Model Predictive Control for Tracking (MPCT) is an advanced control strategy that allows to change the reference point without losing feasibility. Furthermore, the formulation of the MPCT allows to enlarge the domain of attraction conceding it higher controllability. These advantages make it a strategy with wide variety of applications. The goal of this work is to give a comparison between the existing formulations of Robust MPCT and stochastic MPCT. An illustrative example shows the properties of theses controllers.
(2018). Robust and Stochastic MPC for tracking: a performance comparison . Retrieved from http://hdl.handle.net/10446/169392
Robust and Stochastic MPC for tracking: a performance comparison
Ferramosca, Antonio
2018-01-01
Abstract
Model Predictive Control for Tracking (MPCT) is an advanced control strategy that allows to change the reference point without losing feasibility. Furthermore, the formulation of the MPCT allows to enlarge the domain of attraction conceding it higher controllability. These advantages make it a strategy with wide variety of applications. The goal of this work is to give a comparison between the existing formulations of Robust MPCT and stochastic MPCT. An illustrative example shows the properties of theses controllers.| File | Dimensione del file | Formato | |
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