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Robust and Optimal Control of Spatially Interconnected Systems

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Abstract:
Many systems consist of similar units which directly interact with their nearest neighbors. Even when these units have tractable models and interact with their neighbors in a simple and predictable fashion, when viewed as a whole the resulting system often displays rich and complex behavior. Examples include vehicle platoons, vehicles flying in formation, and in the limit as the size of the subsystems approach zero, many systems governed by partial differential equations. An important aspect of many of these systems is that sensing and actuation capabilities exist at every unit. In the examples above, this is clearly the case for vehicle platoons and aerial vehicle systems; with the rapid advances in microelectro- mechanical actuators and sensors, one may control systems governed by partial differential equations with a large number of distributed actuators and sensors as well. If one attempts to control these systems using standard control design techniques, severe limitations will be quickly encountered as most optimal control techniques cannot handle systems of high dimension and with a large number of inputs and outputs. In addition, it is typically not feasible to control these systems with centralized schemes, as these require high levels of connectivity, impose a substantial computational burden, and are typically more sensitive to failures and modeling errors than decentralized schemes. In this talk we discuss new techniques for synthesizing control systems for spatially distributed and interconnected systems. From the point of implementation, the resulting control strategies inherit the same structure as the plant; in particular, the controllers are distributed, with communication allowed between neighboring controllers. The advantages of decentralized computation are thus obtained, without sacrificing global performance objectives. The talk includes several in-depth simulation/ animation examples and a discussion of several experimental test-beds being used to motivate the tools being developed.

http://www.mae.cornell.edu/Raff
Type of Seminar:
Public Seminar
Speaker:
Prof. Raffaelo D'Andrea
218 Upson Hall Sibley School of Mech. & Aero. Engr. Cornell University Ithaca, NY 14853-7501
Date/Time:
Jun 15, 2000   17:15
Location:

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

Prof. M. Morari
No downloadable files available.
Biographical Sketch:
Raffaello D'Andrea received the B.A.Sc. degree in engineering physics from the University of Toronto, and the M.S. and Ph.D. degrees in electrical engineering from the California Institute of Technology. Prior to graduate school, he was employed as an electrical engineer at Bell Northern Research where he designed packet switching hardware. He has been with the Department of Mechanical and Aerospace Engineering at Cornell University since 1997, where he is an Assistant Professor. He is also a member of the Applied Mathematics and Electrical Engineering fields at Cornell University. His research interests include the development of computational tools for the robust control of complex interconnected systems, and applying these techniques to mechanical and aerospace systems. His teaching interests include Systems Engineering and Robot Soccer. Dr. D'Andrea has been the recipient of a Natural Sciences and Engineering Research Council of Canada Centennial Graduate Fellowship (1991-1996), the 1995 American Control Council O. Hugo Schuck Best Paper award, the 1996 IEEE Conference on Decision and Control Best Student Paper award, the 1999 Mechanical and Aerospace Engineering Shepherd Teaching Prize, and the National Science Foundation CAREER award.