Prof. Ali Mesbah
Department of Chemical and Biomolecular Engineering
University of California Berkeley
Tuesday 2019-07-16 16:00
IST-Seminar-Room V2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen Room V2.255 -
Plasma medicine hinges on local generation and delivery of a variety of therapeutic agents including electric fields, reactive chemical species, and thermal effects. With an increasing number of clinically approved atmospheric-pressure plasma devices, there is growing evidence for the effectiveness of plasma medicine in alternative and complementary therapies such as reduction of head and neck cancer and accelerated healing of chronic wounds. However, safe and effective operation of hand-held atmospheric-pressure plasma devices is highly sensitive to the intrinsic variability of plasma characteristics as well as to exogenous disturbances such as variations in the physical and chemical properties of a target substrate. Key challenges in feedback control of these plasma devices arise from the need to: (i) handle the nonlinear, multivariable nature of plasma dynamics, (ii) retain the system operation in a constrained region for safe and reliable operation, and (iii) realize multiple (possibly conflicting) plasma dose delivery objectives. In this talk, we will demonstrate the importance of using predictive control strategies for safe, reproducible, and therapeutically effective application of atmospheric-pressure plasma jets for thermal dose delivery in plasma medicine.
Ali Mesbah is Assistant Professor of Chemical and Biomolecular Engineering at the University of California at Berkeley. Before joining UC Berkeley, he was a senior postdoctoral associate at MIT. He holds a Ph.D. degree in systems and control from Delft University of Technology. He is a senior member of the IEEE Control Systems Society and AIChE. He is on the IEEE Control Systems Society conference editorial board as well as the editorial board of IEEE Transactions on Radiation and Plasma Medical Sciences and Journal of Optimal Control Applications and Methods. He is the recipient of the AIChE's 35 Under 35 Award in 2017, the IEEE Control Systems Outstanding Paper Award in 2017, and the AIChE CAST W. David Smith, Jr. Graduation Publication Award in 2015. His research interests are in the areas of optimization-based systems analysis, fault diagnosis, and predictive control of uncertain systems