rejection of the feed-flow disturbances in a multi-component distillation column using a multiple neural network model-predictive controller
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چکیده
this article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (mpc) of a chemical plant. a combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (mimo) process with time delays. an optimization procedure for a neural mpc algorithm based on this model is then developed. the proposed scheme has been tested on a model of an 18-plate multi-component distillation column. the algorithm provides excellent disturbance rejection for this process.
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عنوان ژورنال:
iranian journal of chemistry and chemical engineering (ijcce)ناشر: iranian institute of research and development in chemical industries (irdci)-acecr
ISSN 1021-9986
دوره 23
شماره 2 2004
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