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The nonlinear model-predictive control of a chemical plant using multiple neural networks

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Abstract

A combination of multiple neural networks (NNs) is selected and used to model nonlinear multi-input multi-output (MIMO) processes with time delays. An optimisation procedure for a nonlinear model-predictive control (MPC) algorithm based on this model is then developed. The proposed scheme has been applied and evaluated for two example problems, including the MPC of a multi-component distillation column.

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Authors and Affiliations

  1. The University of the Petroleum Industry, 63431, Ahwaz, Iran

    H. Jazayeri-Rad

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  1. H. Jazayeri-Rad
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Correspondence to H. Jazayeri-Rad.

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Jazayeri-Rad, H. The nonlinear model-predictive control of a chemical plant using multiple neural networks. Neural Comput & Applic 13, 2–15 (2004). https://doi.org/10.1007/s00521-004-0399-y

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  • DOI: https://doi.org/10.1007/s00521-004-0399-y

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