NDLI: Spectral-approximation-based intelligent modeling for distributed thermal processes

Content Provider	IEEE Xplore Digital Library
Author	Hua Deng Han-Xiong Li Guanrong Chen
Copyright Year	1993
Abstract	A spectral-approximation-based intelligent modeling approach is proposed for the distributed thermal processing of the snap curing oven that is used in semiconductor packaging industry. The snap curing oven can be described by a nonlinear parabolic distributed parameter system (DPS) in the time-space domain. After finding a proper approximation of the complex boundary conditions of the system, the spectral methods can be applied to time-space separation and model reduction, and neural networks (NNs) can be used for state estimation and system identification. With the help of model reduction techniques, the dynamics of the curing process derived from physical laws can be described by a model of low-order nonlinear ordinary differential equations with a few uncertain parameters and unknown nonlinearities. A neural observer can then be designed to estimate the states of the ordinary differential equation model from measurements taken at specified locations in the field. Using the estimated states, a hybrid general regression NN is trained to be a nonlinear model of the curing process in state-space formulation, which is suitable for the further application of traditional control techniques. Real-time experiments on the snap curing oven show that the proposed modeling method is effective. This modeling methodology can be applied to a class of nonlinear DPSs in industrial thermal processing.
Sponsorship	IEEE Control Systems Society
Starting Page	686
Ending Page	700
Page Count	15
File Size	777949
File Format	PDF
ISSN	10636536
Volume Number	13
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Curing Ovens State estimation Reduced order systems Neural networks Differential equations Semiconductor device packaging Distributed parameter systems Boundary conditions System identification state estimation Curing process distributed thermal process neural networks (NNs) nonlinear distributed parameter systems (DPSs) spatial system identification spectral methods
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering

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