13 October 2008 Study on static and dynamic modeling of nonlinear system
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Abstract
In this paper, a means, which is based on Radial Basis Function Neural Network (RBFNN), is firstly presented to make the model for nonlinear systems. As an application example of this means, the high power DC graphitizing furnace is analyzed, and the RBF model for graphitizing furnace is constructed from experiments or simulations. The procedures for training the model are described along with discussions on error. Secondly, the open loop dynamic model is discussed in detail. The dynamic model of graphitizing furnace is accomplished in this paper. All the simulated results show that the discussed approaches are effective.
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Liping Qu, Liping Qu, Hongjian Wang, Hongjian Wang, Xinqian Bian, Xinqian Bian, Kejun Wang, Kejun Wang, } "Study on static and dynamic modeling of nonlinear system", Proc. SPIE 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence, 71271S (13 October 2008); doi: 10.1117/12.806446; https://doi.org/10.1117/12.806446
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