On the linear quadratic data-driven control
On the linear quadratic data-driven control
The classical approach for solving control problems is model based: first a model representation is derived from given data of the plant and then a control law is synthesized using the model and the control specifications. We present an alternative approach that circumvents the explicit identification of a model representation. The considered control problem is finite horizon linear quadratic tracking. The results are derived assuming exact data and the optimal trajectory is constructed off-line.
Markovsky, Ivan
7d632d37-2100-41be-a4ff-90b92752212c
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
July 2007
Markovsky, Ivan
7d632d37-2100-41be-a4ff-90b92752212c
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Markovsky, Ivan and Rapisarda, Paolo
(2007)
On the linear quadratic data-driven control.
European Control Conference (ECC'07), Kos, Greece.
02 - 05 Jul 2007.
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Conference or Workshop Item
(Paper)
Abstract
The classical approach for solving control problems is model based: first a model representation is derived from given data of the plant and then a control law is synthesized using the model and the control specifications. We present an alternative approach that circumvents the explicit identification of a model representation. The considered control problem is finite horizon linear quadratic tracking. The results are derived assuming exact data and the optimal trajectory is constructed off-line.
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DatadrivenECC.pdf
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Published date: July 2007
Additional Information:
Event Dates: July 2-5, 2007
Venue - Dates:
European Control Conference (ECC'07), Kos, Greece, 2007-07-02 - 2007-07-05
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 264820
URI: http://eprints.soton.ac.uk/id/eprint/264820
PURE UUID: f563d702-d5fb-4063-b784-1baea434a836
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Date deposited: 13 Nov 2007 16:05
Last modified: 14 Mar 2024 07:57
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Contributors
Author:
Ivan Markovsky
Author:
Paolo Rapisarda
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