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Linear quadratic theory for distributed control - From telescopes to vehicle formations

A linear quadratic control problem is considered, where several different controllers act as a team, but with access to different measurement variables. Under appropriate assumptions on communication between the controllers, a quadratic control objective can be optimized using finite-dimensional convex optimization. Versions of this problem has been discussed in economic literature, as well as in statistical decision theory. Some instances were solved in the 1960-70's, but significant progress on the role of controller communication has recently been made. In this tutorial presentation we focus on the connection between distributed control and stochastic optimization with correlation constraints. The method gives a non-conservative extension of linear quadratic control theory to distributed control with bounds on the rate of information propagation. The theory is illustrated by application to control of vehicle formations and control of a flexible mirror in a telescope. It is possible to study how the achievable control performance depends on the local availability of measurements. For vehicle formations, the control performance when each vehicle measures the distance to its nearest neighbors is compared with the performance achievable when observing also vehicles further away.
Type of Seminar:
IfA Seminar
Prof. Anders Rantzer
Automatic Control LTH, Lund University , Sweden
Feb 20, 2007   10:15 a.m.

ETH Zentrum, Building ETZ, Room E6, Gloriastrasse 35, 8006 Zurich
Contact Person:

Prof. M. Morari
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Biographical Sketch:
Anders Rantzer was born in 1963. He received a Ph.D. degree in optimization and systems theory from the Royal Institute of Technology (KTH), Stockholm, Sweden. After postdoctoral positions at KTH and at IMA, University of Minnesota, he joined the Department of Automatic Control, Lund, in 1993. In 1999, he was appointed professor of Automatic Control in Lund. The academic year of 2004/05 was spent as visiting associate at Caltech. Rantzer has been serving as associate editor of IEEE Transactions on Automatic Control and several other journals. He is a winner of the SIAM Student Paper Competition and the IFAC Congress Young Author Price and he is a Fellow of IEEE. His research interests are in modeling, analysis and synthesis of control systems, with particular attention to uncertainty, optimization and distributed control.