APPLICATION DRIVEN ENHANCEMENT TO INDUSTRIAL AUTOMATION DEVICE VIA CONTAINER IMPLEMENTATION

    公开(公告)号:US20240103455A1

    公开(公告)日:2024-03-28

    申请号:US17950894

    申请日:2022-09-22

    CPC classification number: G05B11/01 G05B15/02

    Abstract: An industrial automation device includes first processing circuitry configured to perform a first set of operations associated with controlling the industrial automation device or one or more industrial automation devices communicatively coupled to the industrial automation device. The industrial automation device includes input/output circuitry communicatively couplable to an electronic device having second processing circuitry that is configured to execute computer-readable instructions to execute a software container and receive, in the software container, data from the industrial automation device, the one or more industrial automation devices, or both. The second processing circuitry executes the computer-readable instructions to perform, using the software container, a second set of operations associated with controlling the industrial automation device or the one or more industrial automation devices. The second processing circuitry is also executes the computer-readable instructions to adjust an operation of the industrial automation device based on the second set of operations.

    ADVANCED CONTROL SYSTEMS FOR MACHINES
    8.
    发明申请

    公开(公告)号:US20190250569A1

    公开(公告)日:2019-08-15

    申请号:US16388119

    申请日:2019-04-18

    Abstract: Machines can be controlled using advanced control systems that implement an automated version of singular spectrum analysis (SSA). For example, a control system can perform SSA on a time series having one or more time-dependent variables by: generating a trajectory matrix from the time series, performing singular value decomposition on the trajectory matrix to determine elementary matrices; and categorizing the elementary matrices into groups. The elementary matrices can be automatically categorized into the groups by: generating one or more w-correlation matrices based on spectral components associated with the time series, determining w-correlation values based on the one or more w-correlation matrices; categorizing the w-correlation values into a predefined number of w-correlation sets, and forming the groups based on the predefined number of w-correlation sets. The control system can then generate a predictive forecast using the groups and control operation of a machine using the predictive forecast.

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