Linda Bushnell

Linda Bushnell Headshot Photo
First Name: 
Linda
Last Name: 
Bushnell

Linda Bushnell is a Research Associate Professor and Director of the Networked Control Systems Lab at the Electrical Engineering Department of the University of Washington. She received her Ph.D. in EE from UC Berkeley in 1994, her M.A. in Mathematics from UC Berkeley in 1989, her M.S. in EE from UConn in 1987, and her B.S. in EE from UConn in 1985. She also received her MBA from the University of Washington Foster School of Business in 2010. Her research interests include networked control systems, control of complex networks, and secure-control.She is a recipient of the US Government Superior Civilian Service Award, NSF ADVANCE Fellowship, and IEEE Control Systems Society (CSS) Recognition Award. She was the Co-Editor of a special issue of the Asian Journal of Control and Guest Editor for three issues of the Control Systems Magazine. She has been the Organizer/Co-Organizer of four invited/special sessions. She is a Senior Member of the IEEE (1999), and has been a member of the IEEE since 1985, a member of the IEEE CSS since 1990, and a member of the IEEE Women in Engineering since 2013. For IEEE CSS, she is a Distinguished Lecturer, a member of the Women in Control Committee, a member of the TC Control Education, a member of the History Committee, Liaison to IEEE Women in Engineering, a 2014 Appointed Member to the Board of Governors, and a Member of the Board of Governors for 2015 - 2017. She was the Secretary-Administrator and Member of the Executive Committee from 2001 – 2007, Member of the Board of Governors 1999 – 2007, Associate Editor of the IEEE CSM 1999 – 2002, Vice-Chair for Invited Sessions for 2001 CCA, Chairperson of the History Standing Committee 1997 – 2000, and Vice-Chair for Invited Sessions for 2000 CDC. For the American Automatic Control Council (AACC), she is currently the Treasurer of the AACC and a Member of the Technical Committee on Control Education. She was the Workshop Chair for 2013 ACC, Technical Program Chair for 2007 ACC, Publicity Chair for 2005 ACC, Vice-Chair for Publications for 1999 ACC, and Vice-Chair for Invited Sessions for 1998 ACC. For the Association for Computing Machinery (ACM), she is the General Co-Chair for the Conference on High Confidence Networked Systems (HiCoNS) at CPSWeek 2014, and was the Technical Program Co-Chair for the HiCoNS at CPSWeek 2013. She has been a member of multipleTechnical Program Committees for the CDC, ACC, HiCoNS, and ISIC conferences.

www.ee.washington.edu/people/faculty/bushnell/

Contact Information
Email: 
LB2@uw.edu
Telephone: 
206-221-6717
Fax: 
206-543-3842
Affiliation: 
University of Washington
Position: 
CSS Board of Governors, term ending 31 December 2017 (elected); Distinguished Lecturer; Women in Control Committee Chair

Location

185 NE Stevens Way
Seattle 98195-2500
United States

Distinguished Lecture Program

Talk Title: Leader Title: Leader Selection for Performance and Control of Complex Networks

Control of complex networks, including unmanned vehicle networks, social networks, and biological systems, is an ever-growing challenge.  A standard approach is to directly control a subset of leader nodes, which then influence the remaining (follower) nodes.  While the choice of leader nodes is known to impact the performance, controllability, and security of complex networks, efficient algorithms for selecting optimal leaders are currently lacking.In this talk, we give an overview of our ongoing work on leader selection in complex networks.  We focus on three design criteria, namely, the robustness of the system to noise in the links between nodes, the time for the follower nodes to converge to their desired state, and the controllability to the follower nodes from the leader nodes.  We present a unifying framework based on submodularity, a diminishing returns property analogous to concavity of real-valued functions, for studying each of these criteria.  Our framework enables efficient leader selection based on the criteria above, with provable guarantees on the resulting system performance.  Moreover, we generalize our approach to time-varying networks, including networks with random failures, arbitrary topology variations due to node mobility, and attacks by an intelligent adversary targeting one or more links.  

Talk Title: Submodularity in Dynamics and Control of Networked Systems

Networked systems, consisting of distributed nodes that sense their surroundings, exchange information with other nodes, and perform actuation, play an ever-increasing role in applications such as transportation, energy, and health care. In order to provide guarantees on stability and performance, these systems must be controlled via external inputs. An efficient way to do this is by controlling a small subset (leaders) of the network nodes, which then steer the “follower nodes” to the desired state via local interactions. The choice of input nodes will determine critical properties of the system, such as robustness, controllability, and convergence. Selecting a subset of input nodes, however, is inherently a discrete optimization problem, making continuous optimization techniques for control synthesis inapplicable. This talk will describe a submodular optimization framework for selecting the input nodes. Submodularity is a diminishing returns property of discrete functions, analogous to concavity of continuous functions that enables efficient optimization algorithms with provable optimality guarantees.