Home > Seminars > Minimal Information for Estimation and Control: A Semidefinite Programming Approach

Minimal Information for Estimation and Control: A Semidefinite Programming Approach

Start:

6/26/2015 at 3:00PM

End:

6/26/2015 at 4:00PM

Location:

258 Fitzpatrick Hall

Host:

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Vijay Gupta

Vijay Gupta

VIEW FULL PROFILE Email: vgupta2@nd.edu
Phone: 574-631-2294
Website: http://ee.nd.edu/faculty/vgupta/
Office: 270 Fitzpatrick Hall

Affiliations

Department of Electrical Engineering Professor and Associate Chair of Graduate Studies
Research Interests: Dr. Gupta's current research interests are in the analysis and design of cyberphysical systems. Such systems are the next generation of engineering systems and involve tightly coupled control, communication, and processing algorithms. Applications include structural health ...
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574-631-2294
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Real-time decision making requires continuous acquisition of information from the environment, but in many cases information acquisition is a costly process. In this talk, we discuss a methodology to design an "information-efficient" sensing mechanism, whose information acquisition rate is "just enough" to make real-time decisions with acceptable accuracy.

Specifically, in the linear-quadratic-Gaussian (LQG) regime, we show that the sensor design problem can be formulated as a semidefinite programming (SDP) problem after applying a novel variable elimination technique. This result also provides an SDP-based solution to the Gaussian sequential rate-distortion problem (a natural generalization of the standard rate-distortion problem to real-time settings), whose complete solution has not been identified in the literature. As a demonstration, we consider a numerical case study of real-time satellite attitude estimation problem using minimal telecommunication.

We also discuss an SDP-based solution to the information-constrained LQG control problems. Open problems and future perspectives will be also discussed.

Seminar Speaker:

Takashi Tanaka

Takashi Tanaka

MIT

Takashi Tanaka received his B.S. degree from Tokyo University in 2006, M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign in 2009 and 2012, all in Aerospace Engineering. Currently, he is a postdoctoral associate at the Laboratory for Information and Decision Systems (LIDS) at Massachusetts Institute of Technology. His research interests are in the joint area of control, optimization, game theory and information theory.