Optimal Selection of Measurements and Manipulated Variables for Production Control

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dc.contributor.advisorMc Avoy, Thomas Jen_US
dc.contributor.advisorZafiriou, Evanghelosen_US
dc.contributor.authorAbi Assali, Wuendyen_US
dc.contributor.departmentChemical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2009-01-24T06:45:34Z
dc.date.available2009-01-24T06:45:34Z
dc.date.issued2008-10-14en_US
dc.description.abstractThe main objective in a chemical plant is to improve profit while assuring products meet required specifications and satisfy environmental and operational constraints. A sub-objective that directly affects profit (main objective) is to improve the control performance of key economic variables in the plant, such as production rate and quality. An optimal control-based approach is proposed to determine a set of measurements and manipulated variables (dominant variables) and to structure them to improve plant profitability. This approach is model-based, and it uses optimal control theory to find the dominant variables that affect economic variables in the plant. First, the measurements and manipulated variables that affect product flow and quality are identified. Then, a decentralized control structure is designed to pair these measurements with the manipulated variables. Finally, a model predictive control (MPC) is built on top of the resulting control structure. This is done to manipulate the set point of these loops in order to change the production rate and product quality. Another sub-objective that affects the profit in the plant is to improve the control of inerts. In general, the inventory of the inerts is controlled using a purge. A new methodology to optimally control inerts is presented. This methodology aims to reduce the losses that occur throughout the purge by solving an optimization problem to determine the maximum amount of inert that can be handled in the plant without having shut down of the plant due to inert accumulation. The methodology is successfully applied to the Tennessee Eastman Plant where the operating cost was reduced approximately 4%. This methodology solves an approximation to an optimal economic problem. First, it improves the control performance of key economic variables in the plant. Therefore, tighter control of these economic variables is achieved and the plant can be operated closer to operational constraints. Second, it minimizes purge which is a variable that generally causes significant costs in the plant. This approach is applied to the Tennessee Eastman and the Vinyl Acetate Processes. Results demonstrating the effectiveness of this method are presented and compared with the results from other authors.en_US
dc.format.extent1348394 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/8780
dc.language.isoen_US
dc.subject.pqcontrolledEngineering, Chemicalen_US
dc.subject.pqcontrolledEngineering, Chemicalen_US
dc.subject.pquncontrolledProcess Controlen_US
dc.subject.pquncontrolledOptimal Controlen_US
dc.subject.pquncontrolledMeasurement Selectionen_US
dc.subject.pquncontrolledManipulated Variables Selectionen_US
dc.subject.pquncontrolledTennessee Eastman Planten_US
dc.subject.pquncontrolledVinyl Acetate Planten_US
dc.subject.pquncontrolledKalman Filteren_US
dc.subject.pquncontrolledSoft Sensoren_US
dc.subject.pquncontrolledInert controlen_US
dc.titleOptimal Selection of Measurements and Manipulated Variables for Production Controlen_US
dc.typeDissertationen_US

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