First Derivatives Estimation of Nonlinear Parameters in Hybrid System(Concurrent Systems)

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概要

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• 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.

• 社団法人電子情報通信学会の論文
• 2006-12-01

著者

• Song Kyung-bin

  Department Of Electrical Engineering Soongsil University

• PARK Jung-Wook

  School of Electrical and Electronic Engineering, Yonsei University

• Choi Byoung-kon

  School Of Electrical And Computer Engineering Cornell University

• Park Jung-wook

  School Of Electrical And Electronic Engineering Yonsei University

関連論文

• Hybrid System Based Interpolation Line Search Optimization Applied to Nonlinear Controller in a Power Network(Hybrid Dynamical Systems,Concurrent/Hybrid Systems: Theory and Applications)
• Kalman-Filter Based Estimation of Electric Load Composition with Non-ideal Transformer Modeling(Numerical Analysis and Optimization)
• First Derivatives Estimation of Nonlinear Parameters in Hybrid System(Concurrent Systems)
• Hybrid System Based Nonlinear Least Squares Optimization Applied to a Multi-Machine Power System Control(Hybrid Dynamical Systems,Concurrent/Hybrid Systems: Theory and Applications)

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