Abstract: The time-driven paradigm for modeling, sampling, estimation, control, and optimization is based on centuries of theoretical underpinnings and was further promoted by the digital technological advances of the 1970s. In a world increasingly networked, wireless, and consisting of large-scale distributed systems, the universal value of this paradigm has understandably come to question. For example, time-driven sampling and communication with energy-constrained wireless devices can be inefficient, unnecessary, and sometimes infeasible. The event-driven paradigm offers an alternative complementary look at control and optimization. The key idea is that a “clock” should not be dictating actions simply because a time step is taken; rather, an action should be triggered by an “event” which may be a well-defined condition on the system state (including a simple time step) or a random state transition.
We will discuss two areas where event-driven control and optimization have been well-developed and justify the research activity recently seen in the systems and control community in this direction. First, in distributed systems, we will show how event-driven, rather than synchronous, communication can guarantee convergence in cooperative distributed optimization while provably maintaining optimality. Second, when modeling stochastic systems with complex dynamics, systematic abstraction methods can generate hybrid models where well-defined events decompose system operation into discrete states. This facilitates the use of analytical tools which are robust with respect to modeling details which can, therefore, be safely omitted. A case in point is the use of gradient estimation techniques which boil down to a set of Infinitesimal Perturbation Analysis equations (an “IPA calculus”). We will illustrate how this IPA calculus is used to solve a large class of stochastic optimization problems.
Parking in Boston can be a grueling experience, but Christos Cassandras envisions a way to make it almost effortless: Have the city itself sense when spaces are opening up, and guide drivers to the most efficient spot. The engineering professor at Boston University and his students have already piloted a “smart parking” system in a garage at the school, which uses a smartphone app and software that finds the optimal spot for each driver and tells drivers exactly where to go. “Everybody wins,” he says. “Less time wasted, less fuel consumed, less pollution.”
Cassandras’s scheme is just one step in the march toward what futurists and urban planners call the “smart city”—a wired, sensor-filled streetscape that uses cloud computing and sophisticated software to transform cities into intelligent machines that adapt to people’s lives and steer behavior. Smart city advocates envision a future in which tech-savvy cities offer better civic services, move us faster through traffic, reduce waste and greenhouse gas emissions, and gather so much data that the complexities of urban life can be understood and smoothly managed.
Boston Globe, May 19, 2013
In this issue of IEEE Control Systems Magazine (CSM) we speak with Christos
Cassandras, 2012 IEEE Control Systems Society (CSS) president. Christos is
head of the Division of Systems Engineering and professor of electrical and computer
engineering at Boston University. He served as editor-in-chief of IEEE Transactions
on Automatic Control from 1998 through 2010, and he has held numerous
positions in CSS. He is the author of over 300 refereed papers and fi ve books, and
he is the recipient of several awards including, most recently, the 2011 IEEE Control
Systems Technology Award.
Control Systems Magazine, December 2011
IEEE-USA Today’s Engineer, November 2011
NECN, September 23, 2011
CHRISTOS G. CASSANDRAS
Distinguished Professor of Engineering
Head, Division of Systems Engineering
Professor of Electrical and Computer Engineering
15 St. Mary’s St., Boston University
Brookline, MA 02446
Tel. (617) 353-7154 Fax: (617) 353-4830
425 Photonics Building, 8 St. Mary’s St.