Predictive Optimal Iterative Learning Control
Amann, N, Owens, D H and Rogers, E (1998) Predictive Optimal Iterative Learning Control. International Journal of Control, 69, (2), 203-226.
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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.
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||04 Mar 2004|
|Last Modified:||12 Aug 2012 00:05|
|Contributors:||Amann, N (Author)
Owens, D H (Author)
Rogers, E (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||102|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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