Predictive Optimal Iterative Learning Control
Predictive Optimal Iterative Learning Control
A new optimization-based iterative learning control algorithm is proposed and its properties derived. An important characteristic of this algorithm is that it uses present and future predicted errors to compute the current control, in a similar manner to model-based predictive control using a receding horizon. In particular, it enables the algorithm designer to achieve good control over convergence rate. The actual implementation has a multimodel structure but uses standard linear quadratic regulator methods for a causal formulation (in the iterative learning sense) of what is originally a non-causal algorithm. The results are illustrated by simulations.
203-226
Amann, N
4ae6bc24-2ac6-438b-8408-08f3dfeef9bc
Owens, D H
db24b8ef-282b-47c0-9cd2-75e91d312ad7
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
1998
Amann, N
4ae6bc24-2ac6-438b-8408-08f3dfeef9bc
Owens, D H
db24b8ef-282b-47c0-9cd2-75e91d312ad7
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
Amann, N, Owens, D H and Rogers, E
(1998)
Predictive Optimal Iterative Learning Control.
International Journal of Control, 69 (2), .
Abstract
A new optimization-based iterative learning control algorithm is proposed and its properties derived. An important characteristic of this algorithm is that it uses present and future predicted errors to compute the current control, in a similar manner to model-based predictive control using a receding horizon. In particular, it enables the algorithm designer to achieve good control over convergence rate. The actual implementation has a multimodel structure but uses standard linear quadratic regulator methods for a causal formulation (in the iterative learning sense) of what is originally a non-causal algorithm. The results are illustrated by simulations.
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Published date: 1998
Organisations:
Southampton Wireless Group
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Local EPrints ID: 250673
URI: http://eprints.soton.ac.uk/id/eprint/250673
ISSN: 0020-3270
PURE UUID: ff5e225c-9d12-4543-a70a-3d6fe67c29b8
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Date deposited: 04 Mar 2004
Last modified: 18 Oct 2022 01:32
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Author:
N Amann
Author:
D H Owens
Author:
E Rogers
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