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1. 发明授权

US08019701B2 Training a model of a non-linear process 有权
标题翻译：训练非线性过程的模型
公开(公告)号：US08019701B2
公开(公告)日：2011-09-13
申请号：US12112750
申请日：2008-04-30
申请人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celso Axelrud
发明人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celso Axelrud
IPC分类号： G06N5/00
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： 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., substantially concurrently, by identifying process inputs and outputs (I/O), collecting data for process I/O, determining constraints on model behavior from prior knowledge, formulating an optimization problem, executing an optimization algorithm to determine model parameters subject to the determined constraints, and verifying the compliance of the model with the constraints.
摘要翻译：用于建模非线性过程的系统和方法。用于非线性过程的预测优化或控制的组合模型包括耦合到参数化动态或静态模型的非线性近似器，可操作以对非线性过程建模。非线性近似器接收过程输入，并为参数化动态模型生成参数。参数化动态模型接收参数和过程输入，并根据参数和过程输入生成预测过程输出，其中预测过程输出可用于分析和/或控制非线性过程。组合模型可以通过识别过程输入和输出（I / O），收集过程I / O的数据，确定来自先验知识的模型行为的约束，制定优化问题，以基本上同时的方式进行训练，执行优化算法以确定受限于确定的模型参数，并验证模型与约束的一致性。

2. 发明申请

US20080235166A1 TRAINING A MODEL OF A NON-LINEAR PROCESS 有权
标题翻译：培养非线性过程的模型
公开(公告)号：US20080235166A1
公开(公告)日：2008-09-25
申请号：US12112750
申请日：2008-04-30
申请人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celso Axelrud
发明人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celso Axelrud
IPC分类号： G06F15/18
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： 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., substantially concurrently, by identifying process inputs and outputs (I/O), collecting data for process I/O, determining constraints on model behavior from prior knowledge, formulating an optimization problem, executing an optimization algorithm to determine model parameters subject to the determined constraints, and verifying the compliance of the model with the constraints.
摘要翻译：用于建模非线性过程的系统和方法。用于非线性过程的预测优化或控制的组合模型包括耦合到参数化动态或静态模型的非线性近似器，可操作以对非线性过程建模。非线性近似器接收过程输入，并为参数化动态模型生成参数。参数化动态模型接收参数和过程输入，并根据参数和过程输入生成预测过程输出，其中预测过程输出可用于分析和/或控制非线性过程。组合模型可以通过识别过程输入和输出（I / O），收集过程I / O的数据，确定来自先验知识的模型行为的约束，制定优化问题，以基本上同时的方式进行训练，执行优化算法以确定受限于确定的模型参数，并验证模型与约束的一致性。

3. 发明申请

US20050187643A1 Parametric universal nonlinear dynamics approximator and use 审中-公开
标题翻译：参数通用非线性动力学近似和使用
公开(公告)号：US20050187643A1
公开(公告)日：2005-08-25
申请号：US10842157
申请日：2004-05-10
申请人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celso Axelrud
发明人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celso Axelrud
IPC分类号： G05B13/02 , G05B13/04 , G05B17/02 , G06F15/18
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： 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., substantially concurrently, by identifying process inputs and outputs (I/O), collecting data for process I/O, determining constraints on model behavior from prior knowledge, formulating an optimization problem, executing an optimization algorithm to determine model parameters subject to the determined constraints, and verifying the compliance of the model with the constraints.
摘要翻译：用于建模非线性过程的系统和方法。用于非线性过程的预测优化或控制的组合模型包括耦合到参数化动态或静态模型的非线性近似器，可操作以对非线性过程建模。非线性近似器接收过程输入，并为参数化动态模型生成参数。参数化动态模型接收参数和过程输入，并根据参数和过程输入生成预测过程输出，其中预测过程输出可用于分析和/或控制非线性过程。组合模型可以通过识别过程输入和输出（I / O），收集过程I / O的数据，确定来自先验知识的模型行为的约束，制定优化问题，以基本上同时的方式进行训练，执行优化算法以确定受限于确定的模型参数，并验证模型与约束的一致性。

4. 发明申请

US20080208778A1 CONTROLLING A NON-LINEAR PROCESS 审中-公开
标题翻译：控制非线性过程
公开(公告)号：US20080208778A1
公开(公告)日：2008-08-28
申请号：US12112847
申请日：2008-04-30
申请人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celson Axelrud
发明人： Bijan Sayyar-Rodsari , Edward Plumer , Eric Hartman , Kadir Liano , Celson Axelrud
IPC分类号： G06F15/18 , G05B13/02
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： 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., substantially concurrently, by identifying process inputs and outputs (I/O), collecting data for process I/O, determining constraints on model behavior from prior knowledge, formulating an optimization problem, executing an optimization algorithm to determine model parameters subject to the determined constraints, and verifying the compliance of the model with the constraints.
摘要翻译：用于建模非线性过程的系统和方法。用于非线性过程的预测优化或控制的组合模型包括耦合到参数化动态或静态模型的非线性近似器，可操作以对非线性过程建模。非线性近似器接收过程输入，并为参数化动态模型生成参数。参数化动态模型接收参数和过程输入，并根据参数和过程输入生成预测过程输出，其中预测过程输出可用于分析和/或控制非线性过程。组合模型可以通过识别过程输入和输出（I / O），收集过程I / O的数据，确定来自先验知识的模型行为的约束，制定优化问题，以基本上同时的方式进行训练，执行优化算法以确定受限于确定的模型参数，并验证模型与约束的一致性。

5. 发明授权

US06934931B2 System and method for enterprise modeling, optimization and control 有权
标题翻译：企业建模，优化与控制的系统与方法
公开(公告)号：US06934931B2
公开(公告)日：2005-08-23
申请号：US09827838
申请日：2001-04-05
申请人： Edward Stanley Plumer , Bijan Sayyar-Rodsari , Carl Anthony Schweiger , Ralph Bruce Ferguson, II , William Douglas Johnson , Celso Axelrud
发明人： Edward Stanley Plumer , Bijan Sayyar-Rodsari , Carl Anthony Schweiger , Ralph Bruce Ferguson, II , William Douglas Johnson , Celso Axelrud
IPC分类号： G05B13/02 , G06F9/44 , G06F9/45 , G06Q10/00
CPC分类号： G06Q10/04 , G06Q10/00 , G06Q10/06
摘要： 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. The system further includes an integrated process scheduling solution referred to as process coordinator that seamlessly incorporates the capabilities of advanced control and execution into a real time event triggered optimal scheduling solution.
摘要翻译：一种用于执行建模，预测，优化和控制的系统和方法，包括用于构建建模，优化和控制解决方案的企业范围框架。框架包括可用于创建原始软件对象的多个基类。然后可以将这些对象组合以创建优化和/或控制解决方案。分布式事件驱动组件架构在创建，部署和修改建模，优化和控制解决方案方面提供了更大的灵活性和强大功能。该系统还包括用于执行改进的建模，优化和控制以及改进调度和控制的各种技术。例如，系统可以包括批处理和连续处理框架的组合，以及允许封装和组合不同模型类型的统一的混合建模框架，诸如第一原理模型和经验模型。该系统还包括被称为过程协调器的集成过程调度解决方案，其将高级控制和执行的能力无缝地结合到实时事件触发的最优调度解决方案中。

6. 发明授权

US09141098B2 Integrated optimization and control for production plants 有权
标题翻译：生产工厂的综合优化与控制
公开(公告)号：US09141098B2
公开(公告)日：2015-09-22
申请号：US12609785
申请日：2009-10-30
申请人： Bijan Sayyar-Rodsari , Carl Anthony Schweiger
发明人： Bijan Sayyar-Rodsari , Carl Anthony Schweiger
IPC分类号： G05B13/04
CPC分类号： G05B13/04
摘要： The present invention provides novel techniques for optimizing and controlling production plants using parametric multifaceted models. In particular, the parametric multifaceted models may be configured to convert a first set of parameters (e.g., control parameters) relating to a production plant into a second set of parameters (e.g., optimization parameters) relating to the production plant. In general, the first set of parameters will be different than the second set of parameters. For example, the first set of parameters may be indicative of low-level, real-time control parameters and the second set of parameters may be indicative of high-level, economic parameters. Utilizing appropriate parameterization may allow the parametric multifaceted models to deliver an appropriate level of detail of the production plant within a reasonable amount of time. In particular, the parametric multifaceted models may convert the first set of parameters into the second set of parameters in a time horizon allowing for control of the process plant by a control system based on the second set of parameters.
摘要翻译：本发明提供使用参数多方面模型来优化和控制生产设备的新技术。特别地，参数多面模型可以被配置为将与生产设备相关的第一组参数（例如，控制参数）转换为与生产设备相关的第二组参数（例如，优化参数）。一般来说，第一组参数将与第二组参数不同。例如，第一组参数可以指示低级的实时控制参数，并且第二组参数可以指示高级的经济参数。使用适当的参数化可以允许参数多面模型在合理的时间内提供生产工厂的适当水平的细节。特别地，参数多方面模型可以在时间范围内将第一组参数转换为第二组参数，从而允许由控制系统基于第二组参数控制过程工厂。

7. 发明申请

US20090005889A1 MODEL PREDICTIVE CONTROL SYSTEM AND METHOD FOR REDUCTION OF STEADY STATE ERROR 有权
标题翻译：模型预测控制系统和减少稳态错误的方法
公开(公告)号：US20090005889A1
公开(公告)日：2009-01-01
申请号：US12147961
申请日：2008-06-27
申请人： Bijan Sayyar-Rodsari
发明人： Bijan Sayyar-Rodsari
IPC分类号： G05B13/02
CPC分类号： G05B13/048
摘要： A technique is disclosed for reducing an error in a controlled variable via model predictive control. A predicted error in the controlled variable is determined for a forward-looking control horizon based upon measured or computed variables. The integral of the predicted error is computed. If the error or the integral exceed a tolerance for a determined time period, the model predictive control algorithm is modified to drive the error or the integral to within a tolerance. The modifications to the control algorithm may include changes to coefficients for terms based upon the error and/or the integral of the error.
摘要翻译：公开了一种用于通过模型预测控制来减少受控变量中的误差的技术。基于测量或计算的变量，对于前瞻性控制水平确定控制变量中的预测误差。计算预测误差的积分。如果误差或积分超过确定的时间段的公差，则模型预测控制算法被修改以将误差或积分驱动到公差内。对控制算法的修改可以包括基于误差和/或误差的积分的用于术语的系数的改变。

8. 发明申请

US20120239164A1 GRAPHICAL LANGUAGE FOR OPTIMIZATION AND USE 有权
标题翻译：用于优化和使用的图形语言
公开(公告)号：US20120239164A1
公开(公告)日：2012-09-20
申请号：US13051793
申请日：2011-03-18
申请人： Alexander Barton Smith , Bijan Sayyar-Rodsari
发明人： Alexander Barton Smith , Bijan Sayyar-Rodsari
IPC分类号： G05B13/04
CPC分类号： G06Q10/067 , G05B13/047 , G06Q50/04 , G06Q50/06 , Y02P90/30
摘要： The present invention provides novel techniques for graphically modeling, displaying, and interacting with parametric hybrid models used to optimize and control components of industrial plants and enterprises. In particular, a graphical modeling tool of a control/optimization system for controlling a plant or enterprise is configured to transmit a graphical user interface to a user, wherein the graphical user interface enables a plurality of command inputs relating to a plurality of parametric hybrid models based on a security access level of the user. The parametric hybrid models may be displayed by the graphical user interface as nodes of a network with connections connecting the nodes. The user may graphically manipulate the nodes and connections associated with the parametric hybrids models to either modify optimization constraints of the model network, or actually modify the manner in which the parametric hybrid models function (e.g., inputs, outputs, parameters, and so forth, of the parametric hybrid models), depending on the access level of the user.
摘要翻译：本发明提供用于图形化建模，显示和与用于优化和控制工厂和企业部件的参数混合模型相互作用的新技术。特别地，用于控制工厂或企业的控制/优化系统的图形建模工具被配置为向用户传送图形用户界面，其中图形用户界面启用与多个参数混合模型相关的多个命令输入基于用户的安全访问级别。参数化混合模型可以由图形用户界面显示为具有连接节点的连接的网络的节点。用户可以图形地操纵与参数混合模型相关联的节点和连接，以修改模型网络的优化约束，或者实际上修改参数混合模型的功能（例如，输入，输出，参数等等）的参数混合模型），具体取决于用户的访问级别。

9. 发明申请

US20120116546A1 Model Predictive Control System and Method for Reduction of Steady State Error 审中-公开
标题翻译：模型预测控制系统和减少稳态误差的方法
公开(公告)号：US20120116546A1
公开(公告)日：2012-05-10
申请号：US13252029
申请日：2011-10-03
申请人： Bijan Sayyar-Rodsari
发明人： Bijan Sayyar-Rodsari
IPC分类号： G05B13/04
CPC分类号： G05B13/048
摘要： A technique is disclosed for reducing an error in a controlled variable via model predictive control. A predicted error in the controlled variable is determined for a forward-looking control horizon based upon measured or computed variables. The integral of the predicted error is computed. If the error or the integral exceed a tolerance for a determined time period, the model predictive control algorithm is modified to drive the error or the integral to within a tolerance. The modifications to the control algorithm may include changes to coefficients for terms based upon the error and/or the integral of the error.
摘要翻译：公开了一种用于通过模型预测控制来减少受控变量中的误差的技术。基于测量或计算的变量，对于前瞻性控制水平确定控制变量中的预测误差。计算预测误差的积分。如果误差或积分超过确定的时间段的公差，则模型预测控制算法被修改以将误差或积分驱动到公差内。对控制算法的修改可以包括基于误差和/或误差的积分的用于术语的系数的改变。

10. 发明授权

US08682635B2 Optimal self-maintained energy management system and use 有权
标题翻译：最优自保能源管理系统及使用
公开(公告)号：US08682635B2
公开(公告)日：2014-03-25
申请号：US12790488
申请日：2010-05-28
申请人： Bijan Sayyar-Rodsari
发明人： Bijan Sayyar-Rodsari
IPC分类号： G06F17/50
CPC分类号： H02J3/14 , Y02B70/3225 , Y04S20/222
摘要： The present invention provides novel techniques for controlling energy systems. In particular, parametric hybrid models may be used to parameterize inputs and outputs of groups of equipment of energy systems. Each parametric hybrid model may include an empirical model, a parameter model, and a dynamic model. Critical parameters for groups of equipment modeled by the parametric hybrid models, which are correlated with, but not the same as, input and output variables of the groups of equipment may be monitored during operation of the energy system. The critical parameters may be used to generate optimal trajectories for the energy system, which may be used to control the energy system.
摘要翻译：本发明提供了用于控制能量系统的新技术。特别地，可以使用参数混合模型来参数化能量系统设备组的输入和输出。每个参数混合模型可以包括经验模型，参数模型和动态模型。在能量系统运行期间，可以监测与参数化混合模型建模的设备组的关键参数，这些参数与设备组的输入和输出变量相关，但不一致。关键参数可用于为能量系统产生最佳轨迹，可用于控制能量系统。

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