[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