Generalized predictive control in the delta-domain

Morten Bach Lauritsen, Morten Rostgaard Jensen, Niels Kjølstad Poulsen

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    Abstract

    This paper describes new approaches to generalized predictive control formulated in the delta (δ) domain. A new δ-domain version of the continuous-time emulator-based predictor is presented. It produces the optimal estimate in the deterministic case whenever the predictor order is chosen greater than or equal to the number of future predicted samples, however a “good” estimate is usually obtained in a much longer range of samples. This is particularly advantageous at fast sampling rates where a “conventional” predictor is bound to become very computationally demanding. Two controllers are considered: one having a well-defined limit as the sampling period tends to zero, the other being a close approximation to the conventional discrete-time GPC. Both algorithms are discrete in nature and well-suited for adaptive control. The fact, that δ-domain model are used does not introduce an approximation since such a model can be obtained by an exact sampling of a continuous-time model.
    Original languageEnglish
    Title of host publicationProceedings of the American Control Conference
    VolumeVolume 5
    PublisherIEEE
    Publication date1995
    Pages3709-3713
    ISBN (Print)07-80-32445-5
    Publication statusPublished - 1995
    Event1995 American Control Conference - Seattle, WA, United States
    Duration: 21 Jun 199523 Jun 1995
    http://www-control.eng.cam.ac.uk/extras/conferences/ACC95.html

    Conference

    Conference1995 American Control Conference
    CountryUnited States
    CitySeattle, WA
    Period21/06/199523/06/1995
    Internet address

    Bibliographical note

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