A Multi-Agent Based TE Process Simulation and Optimization Platform

Article Preview

Abstract:

For implementing the online control and simulation of TE process, a simulation and optimization platform is proposed based on multi-agent technology. Professional software such as G2, GAMS, Matlab, are wrapped as agents with multi-agent technology. Based on the simple object access protocol, it can control and optimize the online simulation procedure of TE process. Finally the practicability and validity of the proposed platform are verified through the application in the TE process simulation and optimization.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 1049-1050)

Pages:

1098-1101

Citation:

Online since:

October 2014

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] H.Y. Sun, Multi-Agent dynamic fusion method based on utility evaluation for equipment intelligent diagnosis, Journal of Vibration Engineering, 22(4), pp.413-417, (2009).

Google Scholar

[2] E. Serrano, Infrastructure for forensic analysis of multi-Agent systems, Lecture Notes in Computer Science, pp.168-183, (2009).

DOI: 10.1007/978-3-642-03278-3_11

Google Scholar

[3] B. Fan, Dynamic workflow management system supported by multi-intelligent-Agent, Proceedings-2009 International Symposium on Information Engineering and Electronic Commerce, pp.192-196, (2009).

DOI: 10.1109/ieec.2009.45

Google Scholar

[4] F. Zhao, A multi-Agent model for the order driven agile manufacturing systems and order form selection algorithm, 2009 IEEE International Conference on Information and Automation, pp.1625-1630, (2009).

DOI: 10.1109/icinfa.2009.5205177

Google Scholar

[5] J. J. Downs and E. F. Vogel, A Plant-Wide Industrial Process Control Problem. Computers and Chemical Engineering, 3 , pp.245-255(1993).

DOI: 10.1016/0098-1354(93)80018-i

Google Scholar

[6] T. J. McAvoy and N. Ye, Base control for the Tennessee Eastman problem, Computers and Chemical Engineering, 5 , pp.383-414(1998).

DOI: 10.1016/0098-1354(94)88019-0

Google Scholar

[7] N. L. Ricker, Optimal steady-state operation of the Tennessee Eastman challenge process, Computers and Chemical Engineering, 9, pp.949-982(1995).

DOI: 10.1016/0098-1354(94)00043-n

Google Scholar

[8] N. L. Ricker and J. H. Lee, Nonlinear modeling and state estimation for the Tennessee Eastman challenge process, Computers and Chemical Engineering, 9, pp.983-1006(1995).

DOI: 10.1016/0098-1354(94)00113-3

Google Scholar

[9] T. J. McAvoy and N. Ye, Base control for the Tennessee Eastman problem, Computers and Chemical Engineering, 5 , pp.383-414, (1998).

DOI: 10.1016/0098-1354(94)88019-0

Google Scholar