Improving the performance of distributed model predictive control by applying graph partitioning methods

Burk D, Völz A, Graichen K (2022)

Publication Type: Conference contribution

Publication year: 2022

Event location: Sinaia (Romania)

DOI: 10.1109/icstcc55426.2022.9931785

Authors with CRIS profile

Daniel Burk Chair of Automatic Control Andreas Völz Chair of Automatic Control Knut Graichen Chair of Automatic Control

Related research project(s)

Modular distributed model predictive control of nonlinear systems with neighborhood models April 1, 2019 - Dec. 31, 2020

How to cite

APA:

Burk, D., Völz, A., & Graichen, K. (2022). Improving the performance of distributed model predictive control by applying graph partitioning methods. In Proceedings of the 26th International Conference on System Theory, Control and Computing (ICSTCC). Sinaia (Romania).

MLA:

Burk, Daniel, Andreas Völz, and Knut Graichen. "Improving the performance of distributed model predictive control by applying graph partitioning methods." Proceedings of the 26th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia (Romania) 2022.

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