First derivatives estimation of nonlinear parameters in hybrid system

Jung Wook Park; Byoung Kon Choi; Kyung Bin Song

doi:10.1093/ietfec/e89-a.12.3736

First derivatives estimation of nonlinear parameters in hybrid system

Jung Wook Park, Byoung Kon Choi, Kyung Bin Song

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

This letter describes the first derivatives estimation of nonlinear parameters through an embedded identifier in the hybrid system by using a feed-forward neural network (FFNN). The hybrid systems are modelled by the differential-algebraic-impulsive-switched (DAIS) structure. The FFNN is used to identify the full dynamics of the hybrid system. Moreover, the partial derivatives of an objective function J with respect to the parameters are estimated by the proposed identifier. Then, it is applied for the identification and estimation of the non-smooth nonlinear dynamic behaviors due to a saturation limiter in a practical engineering system.

Original language	English
Pages (from-to)	3736-3738
Number of pages	3
Journal	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume	E89-A
Issue number	12
DOIs	https://doi.org/10.1093/ietfec/e89-a.12.3736
Publication status	Published - 2006 Dec

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Graphics and Computer-Aided Design
Electrical and Electronic Engineering
Applied Mathematics

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10.1093/ietfec/e89-a.12.3736

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First derivatives estimation of nonlinear parameters in hybrid system

Abstract

All Science Journal Classification (ASJC) codes

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