Distributed Average Tracking in Multi-agent Networks

October 17, 2014, Webb 1100

Wei Ren

UC Riverside, Electrical Engineering


In this talk, we introduce a distributed average tracking problem and present distributed discontinuous control algorithms to solve the problem. The idea of distributed average tracking is that multiple agents track the average of multiple time-varying reference signals in a distributed manner based only on local information and local communication with adjacent neighbors. We study the cases where the time-varying reference signals have bounded derivatives and accelerations. We also use the distributed average tracking idea to solve a continuous-time distributed convex optimization problem. Tools from nonsmooth analysis are used to analyze the stability of the systems. Simulation examples are presented to show the validity of the theoretical results.

Speaker's Bio

Wei Ren is currently a Professor with the Department of Electrical and Computer Engineering, University of California, Riverside. He received the Ph.D. degree in Electrical Engineering from Brigham Young University, Provo, UT, in 2004. From 2004 to 2005, he was a Postdoctoral Research Associate with the Department of Aerospace Engineering, University of Maryland, College Park. He was an Assistant Professor (2005-2010) and an Associate Professor (2010-2011) with the Department of Electrical and Computer Engineering, Utah State University. His research focuses on distributed control of multi-agent systems and autonomous control of unmanned vehicles. Dr. Ren is an author of two books Distributed Coordination of Multi-agent Networks (Springer-Verlag, 2011) and Distributed Consensus in Multi-vehicle Cooperative Control (Springer-Verlag, 2008). He was a recipient of the National Science Foundation CAREER Award in 2008. He is currently an Associate Editor for Automatica, Systems and Control Letters, and IEEE Transactions on Control of Network Systems.