Rapid development of technology is quickly leading us to an increasingly networked and wireless world. With massive wireless networks on the horizon, the efficient coordination of such large networks becomes an important consideration. To efficiently use the available resources, it is desirable to limit wireless communication to only the instances when the individual subsystems actually need attention. Unfortunately, classical time-triggered control systems are based on performing sensing, actuation, and even communication actions periodically in time rather than when it is necessary. This motivates the need to transcend this prevailing paradigm in exchange for event-triggered control (ETC); where individual subsystems must decide for themselves when to take different actions based on local information. The concept of ETC has been proposed as early as the 1960's and re-popularized around 1999 by a few researchers including UCSB emeritus faculty Karl Astrom. Since then, the idea of ETC has been surging in popularity to now essentially stand alone in the area of systems and control. This then begs the question: why is ETC not yet more mainstream and why has industry still not adopted it in most actual control systems? In this talk we look at this question and argue that the majority of ETC algorithms being proposed today are too theoretical to be useful. We then show how we are addressing this problem by developing a standard set of tools and methodologies for co-designing efficient event-triggered communication and control algorithms for networked systems that can actually be used by practitioners; with quantifiable benefits, performance guarantees, and robustness properties. This talk identifies numerous shortcomings between theoretical concepts and what is actually needed in practice for the theory to be useful, and discusses how we might close this gap. Finally, this talk will cover specific challenges we encountered in applying the state of-the-art event-triggered control algorithms to a wireless clock synchronization problem, and how we overcame them.
Cameron Nowzari received the B.S. in Merchanical Engineering from UCSB in 2009 and the Ph.D. in Mechanical Engineering from UCSD in 2013. He then held a postdoctoral position with the Electrical and Systems Engineering Department at the University of Pennsylvania until 2016. He is currently an Assistant Professor with the Electrical and Computer Engineering Department at George Mason University, in Fairfax, Virginia. He has received numerous awards including the American Automatic Control Council’s O. Hugo Schuck Best Paper Award, the IEEE Control Systems Magazine Outstanding Paper Award, and the International Conference on Data Mining Best Paper Award. His current research interests include dynamical systems and control, distributed coordination algorithms, robotics, event- and self-triggered control, Markov processes, network science, spreading processes on networks, and the Internet of Things.
