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    DETERMINING CAUSAL MODELS FOR CONTROLLING ENVIRONMENTS
    4.
    发明申请
    DETERMINING CAUSAL MODELS FOR CONTROLLING ENVIRONMENTS 有权

    公开(公告)号：US20220146988A1

    公开(公告)日：2022-05-12

    申请号：US17438677

    申请日：2019-09-11

    Applicant: 3M INNOVATIVE PROPERTIES COMPANY

    Inventor： Brian E. Brooks ,  Gilles J. Benoit ,  Peter O. Olson ,  Tyler W. Olson ,  Himanshu Nayar ,  Frederick J. Arsenault ,  Nicholas A. Johnson

    IPC: G05B13/02

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes identifying a procedural instance; determining a temporal extent for the procedural instance based on temporal extent parameters for the one or more entities in the procedural instance; selecting control settings for the procedural instance; monitoring environment responses to the control settings that are received for the one or more entities; determining which of the environment responses to attribute to the procedural instance in a causal model; and adjusting, based at least in part on the environment responses that are attributed to the procedural instance, the temporal extent parameters for the one or more entities.

    DETERMINING CAUSAL MODELS FOR CONTROLLING ENVIRONMENTS
    5.
    发明申请
    DETERMINING CAUSAL MODELS FOR CONTROLLING ENVIRONMENTS 有权

    公开(公告)号：US20220128955A1

    公开(公告)日：2022-04-28

    申请号：US17438725

    申请日：2019-09-11

    Applicant: 3M INNOVATIVE PROPERTIES COMPANY

    Inventor： Gilles J. Benoit ,  Brian E. Brooks ,  Peter O. Olson ,  Tyler W. Olson ,  Himanshu Nayar ,  Frederick J. Arsenault ,  Nicholas A. Johnson

    IPC: G05B13/02 ,  G05B23/02 ,  G06N5/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting, by a control system for the environment, control settings for the environment based on internal parameters of the control system, wherein: at least some of the control settings for the environment are selected based on a causal model, and the internal parameters include a first set of internal parameters that define a number of previously received performance metric values that are used to generate the causal model for a particular controllable element; obtaining, for each selected control setting, a performance metric value; determining that generating the causal model for the particular controllable element would result in higher system performance; and adjusting, based on the determining, the first set of internal parameters.

    METHOD OF PERFORMING A PROCESS AND OPTIMIZING CONTROL SIGNALS USED IN THE PROCESS
    10.
    发明申请
    METHOD OF PERFORMING A PROCESS AND OPTIMIZING CONTROL SIGNALS USED IN THE PROCESS 有权

    公开(公告)号：US20220155733A1

    公开(公告)日：2022-05-19

    申请号：US17433069

    申请日：2019-09-11

    Applicant: 3M INNOVATIVE PROPERTIES COMPANY

    Inventor： Brian E. Brooks ,  Gilles J. Benoit ,  Peter O. Olson ,  Tyler W. Olson ,  Himanshu Nayar ,  Frederick J. Arsenault ,  Nicholas A. Johnson

    IPC: G05B13/04

    Abstract: A method of performing a process using a plurality of control signals and resulting in a plurality of measurable outcomes is described. The method includes optimizing the plurality of control signals by at least: receiving a plurality of process constraints; receiving, for each measurable outcome, an optimum range; receiving, for each control signal, a plurality of potential optimum values; iteratively performing the process, where for each process iteration, the value of each control signal is selected from among the plurality of potential optimum values received for the control signal; for each process iteration, measuring each outcome in the plurality of measurable outcomes; and generating confidence intervals for the control signals to determine a causal relationship between the control signals and the measurable outcomes. The method includes performing the process using at least the control signals determined by the causal relationship to causally affect at least one of the measurable outcomes.

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