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Industrial applications of a new adaptive estimator for inferential control

  • Applicatons Of Adaptive Control
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Adaptive Control Strategies for Industrial Use

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 137))

Abstract

Two methods for inferring process outputs which can only be measured at infrequent intervals of time, from other more rapidly sampled secondary outputs, are presented. The estimators (or soft-sensors) use both a general input-output representation of the plant and a state space representation as starting points for synthesis of the algorithms. The developments are supported by results from some recent industrial scale site tests: on-line determination of product composition in a large industrial distillation tower and in a companion study, biomass concentration in an industrial mycelial fermentation. The technique uses measurements from established instruments such as temperature in the distillation column and off-gas carbon dioxide in the fermenter. The key development is an adaptive estimation relationship for inferring infrequently measured process outputs, from other more rapidly sampled secondary outputs. The structure of the estimators are not application dependent and their parameters can be continuously estimated and updated. As a result, slow variations in plant or disturbance characteristics can be tracked. In contrast to model-based estimators (e.g. Kalman filtering), the methods proposed require minimal effort for estimator design. A significant improvement in overall process control performance is possible using the estimated values of plant output rather than employing direct feedback of the infrequently obtained measurements. Simulation studies and production scale plant tests demonstrate estimator capabilities.

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Author information

Authors and Affiliations

  1. Department of Chemical and Process Engineering, University of Newcastle upon Tyne, England

    A. J. Morris, M. T. Tham & G. A. Montague

Authors
  1. A. J. Morris
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  2. M. T. Tham
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  3. G. A. Montague
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Editor information

Sirish L. Shah Guy Dumont

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© 1989 Springer-Verlag

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Morris, A.J., Tham, M.T., Montague, G.A. (1989). Industrial applications of a new adaptive estimator for inferential control. In: Shah, S.L., Dumont, G. (eds) Adaptive Control Strategies for Industrial Use. Lecture Notes in Control and Information Sciences, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0042935

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  • DOI: https://doi.org/10.1007/BFb0042935

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-51869-3

  • Online ISBN: 978-3-540-46833-2

  • eBook Packages: Springer Book Archive

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