2022
- Constraint Violation Probability Minimization for Norm-Constrained Linear Model Predictive Control. 2022 European Control Conference (ECC), 2022, 839-846 more… Full text ( DOI )
Technical University of Munich
Chair of Automatic Control Engineering (Prof. Buss)
Postal:
Theresienstr. 90
80333 München
Chair of Automatic Control Engineering (Prof. Buss)
Work:
Theresienstr. 90(0105)/II
80333 München
Since Nov. 2020 | Research Assistant |
2018-2020 | Master of Science, Electrical Engineering and Information Technology Focus: Automation and Robotics Technical University Munich, Germany (TUM) |
2014-2018 | Bachelor of Engineering, Electrical Engineering and Information Technology University of Applied Sciences Landshut, Germany |
System uncertainty can be handled in different ways within MPC. Robust MPC, as the name indicates, robustly accounts for the uncertainty, often resulting in conservative solutions. While Stochastic MPC yields efficient solutions, a small probability of constraint violation is permitted, based on a predefined risk parameter.
In contrast to Robust MPC and Stochastic MPC, we propose an MPC method (CVPM-MPC), which minimizes the probability that a constraint is violated while also optimizing other control objectives. The proposed method is capable of dealing with changing uncertainty and does not require to choose a risk parameter. CVPM-MPC can be reagarded as a link between Robust and Stochastic MPC.
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