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Regret and Conservatism of Constrained Stochastic Model Predictive Control

Pfefferkorn, Maik ; Renganathan, Venkatraman LU and Findeisen, Rolf (2024)
Abstract
We analyse conservatism and regret of stochastic model predictive control (SMPC) when using moment-based ambiguity sets for modeling unknown uncertainties. To quantify the conservatism, we compare the deterministic constraint tightening while taking a distributionally robust approach against the optimal tightening when the exact distributions of the stochastic uncertainties are known. Furthermore, we quantify the regret by comparing the performance when the distributions of the stochastic uncertainties are known and unknown. Analysing the accumulated sub-optimality of SMPC due to the lack of knowledge about the true distributions of the uncertainties marks the novel contribution of this work.
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author
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publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
in press
subject
host publication
Regret and Conservatism of Constrained Stochastic Model Predictive Control
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
project
Scalable Control of Interconnected Systems
language
English
LU publication?
yes
id
8cbb4cd8-74d5-4168-af96-ad526c7d4e14
date added to LUP
2024-02-22 12:00:07
date last changed
2024-02-26 10:35:35
@inproceedings{8cbb4cd8-74d5-4168-af96-ad526c7d4e14,
  abstract     = {{We analyse conservatism and regret of stochastic model predictive control (SMPC) when using moment-based ambiguity sets for modeling unknown uncertainties. To quantify the conservatism, we compare the deterministic constraint tightening while taking a distributionally robust approach against the optimal tightening when the exact distributions of the stochastic uncertainties are known. Furthermore, we quantify the regret by comparing the performance when the distributions of the stochastic uncertainties are known and unknown. Analysing the accumulated sub-optimality of SMPC due to the lack of knowledge about the true distributions of the uncertainties marks the novel contribution of this work.}},
  author       = {{Pfefferkorn, Maik and Renganathan, Venkatraman and Findeisen, Rolf}},
  booktitle    = {{Regret and Conservatism of Constrained Stochastic Model Predictive Control}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Regret and Conservatism of Constrained Stochastic Model Predictive Control}},
  year         = {{2024}},
}