Disturbance modeling and state estimation for offset-free predictive control with state-space process models
By: Piotr Tatjewski
References
- Anderson, D. and Moore, J. (2005)., Dover Publications Inc, New York, NY.
- Astrom, K. and Wittenmark, B. (1997)., Prentice Hall, Upper Saddle River, NJ.
- Blevins, T.L., McMillan, G.K., Wojsznis, W.K. and Brown, M.W. (2003)., The ISA Society, Research Triangle Park, NC.
- Blevins, T.L., Wojsznis, W.K. and Nixon, M. (2013)., The ISA Society, Research Triangle Park, NC.
- Camacho, E. and Bordons, C. (1999)., Springer Verlag, London.
- Doyle III, F., Ogunnaike, B. and Pearson, R. (1996). Nonlinear model predictive control of a simulated multivariable polymerization reactor using second-order Volterra models,32(9): 1285–1301.
- Gonzalez, A.H., Adam, E.J. and Marchetti, J.L. (2008). Conditions for offset elimination in state space receding horizon controllers: A tutorial analysis,47(12): 2184–2194.
- Hesketh, T. (1982). State-space pole-placing self-tuning regulator using input-output values,129(4): 123–128.
- Ławry´nczuk, M. (2009). Efficient nonlinear predictive control based on structured neural models,19(2): 233–246, DOI: 10.2478/v10006-009-0019-1.
- Ławry´nczuk, M. and Tatjewski, P. (2010). Nonlinear predictive control based on neural multi-models,20(1): 7–21, DOI: 10.2478/v10006-010-0001-y.
- Maciejowski, J. (2002)., Prentice Hall, Harlow.
- Maeder, U. and Morari, M. (2010). Offset-free reference tracking with model predictive control,46(9): 1469–1476.
- Morari, M. and Maeder, U. (2012). Nonlinear offset-free model predictive control,48(9): 2059–2067.
- Muske, K. and Badgwell, T. (2002). Disturbance modeling for offset-free linear model predictive control,12(5): 617–632.
- Pannocchia, G. and Bemporad, A. (2007). Combined design of disturbance model and observer for offset-free model predictive control,52(6): 1048–1053.
- Pannocchia, G. and Rawlings, J. (2003). Disturbance models for offset-free model predictive control,49(2): 426–437.
- Prett, D. and Garcia, C. (1988)., Butterworths, Boston, MA.
- Qin, S. and Badgwell, T. (2003). A survey of industrial model predictive control technology,11(7): 733–764.
- Rao, V. and Rawlings, J.B. (2009)., Nob Hill Publishing, Madison, WI.
- Rossiter, J. (2003)., CRC Press, Boca Raton, FL.
- Tatjewski, P. (2007)., Springer Verlag, London.
- Tatjewski, P. (2008). Advanced control and on-line process optimization in multilayer structures,32(1): 71–85.
- Tatjewski, P. (2010). Supervisory predictive control and on-line set-point optimization,20(3): 483–495, DOI: 10.2478/v10006-010-0035-1.
- Tatjewski, P. (2011). Disturbance modeling and state estimation for predictive control with different state-space process models,, pp. 5326–5331.
- Tatjewski, P. (2012). Modeling deterministic disturbances and state filtering in model predictive control with state-space models,M. Busłowicz and K. Malinowski (Eds.),, OWPB, Białystok, pp. 263–274.
- Tatjewski, P. and Ławry´nczuk, M. (2006). Soft computing in model-based predictive control,16(1): 7–26.
- Wang, L. (2009). Model Predictive Control System Design and Implementation Using MATLAB, Springer Verlag, London.
Language: English
Page range: 313 - 323
Submitted on: Sep 27, 2013
Published on: Jun 26, 2014
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
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© 2014 Piotr Tatjewski, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.