Patents by Inventor Celso Axelrud
Celso Axelrud has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Patent number: 11169494Abstract: System and method for modeling a nonlinear process. A combined model for predictive optimization or control of a nonlinear process includes a nonlinear approximator, coupled to a parameterized dynamic or static model, operable to model the nonlinear process. The nonlinear approximator receives process inputs, and generates parameters for the parameterized dynamic model. The parameterized dynamic model receives the parameters and process inputs, and generates predicted process outputs based on the parameters and process inputs, where the predicted process outputs are useable to analyze and/or control the nonlinear process. The combined model may be trained in an integrated manner, e.g.Type: GrantFiled: March 16, 2015Date of Patent: November 9, 2021Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyar-Rodsari, Edward S Plumer, Eric Hartman, Celso Axelrud, Kadir Liano
-
Patent number: 10528038Abstract: In one embodiment, a model predictive control system for an industrial process includes a processor to execute an optimization module to determine manipulated variables for the process over a control horizon based on simulations performed using an objective function with an optimized process model and to control the process using the manipulated variables, to execute model modules including mathematical representations of a response or parameters of the process. The implementation details of the model modules are hidden from and inaccessible to the optimization module. The processor executes unified access modules (UAM). A first UAM interfaces between a first subset of the model modules and the optimization module and adapts output of the first subset for the optimization module, and a second UAM interfaces between a second subset of the model modules and the first subset and adapts output of the second subset for the first subset.Type: GrantFiled: January 14, 2016Date of Patent: January 7, 2020Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyarrodsari, Celso Axelrud, Kadir Liano
-
Publication number: 20170205813Abstract: In one embodiment, a model predictive control system for an industrial process includes a processor to execute an optimization module to determine manipulated variables for the process over a control horizon based on simulations performed using an objective function with an optimized process model and to control the process using the manipulated variables, to execute model modules including mathematical representations of a response or parameters of the process. The implementation details of the model modules are hidden from and inaccessible to the optimization module. The processor executes unified access modules (UAM). A first UAM interfaces between a first subset of the model modules and the optimization module and adapts output of the first subset for the optimization module, and a second UAM interfaces between a second subset of the model modules and the first subset and adapts output of the second subset for the first subset.Type: ApplicationFiled: January 14, 2016Publication date: July 20, 2017Inventors: Bijan Sayyarrodsari, Celso Axelrud, Kadir Liano
-
Publication number: 20150185717Abstract: System and method for modeling a nonlinear process. A combined model for predictive optimization or control of a nonlinear process includes a nonlinear approximator, coupled to a parameterized dynamic or static model, operable to model the nonlinear process. The nonlinear approximator receives process inputs, and generates parameters for the parameterized dynamic model. The parameterized dynamic model receives the parameters and process inputs, and generates predicted process outputs based on the parameters and process inputs, where the predicted process outputs are useable to analyze and/or control the nonlinear process. The combined model may be trained in an integrated manner, e.g.Type: ApplicationFiled: March 16, 2015Publication date: July 2, 2015Inventors: Bijan Sayyar-Rodsari, Edward S. Plumer, Eric Hartman, Celso Axelrud, Kadir Liano
-
Patent number: 8521310Abstract: A system and method are provided for integrated management of a biofuel distillation process and a biofuel dehydration process of a biofuel production process, comprising a dynamic multivariate model-based controller coupled to a dynamic multivariate predictive model. The model is executable to: receive distillation and dehydration process information including biofuel compositions, receive an objective for biofuel production output from the distillation and dehydration processes, e.g., target product composition, production rate, and/or feed rate, and generate model output comprising target values for a plurality of manipulated variables related to the distillation and dehydration processes in accordance with the objective. The controller is operable to dynamically control the biofuel production process by adjusting the plurality of manipulated variables to the model-determined target values in accordance with the objective for biofuel production.Type: GrantFiled: September 27, 2007Date of Patent: August 27, 2013Assignee: Rockwell Automation Technologies, Inc.Inventors: Celso Axelrud, Maina A. Macharia, Michael E. Tay
-
Patent number: 8019701Abstract: System and method for modeling a nonlinear process. A combined model for predictive optimization or control of a nonlinear process includes a nonlinear approximator, coupled to a parameterized dynamic or static model, operable to model the nonlinear process. The nonlinear approximator receives process inputs, and generates parameters for the parameterized dynamic model. The parameterized dynamic model receives the parameters and process inputs, and generates predicted process outputs based on the parameters and process inputs, where the predicted process outputs are useable to analyze and/or control the nonlinear process. The combined model may be trained in an integrated manner, e.g.Type: GrantFiled: April 30, 2008Date of Patent: September 13, 2011Assignee: Rockwell Automation Technologies, IncInventors: Bijan Sayyar-Rodsari, Edward Plumer, Eric Hartman, Kadir Liano, Celso Axelrud
-
Patent number: 7599749Abstract: The present invention provides a method for controlling nonlinear control problems within particle accelerators. This method involves first utilizing software tools to identify variable inputs and controlled variables associated with the particle accelerator, wherein at least one variable input parameter is a controlled variable. This software tool is further operable to determine relationships between the variable inputs and controlled variables. A control system that provides variable inputs to and acts on controller outputs from the software tools tunes one or more manipulated variables to achieve a desired controlled variable, which in the case of a particle accelerator may be realized as a more efficient collision.Type: GrantFiled: February 26, 2007Date of Patent: October 6, 2009Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyarrodsari, Eric Hartman, Celso Axelrud, Kadir Liano
-
Publication number: 20080235166Abstract: System and method for modeling a nonlinear process. A combined model for predictive optimization or control of a nonlinear process includes a nonlinear approximator, coupled to a parameterized dynamic or static model, operable to model the nonlinear process. The nonlinear approximator receives process inputs, and generates parameters for the parameterized dynamic model. The parameterized dynamic model receives the parameters and process inputs, and generates predicted process outputs based on the parameters and process inputs, where the predicted process outputs are useable to analyze and/or control the nonlinear process. The combined model may be trained in an integrated manner, e.g.Type: ApplicationFiled: April 30, 2008Publication date: September 25, 2008Inventors: Bijan Sayyar-Rodsari, Edward Plumer, Eric Hartman, Kadir Liano, Celso Axelrud
-
Publication number: 20080103748Abstract: System and method for integrated management of a biofuel distillation process and a biofuel dehydration process of a biofuel production process, comprising a dynamic multivariate model-based controller coupled to a dynamic multivariate predictive model. The model is executable to: receive distillation and dehydration process information including biofuel compositions, receive an objective for biofuel production output from the distillation and dehydration processes, e.g., target product composition, production rate, and/or feed rate, and generate model output comprising target values for a plurality of manipulated variables related to the distillation and dehydration processes in accordance with the objective. The controller is operable to dynamically control the biofuel production process by adjusting the plurality of manipulated variables to the model-determined target values in accordance with the objective for biofuel production.Type: ApplicationFiled: September 27, 2007Publication date: May 1, 2008Inventors: Celso Axelrud, Maina A. Macharia, Michael E. Tay
-
Publication number: 20070198104Abstract: The present invention provides a method for controlling nonlinear control problems within particle accelerators. This method involves first utilizing software tools to identify variable inputs and controlled variables associated with the particle accelerator, wherein at least one variable input parameter is a controlled variable. This software tool is further operable to determine relationships between the variable inputs and controlled variables. A control system that provides variable inputs to and acts on controller outputs from the software tools tunes one or more manipulated variables to achieve a desired controlled variable, which in the case of a particle accelerator may be realized as a more efficient collision.Type: ApplicationFiled: February 26, 2007Publication date: August 23, 2007Inventors: Bijan Sayyarrodsari, Eric Hartman, Celso Axelrud, Kadir Liano
-
Patent number: 7184845Abstract: The present invention provides a method for controlling nonlinear control problems within particle accelerators. This method involves first utilizing software tools to identify variable inputs and controlled variables associated with the particle accelerator, wherein at least one variable input parameter is a controlled variable. This software tool is further operable to determine relationships between the variable inputs and controlled variables. A control system that provides variable inputs to and acts on controller outputs from the software tools tunes one or more manipulated variables to achieve a desired controlled variable, which in the case of a particle accelerator may be realized as a more efficient collision.Type: GrantFiled: December 9, 2003Date of Patent: February 27, 2007Assignee: Pavilion Technologies, Inc.Inventors: Bijan Sayyarrodsari, Eric Hartman, Celso Axelrud, Kadir Liano
-
Patent number: 7039475Abstract: The present invention provides a method for controlling nonlinear process control problems. This method involves first utilizing modeling tools to identify variable inputs and controlled variables associated with the process, wherein at least one variable input is a manipulated variable. The modeling tools are further operable to determine relationships between the variable inputs and controlled variables. A control system that provides inputs to and acts on inputs from the modeling tools tunes one or more manipulated variable inputs to achieve a desired result like greater efficiency, higher quality, or greater consistency.Type: GrantFiled: December 9, 2003Date of Patent: May 2, 2006Assignee: Pavilion Technologies, Inc.Inventors: Bijan Sayyarrodsari, Eric Hartman, Celso Axelrud, Kidir Liano
-
Publication number: 20050187643Abstract: System and method for modeling a nonlinear process. A combined model for predictive optimization or control of a nonlinear process includes a nonlinear approximator, coupled to a parameterized dynamic or static model, operable to model the nonlinear process. The nonlinear approximator receives process inputs, and generates parameters for the parameterized dynamic model. The parameterized dynamic model receives the parameters and process inputs, and generates predicted process outputs based on the parameters and process inputs, where the predicted process outputs are useable to analyze and/or control the nonlinear process. The combined model may be trained in an integrated manner, e.g.Type: ApplicationFiled: May 10, 2004Publication date: August 25, 2005Inventors: Bijan Sayyar-Rodsari, Edward Plumer, Eric Hartman, Kadir Liano, Celso Axelrud
-
Patent number: 6934931Abstract: A system and method for performing modeling, prediction, optimization, and control, including an enterprise wide framework for constructing modeling, optimization, and control solutions. The framework includes a plurality of base classes that may be used to create primitive software objects. These objects may then be combined to create optimization and/or control solutions. The distributed event-driven component architecture allows much greater flexibility and power in creating, deploying, and modifying modeling, optimization and control solutions. The system also includes various techniques for performing improved modeling, optimization, and control, as well as improved scheduling and control. For example, the system may include a combination of batch and continuous processing frameworks, and a unified hybrid modeling framework which allows encapsulation and composition of different model types, such as first principles models and empirical models.Type: GrantFiled: April 5, 2001Date of Patent: August 23, 2005Assignee: Pavilion Technologies, Inc.Inventors: Edward Stanley Plumer, Bijan Sayyar-Rodsari, Carl Anthony Schweiger, Ralph Bruce Ferguson, II, William Douglas Johnson, Celso Axelrud
-
Publication number: 20040130276Abstract: The present invention provides a method for controlling nonlinear control problems within particle accelerators. This method involves first utilizing software tools to identify variable inputs and controlled variables associated with the particle accelerator, wherein at least one variable input parameter is a controlled variable. This software tool is further operable to determine relationships between the variable inputs and controlled variables. A control system that provides variable inputs to and acts on controller outputs from the software tools tunes one or more manipulated variables to achieve a desired controlled variable, which in the case of a particle accelerator may be realized as a more efficient collision.Type: ApplicationFiled: December 9, 2003Publication date: July 8, 2004Inventors: Bijan Sayyarrodsari, Eric Hartman, Celso Axelrud, Kidir Liano
-
Publication number: 20040117040Abstract: The present invention provides a method for controlling nonlinear process control problems. This method involves first utilizing modeling tools to identify variable inputs and controlled variables associated with the process, wherein at least one variable input is a manipulated variable. The modeling tools are further operable to determine relationships between the variable inputs and controlled variables. A control system that provides inputs to and acts on inputs from the modeling tools tunes one or more manipulated variable inputs to achieve a desired result like greater efficiency, higher quality, or greater consistency.Type: ApplicationFiled: December 9, 2003Publication date: June 17, 2004Inventors: Bijan Sayyarrodsari, Eric Hartman, Celso Axelrud, Kidir Liano
-
Patent number: 6718234Abstract: A system for on line inference and control of physical and chemical properties of polypropylene and its copolymers is described. The system comprises models for the inference of physical and chemical properties that are not continuously measured and relevant models to control these properties as well as production rate, density of the reaction medium and other process variables of interest. The described control system allows to maximize production rate as well as catalyst yield in the producing process.Type: GrantFiled: December 4, 2001Date of Patent: April 6, 2004Assignee: Braskem S.A.Inventors: Esdras Piraguacy Demoro, Autur Toledo Martins De Oliveira, Celso Axelrud
-
Publication number: 20010049595Abstract: A system and method for performing modeling, prediction, optimization, and control, including an enterprise wide framework for constructing modeling, optimization, and control solutions. The framework includes a plurality of base classes that may be used to create primitive software objects. These objects may then be combined to create optimization and/or control solutions. The distributed event-driven component architecture allows much greater flexibility and power in creating, deploying, and modifying modeling, optimization and control solutions. The system also includes various techniques for performing improved modeling, optimization, and control, as well as improved scheduling and control. For example, the system may include a combination of batch and continuous processing frameworks, and a unified hybrid modeling framework which allows encapsulation and composition of different model types, such as first principles models and empirical models.Type: ApplicationFiled: April 5, 2001Publication date: December 6, 2001Inventors: Edward Stanley Plumer, Bijan Sayyar-Rodsari, Carl Anthony Schweiger, Ralph Bruce Ferguson, William Douglas Johnson, Celso Axelrud