Secure models for model-based control and optimization

    公开(公告)号:US10852716B2

    公开(公告)日:2020-12-01

    申请号:US16447659

    申请日:2019-06-20

    Abstract: In certain embodiments, a control/optimization system includes an instantiated model object stored in memory on a model server. The model object includes a model of a plant or process being controlled. The model object comprises an interface that precludes the transmission of proprietary information via the interface. The control/optimization system also includes a decision engine software module stored in memory on a decision support server. The decision engine software module is configured to request information from the model object through a communication network via a communication protocol that precludes the transmission of proprietary information, and to receive the requested information from the model object through the communication network via the communication protocol.

    MULTI-ENGINE MODELING FOR MONITORING, DIAGNOSTICS, OPTIMIZATION AND CONTROL

    公开(公告)号:US20190102352A1

    公开(公告)日:2019-04-04

    申请号:US15720705

    申请日:2017-09-29

    Abstract: Modular analytics engines are provided for industrial automation applications. The engines may be instantiated on a data-driven basis, such as by receipt of a data structure comprising annotated data relating to a machine or process to be monitored and/or controlled. The modules may comprise, for example, modules for modeling the machine or process, classification modules, optimization modules, and control modules. Output of the modules may comprise data structures, and these may be used as inputs to the same type or different types of modules. Multiple of the modules may be instantiated at the same level in the machine or process, or at different levels, such as in a department, institution, factory, or enterprise.

    AUTOMATIC MODELING FOR MONITORING, DIAGNOSTICS, OPTIMIZATION AND CONTROL

    公开(公告)号:US20190101902A1

    公开(公告)日:2019-04-04

    申请号:US15720714

    申请日:2017-09-29

    Abstract: A modular modeling engine is provided for industrial automation applications. The module may be instantiated upon demand, such as upon receipt of annotated data for a system or process being monitored and/or controlled. The model is agnostic insomuch as little or no prior knowledge is required of the system or process. Variables, functions, and their combinations are selected and the model is refined automatically. A data structure is received for instantiation of the model, and following modeling, a similar data structure is produced. The module may be used together with other modules for caning out complex automation processing at the same or multiple levels in an automation setting.

    Predictive monitoring and diagnostics systems and methods

    公开(公告)号:US10073421B2

    公开(公告)日:2018-09-11

    申请号:US14943621

    申请日:2015-11-17

    Abstract: System and method for improving operation of an industrial automation system, which includes a control system that controls operation of an industrial automation process. The control system includes a feature extraction block that determines extracted features by transforming process data determined during operation of an industrial automation process based at least in part on feature extraction parameters; a feature selection block that determines selected features by selecting a subset of the extracted features based at least in part on feature selection parameters, in which the selected features are expected to be representative of the operation of the industrial automation process; and a clustering block that determines a first expected operational state of the industrial automation system by mapping the selected features into a feature space based at least in part on feature selection parameters.

    Secure models for model-based control and optimization
    66.
    发明授权
    Secure models for model-based control and optimization 有权
    用于基于模型的控制和优化的安全模型

    公开(公告)号:US09292012B2

    公开(公告)日:2016-03-22

    申请号:US13669165

    申请日:2012-11-05

    CPC classification number: G05B19/41885 G05B17/02 G05B2219/42155

    Abstract: In certain embodiments, a control/optimization system includes an instantiated model object stored in memory on a model server. The model object includes a model of a plant or process being controlled. The model object comprises an interface that precludes the transmission of proprietary information via the interface. The control/optimization system also includes a decision engine software module stored in memory on a decision support server. The decision engine software module is configured to request information from the model object through a communication network via a communication protocol that precludes the transmission of proprietary information, and to receive the requested information from the model object through the communication network via the communication protocol.

    Abstract translation: 在某些实施例中,控制/优化系统包括存储在模型服务器上的存储器中的实例化模型对象。 模型对象包括被控制的工厂或过程的模型。 模型对象包括通过接口排除专有信息传输的接口。 控制/优化系统还包括存储在决策支持服务器上的存储器中的决策引擎软件模块。 决策引擎软件模块被配置为经由通信协议通过通信网络从模型对象请求信息,该通信协议排除专有信息的传输,并且经由通信协议通过通信网络从模型对象接收所请求的信息。

    PARAMETRIC UNIVERSAL NONLINEAR DYNAMICS APPROXIMATOR AND USE
    67.
    发明申请
    PARAMETRIC UNIVERSAL NONLINEAR DYNAMICS APPROXIMATOR AND USE 审中-公开
    参数通用非线性动力学近似和使用

    公开(公告)号:US20150185717A1

    公开(公告)日:2015-07-02

    申请号:US14659003

    申请日:2015-03-16

    CPC classification number: G05B13/048 G05B13/042 G05B17/02

    Abstract: 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.

    Abstract translation: 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。

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