Environmental Engineering Reference
In-Depth Information
[39]
Kouvaritakis B, Cannon M. (2001) Nonlinear Predictive Control: Theory and Practice. The
Institution of Electrical Engineers, London
[40]
Nørgaard M, Ravn O, Poulsen N, Hansen L (2000) Neural networks for modelling and con-
trol of dynamic systems. Springer-Verlag, London
[41]
US Patent and Trademark Office, http://patft.uspto.gov
[42]
Morari M, Baotic M, Borrelli F (2003) Hybrid systems modeling and control. European
Journal of Control 9(2-3):177-189
[43]
Qin S, Badgwell T (2003). A survey of industrial model predictive control technology. Con-
trol Engineering Practice 11:733-764
[44]
Emerson Process Management, www.emersonprocess.com
[45]
Rockwell, www.rockwell.com
[46]
Pavilion Technologies, www.pavtech.com
[47]
ABB, www.abb.com
[48]
ABB
Process
control
system
patent,
European
Patent
EP1553470,
www.freepatentsonline.com
[49]
Gaulocher S, Gallestey E (2008) Advanced process control of a froth flotation circuit, Pro-
ceedings of the Fifth International Seminar on Mineral Processing, Procemin 2008, Santiago
(Chile)
[50]
Andritz Ideas Simulation & Control, www.ideas-simulation.com
[51]
Zervos C, Dumont G (1988) Deterministic adaptive control on Laguerre series representa-
tion. International Journal of Control 48(6):2333-2359
[52]
Honeywell, www.honeywell.com
[53]
Lu Z (1996) Method for optimal controller design for multivariable predictive control utiliz-
ing range control. US Patent No 5.572.420,
[54]
Krishnan A, Kosanovich K, DeWitt M, Creec M (1998) Robust model predictive control
of an industrial solid phase polymerizer. Proceedings of the American Control Conference,
Philadelphia (USA)
[55]
Mathur A, Parthasarathy S, Gaikwad S (1999). Hybrid neural network multivariable predic-
tive controller for handling abnormal events in processing applications. Proceedings of the
1999 IEEE International Conference on Control Applications, Hawai (USA)
[56]
Invensys, www.invensys.com
[57]
Nix A, Morrow A, Gordon L (2000). Using multivariable predictive control to optimize
the Asarco Mission mill. In J. A. Hebst (Ed.), Proceedings of Control 2000, SME Annual
Meeting, Littleton (USA), 201-207
[58]
Mintek, www.mintek.com
[59]
Craig L, Henning R (2000) Evaluation of advanced industrial control projects: a framework
for determining economic benefits. Control Engineering Practice 8: 769-780
[60]
Roseman L., Schubert J, Jart J, Carew W (2001) Plantstar 2000: a plant - wide control
platform for mineral processing, Minerals Engineering 14: 593-600
[61]
SGS, www.sgs.com
[62]
Gensym, www.gensym.com
[63]
Keaton M, Wood M, Schaffer M (2002) Application at Ok Tedi Mining of a neural
network model within the expert system for SAG mill control. SGS Internal Report,
www.met.sgs.com
[64]
Cipriano A, Gonzalez G, Sbarbaro D (2007) Final Report Project Amira P893A, Training in
Automation for optimizing the profitability of technological investments