Abstract
An augmented state space formulation for multiple model predictive control (MMPC) is developed to improve the regulation of nonlinear and uncertain process systems. By augmenting disturbances as states that are estimated using a Kalman filter, improved disturbance rejection is achieved compared to an additive output disturbance assumption. The approach is applied to a Van de Vusse reactor example, which has challenging dynamic behavior in the form of a right half plane zero and input multiplicity.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Athans, M., Castanon, D., Dunn, K., Greene, C., Lee, W., Sandell, N., Willsky, A.: The stochastic control of the F-8C aircraft using a multiple model adaptive control method. IEEE Trans. Auto Cont. 22, 768–780 (1977)
Muske, K., Badgwell, T.: Disturbance modeling for offset-free linear model predictive control. J. Process Control 12, 617–632 (2002)
Sistu, P., Bequette, B.W.: Model predictive control of processes with input multiplicities. Chem. Eng. Sci. 50, 921–936 (1995)
Bequette, B.W.: Process Control: Modeling, Design and Simulation. Prentice Hall, Upper Saddle River (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Kuure-Kinsey, M., Bequette, B.W. (2009). Multiple Model Predictive Control of Nonlinear Systems. In: Magni, L., Raimondo, D.M., Allgöwer, F. (eds) Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01094-1_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-01094-1_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01093-4
Online ISBN: 978-3-642-01094-1
eBook Packages: EngineeringEngineering (R0)