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Dal'nevostochnyi Matematicheskii Zhurnal, 2022, Volume 22, Number 2, Pages 152–157
DOI: https://doi.org/10.47910/FEMJ202216
(Mi dvmg479)
 

Model predictive control of dynamic systems with mixed uncertainty and its application to supply chain management

E. V. Chausova

Tomsk State University
References:
Abstract: The paper is devoted to a discrete-time linear system with constraints on states and control inputs under conditions of interval and stochastic uncertainty. We use the model predictive control approach and get the optimal control strategy that brings the system to a setpoint. The developed results are applied to the inventory control problem in a supply chain. A numerical example is studied.
Key words: linear dynamic system, model predictive control, interval-stochastic uncertainty, interval analysis, multi-objective optimization, quadratic programming, inventory control, supply chain.
Received: 24.06.2022
Bibliographic databases:
Document Type: Article
UDC: 517.977.55
MSC: 93C95
Language: English
Citation: E. V. Chausova, “Model predictive control of dynamic systems with mixed uncertainty and its application to supply chain management”, Dal'nevost. Mat. Zh., 22:2 (2022), 152–157
Citation in format AMSBIB
\Bibitem{Cha22}
\by E.~V.~Chausova
\paper Model predictive control of dynamic systems with mixed uncertainty and its application to supply chain management
\jour Dal'nevost. Mat. Zh.
\yr 2022
\vol 22
\issue 2
\pages 152--157
\mathnet{http://mi.mathnet.ru/dvmg479}
\crossref{https://doi.org/10.47910/FEMJ202216}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=4529950}
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