<div class="csl-bib-body">
<div class="csl-entry">Angelov, G., Dominguez Corella, A., & Veliov, V. M. (2022). On the Accuracy of the Model Predictive Control Method. <i>SIAM Journal on Control and Optimization</i>, <i>60</i>(4), 2469–2487. https://doi.org/10.1137/21M1460430</div>
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dc.identifier.issn
0363-0129
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/136047
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dc.description.abstract
The paper investigates the accuracy of the model predictive control (MPC) method for finding on-line approximate optimal feedback control for Bolza-type problems on a fixed finite horizon. The predictions for the dynamics, the state measurements, and the solution of the auxiliary open-loop control problems that appear at every step of the MPC method may be inaccurate. The main result provides an error estimate of the MPC-generated solution compared with the optimal open-loop solution of the “ideal” problem, where all predictions and measurements are exact. The technique of proving the estimate involves an extension of the notion of strong metric subregularity of set-valued maps and utilization of a specific new metric in the control space, which makes the proof nonstandard. The result is specialized for two problem classes: coercive problems and affine problems.
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dc.description.sponsorship
Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
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dc.language.iso
en
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dc.publisher
SIAM PUBLICATIONS
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dc.relation.ispartof
SIAM Journal on Control and Optimization
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dc.subject
Lagrange problem
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dc.subject
metric subregularity
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dc.subject
model predictive control
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dc.subject
optimal control
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dc.title
On the Accuracy of the Model Predictive Control Method