Active set updates in event-triggered networked MPC

Berner, Patrik Simon; König, Kai; Kvasnica, Michal; Mönnigmann, Martin

doi:10.23919/ecc.2019.8796297

Cited by 2 publications

(1 citation statement)

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“…Finally, future work must combine the proposed approach with methods for predicting the sequence of affine laws along the closed-loop trajectory [4]. This will help reducing the number of optimal control problems further in particular far from the origin, where the affine laws are not reused frequently.…”

Section: Discussionmentioning

confidence: 99%

A Complexity Analysis of Event-Triggered Model Predictive Control on Industrial Hardware

Berner

Mönnigmann

2020

IEEE Trans. Contr. Syst. Technol.

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We implement a recently proposed event-triggered networked MPC approach on industrial hardware to analyze its practical relevance. There exist several alternatives for such an implementation that differ with respect to the distribution of computational load between local and central nodes, and with respect to network bandwidth requirements. These alternatives have been analyzed theoretically before, but when implemented it becomes evident that their usefulness cannot be predicted based on theoretical considerations alone. It is the purpose of the present paper to account for both practical and theoretical aspects in determining which alternative is most appropriate for an implementation on industrial hardware. The smallest possible bandwidth is known to result for a variant in which only the active set of constraints is transmitted from the central to the local nodes. Since local nodes must determine the control law from the active set in this case, which requires matrix inversions, an unattractive computational cost results at first sight. Somewhat surprisingly, the computational cost scales practically linearly in the problem size when implemented. We confirm this result with a more detailed theoretical complexity analysis than given in previous papers. All results are illustrated with data obtained with an implementation on industrial hardware components.

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Section: Discussionmentioning

confidence: 99%