Rejection of the Feed-Flow Disturbances in a Multi-Component Distillation Column Using a Multiple Neural Network Model-Predictive Controller
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. ...
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| Format: | Article |
| Language: | English |
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Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR
2004-12-01
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| Series: | Iranian Journal of Chemistry & Chemical Engineering |
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| Online Access: | http://www.ijcce.ac.ir/article_8134_6692984a133dff071266e56ce02b0cf4.pdf |
| Summary: | 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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| ISSN: | 1021-9986 1021-9986 |