Convergence of control performance by unfalsification of models - levels of confidence
Convergence of control performance by unfalsification of models - levels of confidence
A general framework is introduced for iterative/adaptive controller design schemes by model unfalsification. An important feature of the schemes is their convergence near to the best possible controller given a set of model and controller structures. The problem of stability assured controller tuning is examined through unfalsified Riemannian bands of the Nyquist plot. Instability tolerant H(?) and l(1)-norm-based controller tuning schemes are introduced. Computational problems are discussed and a simulation is used to illustrate the new scheme.
471-502
Veres, S.M.
909c60a0-56a3-4eb6-83e4-d52742ecd304
2001
Veres, S.M.
909c60a0-56a3-4eb6-83e4-d52742ecd304
Veres, S.M.
(2001)
Convergence of control performance by unfalsification of models - levels of confidence.
International Journal of Adaptive Control and Signal Processing, 15 (5), .
(doi:10.1002/acs.685).
Abstract
A general framework is introduced for iterative/adaptive controller design schemes by model unfalsification. An important feature of the schemes is their convergence near to the best possible controller given a set of model and controller structures. The problem of stability assured controller tuning is examined through unfalsified Riemannian bands of the Nyquist plot. Instability tolerant H(?) and l(1)-norm-based controller tuning schemes are introduced. Computational problems are discussed and a simulation is used to illustrate the new scheme.
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Published date: 2001
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Local EPrints ID: 22272
URI: http://eprints.soton.ac.uk/id/eprint/22272
ISSN: 0890-6327
PURE UUID: 8dd73228-19aa-4ec0-bcd9-bf72301bff4c
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Date deposited: 21 Mar 2006
Last modified: 15 Mar 2024 06:36
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S.M. Veres
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