Anuradha Annaswamy

Headshot Photo
First Name: 
Anuradha
Last Name: 
Annaswamy

Anuradha Annaswamy received the Ph.D. degree in Electrical Engineering from Yale University in 1985.  She has been a member of the faculty at Yale, Boston University, and MIT where currently she is the director of the Active-Adaptive Control Laboratory and a Senior Research Scientist in the Department of Mechanical Engineering.  Her research interests pertain to adaptive control theory and applications to aerospace and automotive control, active control of noise in thermo-fluid systems, control of autonomous systems, co-design of control and platform architectures in cyber physical systems, and decision and control in smart grids, smart cities, and critical infrastructures. Dr. Annaswamy has received several awards including the George Axelby and Control Systems Magazine best paper awards from the IEEE Control Systems Society, the Presidential Young Investigator award from the National Science Foundation, the Hans Fisher Senior Fellowship from the Institute for Advanced Study at the Technische Universität München in 2008, the Donald Groen Julius Prize for 2008 from the Institute of Mechanical Engineers, and the Distinguished Member award from the IEEE Control Systems Society in 2016. Dr. Annaswamy is a Fellow of the IEEE and IFAC. Dr. Annaswamy is an active member of the IEEE Control Systems Society (CSS) and the American Automatic Control Council. She was a nominated and elected member of the CSS Board of Governors for 1993 and 2010 – 2012, respectively. She was a Program Chair of the American Control Conference (ACC) during 2003, General Chair of the 2008 ACC, and Program Chair for the 2nd Virtual Control Conference on Smart Grid Technology. She served as the Vice-President for Conference Activities in the IEEE CSS Executive Committee for 2014-15, and will serve as the VP for Technical Activities, CSS Excomm for 2016-17. Dr. Annaswamy is a co-editor of the IEEE CSS report on Impact of Control Technology: Overview, Success Stories, and Research Challenges,2011 (1st Edition) and 2014 (2nd Edition) along with Tariq Samad. She is the project lead on the publication, “Vision for Smart Grid Controls: 2030 and Beyond,” (Eds: A.M. Annaswamy, M. Amin, C. DeMarco and T. Samad), 2013.

Contact Information
Email: 
aanna@mit.edu
Telephone: 
617-253-0860
Affiliation: 
Massachusetts Institute of Technology
Position: 
VP Technical Activities; Distinguished Lecturer

Location

Room 3-348, MIT, Department of Mechanical Engineering, 77 Massachusetts Avenue
Cambridge, Massachusetts 02139
United States

Distinguished Lecture Program

Talk Title: Transactive Control in Smart Cities

The concept of Smart City is gaining popular attention with the goal of sustainability and efficiency, the needs of enhancing quality and performance, and the explosion of technological advances in communication and computation. Given that 50% of the world’s population lives in urban regions, critical infrastructures of energy, transportation, and health and their growing interdependencies have to be collectively analyzed and designed to provide the substrate for the realization of the Smart City Concept. This talk will address one of these infrastructures, Urban Mobility, and in particular the concept of dynamic toll pricing to alleviate congestion. With the growth and expansion of many large metropolitan centers in the last few decades, the problem of traffic congestion continues to grow and vex commuters, commercial drivers, city planners and officials, and environmentalists worldwide. Over 1 billion vehicles travel on the roads today, and that number is projected to double by 2020. Driving a car is an unavoidable choice for at least 50% of city populations, who rely on their vehicles to get to school or to work. Transactive control, the concept of feedback through economic transactions, appears to be a promising tool for addressing traffic congestion. In particular, we have explored dynamic toll pricing for alleviating traffic congestion and increasing traffic flow during peak hours of the day. A model-based approach to dynamic toll pricing has been developed to provide a systematic method for determining optimal toll pricing schemes. Real-time traffic information from on-road sensors is integrated with complex models of driver behavior and traffic flow to determine the toll price, which acts as a controller to divert traffic flows to desired lanes and routes and lessen the traffic congestion experienced in certain areas. The overall idea of transactive control with particular illustrations of dynamic toll pricing will be presented in this talk.

Talk Title: A Dynamic Framework for Integration of Renewables in Smart Grids

Two major players in a smart grid are renewables and flexible consumption. The former is necessitated by global concerns of sustainability and greenhouse gas emissions, and dwindling resources of fossil fuels. The latter is enabled through the feasibility of fast and large-scale communication and the growing acceptance and economic potential of flexible consumption. Introduction of these two players brings with it a host of challenges, many of which stem from the introduction of complex and uncertain dynamics at various time-scales. In order to assess the impact of these dynamics, and realize the desired goals of a smart grid, of delivering affordable and reliable power to all end-users, an end-to-end framework that is dynamic, and allows the deployment of various analysis and synthesis tools of stability, estimation, optimization, and control is needed. This framework should not only encompass the physically relevant, and traditional timescales of frequency and voltage control, but economically relevant market-based decisions for planning and economic dispatch. More importantly, this framework should address the interactions between the former active-control components that manipulate physical variables and the latter transactive-control components that manipulate economic variables. In this talk, recent results developed in the AAC laboratory at MIT related to the development of such a dynamic framework will be presented.

Talk Title: Practical Adaptive Control

Adaptive Control is viewed as a game changer in many application domains where real-time feedback control is essential to ensure the desired performance. Adaptive controllers, whose distinguishing feature is a parameter estimator that prescribes the rule for changing the control parameters in real-time, have been studied extensively over the past forty years, with fundamental properties of stability and robustness well understood. Guidelines for analysis and synthesis for adaptive controllers have been laid out for linear and (specific classes of) nonlinear systems, continuous and discrete-time systems, single-input and multi-input systems, and deterministic and stochastic systems. So what’s missing?  There are glaring gaps in adaptive control theory that remain to be closed for adaptive control to be a viable, practical, and easily implementable methodology. Guarantees have to be provided that ensure robustness to a wide variety of non-parametric perturbations. Guidelines have to be in place for a systematic design of all free parameters in the controller. Bounds have to be derived, not only for steady-state behavior, but also for transient characteristics. Implementation issues will have to be satisfactorily addressed. The ability to accommodate actuator constraints in terms of bandwidth, magnitude limits, and rate limits has to be precisely characterized. Recently, there have been breakthroughs in Adaptive Control that have led to reducing the above gaps. This talk will outline the basic principles of the now classical adaptive control theory, but also highlight these recent results and show how they contribute towards making adaptive control practical.