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Predictive Optimal Iterative Learning Control

Predictive Optimal Iterative Learning Control
Predictive Optimal Iterative Learning Control
A new optimization-based iterative learning control algorithm is proposed and its properteis dervied. 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.
0020-3270
203-226
Amann, N
4ae6bc24-2ac6-438b-8408-08f3dfeef9bc
Owens, D H
d1838c62-b96e-4710-9e5a-ed097fae28f6
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
Amann, N
4ae6bc24-2ac6-438b-8408-08f3dfeef9bc
Owens, D H
d1838c62-b96e-4710-9e5a-ed097fae28f6
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), 203-226.

Record type: Article

Abstract

A new optimization-based iterative learning control algorithm is proposed and its properteis dervied. 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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More information

Published date: 1998
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250673
URI: https://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 Jul 2017 10:40

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Contributors

Author: N Amann
Author: D H Owens
Author: E Rogers

University divisions

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