Study on static and dynamic modeling of nonlinear system

Liping Qu; Hongjian Wang; Xinqian Bian; Kejun Wang

doi:10.1117/12.806446

13 October 2008 Study on static and dynamic modeling of nonlinear system

Liping Qu, Hongjian Wang, Xinqian Bian, Kejun Wang

Proceedings Volume 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence; 71271S (2008) https://doi.org/10.1117/12.806446
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China

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.

Citation Download Citation

Liping Qu, Hongjian Wang, Xinqian Bian, and 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); https://doi.org/10.1117/12.806446

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