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DTSTART:19700329T020000
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DTSTAMP:20250926T124354
UID:b29cf1e7-9ac5-11f0-bc3b-000e0c3db68b
SUMMARY:Talk of Prof. Mark Cannon
DESCRIPTION:Abstract\nThis talk will describe a novel approach for computationally tractable, data-driven,\noptimisation-based control for applications in which safety is critical. Starting with a brief\nintroduction to the main concepts and challenges, the discussion will motivate recent work on Model\nPredictive Control (MPC) and the convex-concave procedure for finding locally optimal solutions of\nnonconvex problems. We will consider how to use differences of convex (DC) functions to derive\nconvex conditions that allow control system performance to be optimized as a sequence of convex\nsub-problems.\nUsing sequences of sets (tubes) to bound predicted trajectory, the method provides guaranteed\nrobustness to uncertainty, and it allows warm-starting and early-termination at feasible suboptimal\nsolutions. Key properties and theoretical results, including feasibility, convergence, optimality\nand closed loop stability will be discussed. The talk will explain how DC representations can be\ncomputed directly from data and how model estimation can be performed online simultaneously with\ncontrol to define safe learning-based control algorithms. We will discuss data-driven techniques\nusing neural networks, machine learning and sum-of-squares polynomials to obtain systematic DC\ndecompositions of nonlinear system dynamics.\nWe will discuss three diverse applications of these techniques: transitioning tiltwing aircraft\nbetween vertical and horizontal filght, controlling batch-fed bioreactors, and deep brain\nstimulation.  \nBiographical Information\nI studied engineering as an undergraduate (MEng in Engineering Science) and completed a\ndoctorate (DPhil) at the University of Oxford, graduating in 1993 and 1998. Between these I did a\nmaster’s degree (SM) at Massachusetts Institute of Technology, graduating in 1995. Since 2002 I\nhave been with the Engineering Science Department and a Fellow of St John’s College. I am Professor\nof Engineering Science a member of the Oxford Control Group. My research is about designing\nfeedback controllers for uncertain systems in order to optimize performance subject to constraints.\nI am interested in the fundamental properties of optmization-based control strategies such as\nfeasibility and closed-loop stability, as well as issues such as convexity and efficiency of\ncomputation, stochastic uncertainty and online model adaptation. Current and past applications I\nhave considered include power management in EVs and hybrid electric aircraft, trajectory\noptimization in VTOL aircraft, deep brain stimulation (DBS) in medical applications, and bioprocess\ncontrol.\n\n\n\n\n  
DTSTART;TZID=Europe/Berlin:20251009T160000
DTEND;TZID=Europe/Berlin:19700101T010000
LOCATION:Institute for Systems Theory and Automatic Control, , Seminar room 2.255, Pfaffenwaldring 9, 70569  Stuttgart, Campus Vaihingen 
URL;VALUE=URI:https://www.ist.uni-stuttgart.de/events/Talk-of-Prof.-Mark-Cannon/
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