Abstract
The benefits of parametric programming for the design of optimal controllers for constrained systems are widely acknowledged, especially for the case of linear systems. In this work we attempt to exploit these benefits and further extend the theoretical contributions to multi-parametric Model Predictive Control (mp-MPC) for non-linear systems with state and input constraints. The aim is to provide an insight and understanding of multi-parametric control and its benefits for non-linear systems and outline key issues for ongoing research work.
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Sakizlis, V., Kouramas, K.I., Faisca, N.P., Pistikopoulos, E.N. (2007). Towards the Design of Parametric Model Predictive Controllers for Non-linear Constrained Systems. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_15
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DOI: https://doi.org/10.1007/978-3-540-72699-9_15
Publisher Name: Springer, Berlin, Heidelberg
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