Secure models for model-based control and optimization

    公开(公告)号:US10359767B2

    公开(公告)日:2019-07-23

    申请号:US15051372

    申请日:2016-02-23

    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.

    OPTIMIZATION-BASED CONTROL WITH OPEN MODELING ARCHITECTURE SYSTEMS AND METHODS

    公开(公告)号:US20170205813A1

    公开(公告)日:2017-07-20

    申请号:US14995977

    申请日:2016-01-14

    Abstract: 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.

    OPTIMIZATION BASED CONTROLLER TUNING SYSTEMS AND METHODS

    公开(公告)号:US20170205809A1

    公开(公告)日:2017-07-20

    申请号:US14996008

    申请日:2016-01-14

    Abstract: One embodiment of the present disclosure describes an industrial system, which includes a control system that controls operation of an industrial process by instructing an automation component in the industrial system to implement a manipulated variable setpoint. The control system includes a process model that model operation of the industrial process, control optimization that determines the manipulated variable setpoint based at least in part on the process model, a control objective function, and constraints on the industrial process, in which the control objective function includes a tuning parameter that describes weighting between aspects of the industrial process affected by the manipulated variable setpoint; and tuning optimization circuitry that determines the tuning parameter based at least in part on a tuning objective function, in which the tuning objective function is determined based at least in part on a closed form solution to an augmented version of the control objective function, which includes the constraints as soft constraints.

    Deterministic optimization based control system and method for linear and non-linear systems
    24.
    发明授权
    Deterministic optimization based control system and method for linear and non-linear systems 有权
    基于确定性优化的线性和非线性系统的控制系统和方法

    公开(公告)号:US09448546B2

    公开(公告)日:2016-09-20

    申请号:US13838315

    申请日:2013-03-15

    CPC classification number: G05B13/047

    Abstract: The embodiments described herein include one embodiment that provides a control method including determining a linear approximation of a pre-determined non-linear model of a process to be controlled, determining a convex approximation of the nonlinear constraint set, determining an initial stabilizing feasible control trajectory for a plurality of sample periods of a control trajectory, executing an optimization-based control algorithm to improve the initial stabilizing feasible control trajectory for a plurality of sample periods of a control trajectory, and controlling the controlled process by application.

    Abstract translation: 本文描述的实施例包括提供控制方法的一个实施例,包括确定待控制的过程的预定非线性模型的线性近似,确定非线性约束集的凸近似,确定初始稳定可行控制轨迹 对于控制轨迹的多个采样周期,执行基于优化的控制算法,以改善控制轨迹的多个采样周期的初始稳定可行控制轨迹,并通过应用控制受控过程。

    ONLINE INTEGRATION OF MODEL-BASED OPTIMIZATION AND MODEL-LESS CONTROL
    25.
    发明申请
    ONLINE INTEGRATION OF MODEL-BASED OPTIMIZATION AND MODEL-LESS CONTROL 审中-公开
    基于模型优化和模型控制的在线整合

    公开(公告)号:US20160170393A1

    公开(公告)日:2016-06-16

    申请号:US15051402

    申请日:2016-02-23

    CPC classification number: G05B19/045 G05B13/042 G05B17/02 G05B2219/25273

    Abstract: In certain embodiments, a control system includes a model-less controller configured to control operation of a plant or process. The control system also includes a model-based controller that includes a model of the plant or process being controlled by the model-less controller. The model-based controller is configured to modify parameters of the model-less controller.

    Abstract translation: 在某些实施例中,控制系统包括被配置为控制设备或过程的操作的无模型控制器。 控制系统还包括基于模型的控制器,其包括由无模型控制器控制的工厂或过程的模型。 基于模型的控制器配置为修改无模型控制器的参数。

    Sequential Deteministic Optimization Based Control System and Method
    26.
    发明申请
    Sequential Deteministic Optimization Based Control System and Method 审中-公开
    基于阶段性知觉优化的控制系统和方法

    公开(公告)号:US20140280301A1

    公开(公告)日:2014-09-18

    申请号:US13836701

    申请日:2013-03-15

    CPC classification number: G06F17/30979 G05B13/047 G06F17/11

    Abstract: The embodiments described herein include one embodiment that a control method including executing an infeasible search algorithm during a first portion of a predetermined sample period to search for a feasible control trajectory of a plurality of variables of a controlled process, executing a feasible search algorithm during a second portion of the predetermined sample period to determine the feasible control trajectory if the infeasible search algorithm does not determine a feasible control trajectory, and controlling the controlled process by application of the feasible control trajectory.

    Abstract translation: 本文描述的实施例包括一个实施例,其包括在预定采样周期的第一部分期间执行不可行搜索算法以搜索受控过程的多个变量的可行控制轨迹的控制方法,在一 如果不可行搜索算法没有确定可行的控制轨迹,并通过应用可行的控制轨迹来控制受控过程,则确定可行的控制轨迹。

    SECURE MODELS FOR MODEL-BASED CONTROL AND OPTIMIZATION
    27.
    发明申请
    SECURE MODELS FOR MODEL-BASED CONTROL AND OPTIMIZATION 有权
    基于模型控制和优化的安全模型

    公开(公告)号:US20140128996A1

    公开(公告)日:2014-05-08

    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。

    Automated Monitoring Using Image Analysis

    公开(公告)号:US20250095131A1

    公开(公告)日:2025-03-20

    申请号:US18961848

    申请日:2024-11-27

    Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving image data after an operation is performed by an industrial automation device on a product; analyzing the image data based an object-based image analysis (OBIA) model to classify the product as one of a plurality of conditions related to manufacturing quality and the OBIA model includes property layers associated with features related to a manufacturing of the product; determining whether the one of the conditions indicates an anomaly being present in the product; sending a notification indicative of the one of the plurality of conditions is presently associated with the product; identifying a property layer associated with classifying the one of the plurality of conditions; and updating the OBIA model based on the property layer and the input indicative of the anomaly being incorrectly associated with the product.

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