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Data-driven control: a behavioral approach

Data-driven control: a behavioral approach
Data-driven control: a behavioral approach
In this work, we study the design of a controller using system data. We present three data-driven approaches based on the notion of control as interconnection. In the first approach, we use both the data and representations to compute control variable trajectories that impose a prescribed path on the to-be-controlled variables. The second method is completely data-driven and we prove sufficient conditions for determining a controller directly from data. Finally, we show how to determine a controller directly from data in the case where the control and to-be-controlled variables coincide.
0167-6911
37-43
Maupong, Thabiso
72ad3e98-f5d0-4417-9b23-89f2c5d774f3
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Maupong, Thabiso
72ad3e98-f5d0-4417-9b23-89f2c5d774f3
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b

Maupong, Thabiso and Rapisarda, Paolo (2017) Data-driven control: a behavioral approach. [in special issue: JCW] Systems & Control Letters, 101, 37-43. (doi:10.1016/j.sysconle.2016.04.006).

Record type: Article

Abstract

In this work, we study the design of a controller using system data. We present three data-driven approaches based on the notion of control as interconnection. In the first approach, we use both the data and representations to compute control variable trajectories that impose a prescribed path on the to-be-controlled variables. The second method is completely data-driven and we prove sufficient conditions for determining a controller directly from data. Finally, we show how to determine a controller directly from data in the case where the control and to-be-controlled variables coincide.

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More information

Accepted/In Press date: 5 April 2016
e-pub ahead of print date: 25 May 2016
Published date: March 2017
Organisations: Vision, Learning and Control
Learn more about Vision, Learning and Control research Learn more about Vision, Learning and Control research Learn more about Electronics & Computer Science research

Identifiers

Local EPrints ID: 393528
URI: http://eprints.soton.ac.uk/id/eprint/393528
DOI: doi:10.1016/j.sysconle.2016.04.006
ISSN: 0167-6911
PURE UUID: 549df624-0249-418a-adb4-c4e7c1fe8ffd

Catalogue record

Date deposited: 28 Apr 2016 11:53
Last modified: 15 Mar 2024 05:32

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Contributors

Author: Thabiso Maupong
Author: Paolo Rapisarda

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