dc.contributor.author | Rose, Lina | |
dc.contributor.author | D., Pamela | |
dc.contributor.author | Stanley, P. Kingston | |
dc.contributor.author | Daniel, P. Vijay | |
dc.date.accessioned | 2019-11-05T09:37:11Z | |
dc.date.available | 2019-11-05T09:37:11Z | |
dc.date.issued | 2019-10-01 | |
dc.identifier.issn | 1819-6608 | |
dc.identifier.uri | http://142.54.178.187:9060/xmlui/handle/123456789/888 | |
dc.description.abstract | A model based approach was chosen for such a complex MIMO system is due to the restrictions the system bear in terms of control variables. Though the process simply refers to separation of two or more liquid or vapor components, the process flow and the component fractions really has to be identified since that determines the quality of the distillate. A pure modeling concept for a sophisticated process like distillation column is demonstrated in this study. It’s a complex task to model the distillation column and control the parameters since the process is a multiple input multiple output (MIMO) system. Hence only based on many assumptions about many of the control variables the response can be found. The work has been extended to modeling and control of various parts of column such as reflux drum and feed tray. Fuzzy Control of Reflux Drum was carried out where, the analysis of approximate data has done as a case study due to lack of industrial information | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Engineering and Technology | en_US |
dc.subject | Nonlinear processes | en_US |
dc.subject | Volatility | en_US |
dc.subject | Rectifying section | en_US |
dc.subject | Fuzzy control | en_US |
dc.subject | Modeling | en_US |
dc.title | MODELING OF DISTILLATION COLUMN AND INTELLIGENT CONTROL OF REFLUX DRUM | en_US |
dc.type | Article | en_US |