Probabilistically Robust Decision Making for Uncertain Dynamical Systems

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• Venkatraman Renganathan, Cranfield University
• Thursday 12 June 2025, 14:00-15:00
• JDB Seminar Room, Department of Engineering and online (Zoom).

If you have a question about this talk, please contact Fulvio Forni.

Typically, how much do we know about an uncertain dynamical system (UDS) matters a lot when we want to control them. Aiming to accurately capture the evolution of such UDS is impossible as true system uncertainties cannot be captured exactly. Lack of exact system knowledge increases the difficulty in estimating the limits of the uncertain system’s performance. As a result, we often seek to control such UDS such that the resulting control decisions from Robust Decision Making (RDM) paradigms render the UDS insensitive to what we don’t know about them. However, nature can violate the assumptions that the RDM module assume for the system uncertainties with small probability. Controlling UDS under such unforeseen events necessitate the addition of probabilistic rigour on top of the existing RDM approaches. In this talk, I shall propose a Probabilistic RDM (PRDM) approach using the uncertain gap between the dynamical system models (with and without the uncertainty) induced by appropriate distance metric. The proposed framework will allow us to analyse the potential performance degradation of a control action on an UDS when such rare violation events occur. The fertile nature of the probabilistic robust control research area will be highlighted using a list of interesting future research directions.

The seminar will be held in JDB Seminar Room, Department of Engineering, and online (zoom): https://newnham.zoom.us/j/92544958528?pwd=YS9PcGRnbXBOcStBdStNb3E0SHN1UT09

This talk is part of the CUED Control Group Seminars series.

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