Aveva Software, LLC

Invensys Systems, Inc.

Schneider Electric Software, LLC

Purt Tanartkit

Rajkumar Vedam

Detong Zhang

Gareth Hillier

James Jude Kattapuram

Kishore Kumar Hemachandran

Mallikarjun Avanna Lavate

Sanjay Desai

Sankararao Boddupalli

John C Hernandez

Pranav Bhaswanth Madabhushi

Sreenivas Rao Bukka

Rahul Sheth

Gadiraju Varma

Real-time dynamic process modeling in an online model-based process control computing environment. A solver system utilizes an oracle to implement adaptive algorithms for a mixed integer nonlinear programming (MINLP) solver and a nonlinear programming (NLP) solver.

Adaptive mixed integer nonlinear programming for process management

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.

Process optimization by grouping mixed integer nonlinear programming constraints

Some embodiments include a server system including a first logic module executable by a processor for receiving a data communication from an industrial control system coupled to a communications network. In some embodiments, the data communication comprises data or data streams associated with the industrial process. The program logic of the first logic module includes a model configured to receive a variable and iterate and converge an optimization problem to an optimization solution to a first level of optimization based at least in part on the variable and the data or data streams. A second logic module executable by the processor is operatively data-linked to the first logic module and utilizes a model to iteratively process data values of the optimization solution to a second level of optimization with an increased level of optimization over the first level of optimization.

Process optimization server and system

A system and method for modeling industrial processes is described. One embodiment includes collecting a plurality of flowsheets, which include corresponding groups of unit models and combining the plurality of flowsheets to create a combined model. In addition, a first macro associated with a first flowsheet is initiated and other macros by the same name as the first macro are automatically executed. In variations, the other macros are executed from a lowest hierarchical level flowsheet relative to the first flowsheet to a higher hierarchical level until the first macro is run.

Multiple model development using subflowsheet functionality

A software plant process modeling system operates in multiple modes. The software system uses process unit models. A process unit model includes at least one equation and at least one variable. The software system sets a status of a variable in the unit model to a first state. The first state is associated with a first mode of operation. The software system then sets the status of the same variable in the unit model to a second state. The second state is associated with a second mode of operation. The software system generates an open-equation model in operating in multiple modes. The software system receives a modification to at least one process unit model. Thus, a user may create a single plant process model for operation in multiple modes.

Process model generation independent of application mode

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Yorba Linda, CA, United States of America

Purt Tanartkit