Non-linear predictive generalised minimum variance state-dependent control
A non-linear predictive generalised minimum variance control algorithm is introduced for the control of non-linear discrete-time state-dependent multivariable systems. The process model includes two different types of subsystems to provide a variety of means of modelling the system and inferential c...
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Veröffentlicht in: | IET control theory & applications 2015-10, Vol.9 (16), p.2438-2450 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | A non-linear predictive generalised minimum variance control algorithm is introduced for the control of non-linear discrete-time state-dependent multivariable systems. The process model includes two different types of subsystems to provide a variety of means of modelling the system and inferential control of certain outputs is available. A state-dependent output model is driven from an unstructured non-linear input subsystem which can include explicit transport-delays. A multi-step predictive control cost function is to be minimised involving weighted error, and either absolute or incremental control signal costing terms. Different patterns of a reduced number of future controls can be used to limit the computational demands. |
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ISSN: | 1751-8644 1751-8652 1751-8652 |
DOI: | 10.1049/iet-cta.2015.0356 |