Algorithms for industrial model predictive control

David J. Sandoz, Matthew J. Desforges, Barry Lennox, Peter R. Goulding

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This article is concerned with control methods that have been embedded in an industrial model predictive control software package and that have been applied to a wide variety of industrial processes. Three methods are described and the various features are evaluated by considering a constrained multivariable simulation. One method has been in use since 1988 and is widely exploited in industry. The latest methods employ quadratic programming, which has become realistic to employ because of the advances in computing. The relative attributes are contrasted by assessing the ability of the controllers to recover effectively from the impact of a large unmeasured disturbance.
    Original languageEnglish
    Pages (from-to)125-134
    Number of pages9
    JournalComputing and Control Engineering Journal
    Volume11
    Issue number3
    Publication statusPublished - 2000

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