applied to nonlinear time-varying system identification based on feed forward neural network. The proposed algorithm relaxes the data saturation. Simulation results of both a nonlinear time-varying systems with a single variable and a three degrees-of-freedom structural system with nonlinear time-varying stiffness show that the proposed algorithms can overcome the problem of divergence and consume less computational cost and is of higher accuracy and robustness.

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nonlinear time-varying system / multi-layer feed forward neural network / system identification / improved EKF

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Kai-ping Yu;Xiao-ming Mou . Improved EKF Algorithms for Nonlinear Time-varying System Identification Based on Feed Forward Neural Network[J]. Journal of Vibration and Shock, 2010, 29(8): 5-8