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Efficient stochastic model predictive control for embedded systems based on second-order cone programs

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Kögel,  Markus
Otto-von-Guericke-Universität Magdeburg, External Organizations;
International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Zometa, P., Heinemann, H., Lucia, S., Kögel, M., & Findeisen, R. (2016). Efficient stochastic model predictive control for embedded systems based on second-order cone programs. In European Control Conference (ECC) 2016 (pp. 166-171).


Cite as: https://hdl.handle.net/21.11116/0000-0000-F21C-0
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