
Speaker: Venkatraman Renganathan, Cranfield University
Title: Probabilistically Robust Decision Making for Uncertain Dynamical Systems
Abstract: 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.
Bio: Venkatraman Renganathan is currently working as a lecturer at Cranfield University in the UK. Previously, he was a postdoctoral research fellow at the Department of Automatic Control in Lund University, Sweden. He completed his PhD in Mechanical Engineering on 2021 from the University of Texas at Dallas, USA. He finished his MS in Electrical Engineering on 2016 from the Arizona State University, USA, and his Bachelor’s degree in Electrical & Electronics Engineering in 2011 from Anna University in India. His research interests include probabilistic robust control, risk bounded motion planning and control of uncertain networked systems.
We strongly encourage you to attend the seminar in person.
You can also connect via Zoom: https://newnham.zoom.us/j/92544958528?pwd=YS9PcGRnbXBOcStBdStNb3E0SHN1UT09