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near-optimal_sparse_sensor_and_actuator_selection [2018/03/17 21:17] (current)
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 +Title: Near-Optimal Sparse Sensor and Actuator Selection
 +In this talk, I present our recent efforts in developing rigorous approaches to sparse sensor and actuator selection in large-scale linear dynamical systems. While sparse sensor and actuator selection is known to be NP-Hard, using tools from optimal experiment design and submodular optimization,​ we develop a framework for near- optimal sensor and actuator selection with provable approximation guarantees using greedy algorithms. We then extend these results to develop a robust variant of the approximations themes, where the optimization of sensor selection is performed in presence of an adversary who can cause a subset of sensors to fail. Next, using recent developments in graph sparsification and column selection ​ literature, we show how to select a sparse subset of sensors or actuators while guaranteeing performance with respect to the fully sensed or actuated system (and not the optimal sparse one). As a corollary we show  that by utilizing a time varying sense or actuator selection schedule, one can guarantee near-optimal ​ sensing/​control performance by selecting a dimension-independent (constant) number of sensors or actuators. Joint work with Vassilis Tzoumas (Penn), Milad Siami(MIT), and Alex Olshevsky (BU)
 +Ali Jadbabaie is the JR East Professor of Engineering and Associate Director of the Institute for Data, Systems and Society at MIT, where he is also on the faculty of the department of civil and environmental engineering and  a principal investigator in the Laboratory for Information and Decision Systems (LIDS), and the director of the Sociotechnical Systems Research Center, one of MIT’s 13 research laboratories. He received his Bachelors (with high honors) from Sharif University of Technology in Tehran, Iran, a Masters degree in electrical and computer engineering from the University of New Mexico, and his PhD in control and dynamical systems from the California Institute of Technology. He was a postdoctoral scholar at Yale University before joining the faculty at Penn in July 2002 where he was the Alfred Fitler Moore a Professor of Network Science. He was the inaugural editor-in-chief of IEEE Transactions on Network Science and Engineering,​ a new interdisciplinary journal sponsored by several IEEE societies. He is a recipient of a National Science Foundation Career Award, an Office of Naval Research Young Investigator Award, the O. Hugo Schuck Best Paper Award from the American Automatic Control Council, and the George S. Axelby Best Paper Award from the IEEE Control Systems Society. His students have been winners and finalists of student best paper awards at various ACC and CDC conferences. He is an IEEE fellow and a recipient of the 2016 Vannevar Bush Fellowship from the office of Secretary of Defense, and a member of the National Academies of Science, Engineering,​ and Medicine’s Intelligence Science and Technology Expert Group (ISTEG). His current research interests are in distributed decision making and optimization, ​ multi-agent coordination and control, network science, and network economics.
near-optimal_sparse_sensor_and_actuator_selection.txt · Last modified: 2018/03/17 21:17 by ashutosh_nayyar