Process optimization by grouping mixed integer nonlinear programming constraints

Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and...

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Bibliographische Detailangaben
Hauptverfasser:	Zhang, Detong, Hillier, Gareth, Vedam, Rajkumar, Hemachandran, Kishore Kumar, Madabhushi, Pranav Bhaswanth, Boddupalli, Sankararao, Lavate, Mallikarjun Avanna, Tanartkit, Purt, Kattapuram, James Jude
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY FUNCTIONAL ELEMENTS OF SUCH SYSTEMS GENERATION MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING SYSTEMS FOR STORING ELECTRIC ENERGY
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Beschreibung
Zusammenfassung:	Real-time dynamic optimization of a process model in an online model-based process control computing environment. A mixed integer nonlinear programming (MINLP) solver utilizes grouping of first-principle model units to implement constraints of the underlying process. A group identifier parameter and a group complement parameter enable the grouping behavior through association with the first-principles model units.