Dr. Maziar Hemati

Biological flyers and swimmers have a great capacity for interacting with their fluid environments. This ability is demonstrated through the agility, efficiency, and environmental awareness exhibited by numerous creatures, including birds, fish, and insects. While human-engineered systems have benefited from biological in­spiration, the performance gains realized have often fallen short of their full po­tential. A primary limitation to attaining further improvement has been a scarcity of reliable low-dimensional fluid dynamics models, which are often needed (1) to determine the state of a complex flow from available on-board sensors (i.e., flow sensing), and (2) to exploit that knowledge to determine and execute a best course of action for achieving a desired objective (i.e., feedback control). In this talk, I will introduce modal strategies aimed at obtaining reliable dynamical sys­tems models-suitable for real-time fluid flow sensing and control-from empiri­cal data. In particular, I will present recent advances in techniques tailored to ex­tract descriptive insights and predictive models from large, streaming, and noisy datasets. In the second half of the talk, I will present a dynamic mode shaping perspective for feedback flow control synthesis. I will then use this perspective to highlight a fundamental performance limitation inherent to standard observer­based control structures, suggesting that flow reconstruction from sensor meas­urements is not necessarily advisable in all feedback control applications. 

Maziar Hemati is an Assistant Professor in the Department of Aerospace Engi­neering and Mechanics at the University of Minnesota, Twin Cities. Dr. Hemati's research program is aimed at gaining an improved understanding of the various mechanisms required to achieve reliable fluid flow sensing and control in the con­text of human-engineered systems, including flight vehicles, robotic swimmers, and wind turbine arrays. Prior to joining the faculty at the University of Minnesota, Dr. Hemati served as a Post-Doctoral Research Associate in the Department of Mechanical and Aerospace Engineering at Princeton University. He earned his PhD and MS in Mechanical Engineering and his BS in Aerospace Engineering, all from UCLA.