The University of Southampton
University of Southampton Institutional Repository

LMI-based design of robust iterative learning control schemes with finite frequency range tracking specifications

LMI-based design of robust iterative learning control schemes with finite frequency range tracking specifications
LMI-based design of robust iterative learning control schemes with finite frequency range tracking specifications
Many systems compete the same finite duration task over and over again, where once each is complete the system resets to the starting location and the next one begins. Each execution is known as a trial and the duration the trial length. Iterative learning control has been developed for such systems where the distinguishing feature is the use of information from previous trials to update the control signal applied on the next one. The new contributions in this paper are for algorithms that use a feedforward filter often termed the learning filter. A condition for existence of this filter is formulated in terms of linear matrix inequalities through application of the generalized Kalman-Yakubovich-Popov lemma. This allows filter design over a finite, as opposed to the complete, frequency range which is more practically relevant in many cases. An extension to systems with uncertainties represented by a polytopic description is also developed using parameter dependent Lyapunov functions.
Paszke, W.
dd4b8f12-17c7-45ee-bfb0-e9675bd7d854
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Galkowski, K.
40c02cf5-8fcb-44de-bb1e-f9f70fdd265d
Paszke, W.
dd4b8f12-17c7-45ee-bfb0-e9675bd7d854
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Galkowski, K.
40c02cf5-8fcb-44de-bb1e-f9f70fdd265d

Paszke, W., Rogers, E. and Galkowski, K. (2013) LMI-based design of robust iterative learning control schemes with finite frequency range tracking specifications. 2013 American Control Conference, Washington DC, United States. 17 - 19 Jun 2013.

Record type: Conference or Workshop Item (Paper)

Abstract

Many systems compete the same finite duration task over and over again, where once each is complete the system resets to the starting location and the next one begins. Each execution is known as a trial and the duration the trial length. Iterative learning control has been developed for such systems where the distinguishing feature is the use of information from previous trials to update the control signal applied on the next one. The new contributions in this paper are for algorithms that use a feedforward filter often termed the learning filter. A condition for existence of this filter is formulated in terms of linear matrix inequalities through application of the generalized Kalman-Yakubovich-Popov lemma. This allows filter design over a finite, as opposed to the complete, frequency range which is more practically relevant in many cases. An extension to systems with uncertainties represented by a polytopic description is also developed using parameter dependent Lyapunov functions.

Full text not available from this repository.

More information

Published date: 19 June 2013
Venue - Dates: 2013 American Control Conference, Washington DC, United States, 2013-06-17 - 2013-06-19
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 352232
URI: http://eprints.soton.ac.uk/id/eprint/352232
PURE UUID: eaa75384-4b85-4281-b4d8-0f38edfd9c72
ORCID for E. Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 08 May 2013 14:15
Last modified: 20 Jul 2019 01:23

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×