METHOD OF PERFORMING A PROCESS AND OPTIMIZING CONTROL SIGNALS USED IN THE PROCESS

    公开(公告)号:US20220155733A1

    公开(公告)日:2022-05-19

    申请号:US17433069

    申请日:2019-09-11

    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.

    TUNING PID PARAMETERS USING CAUSAL MODELS

    公开(公告)号:US20220137565A1

    公开(公告)日:2022-05-05

    申请号:US17431792

    申请日:2019-10-03

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing parameters of one or more proportional-integral-derivative (PID) controllers. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of respective PID parameters for each of the plurality of PID controllers, based on a causal model that measures causal relationships between PID parameters and a measure of success in controlling the system; ii) determining the measure of success of the configuration of respective PID parameters for the plurality of PID controllers in controlling the system; and iii) adjusting, based on the measure of success of the configuration of respective PID parameters for the plurality of PID controllers in controlling the system, the causal model.

    Causal analytics for powertrain management

    公开(公告)号:US11040721B2

    公开(公告)日:2021-06-22

    申请号:US16753188

    申请日:2018-11-27

    Abstract: Methods for management of a powertrain system in a vehicle. The methods receive data or signals from multiple sensors associated with the vehicle. Optimum thresholds for classifications of the sensor data can be changed based injecting signals into the powertrain system and receiving responsive signals. Expected priorities for the sensor signals can be altered based upon attributes of the signals and confirming actual priorities for the signals. Look-up tables for engine management can be modified based upon injecting signals into the powertrain system and measuring a utility of the responsive signals. The methods can thus dynamically alter and modify data for powertrain management, such as look-up tables, during vehicle operation under a wide range of conditions.

    CAUSAL ANALYTICS FOR POWERTRAIN MANAGEMENT

    公开(公告)号:US20210070313A1

    公开(公告)日:2021-03-11

    申请号:US16753188

    申请日:2018-11-27

    Abstract: Methods for management of a powertrain system in a vehicle. The methods receive data or signals from multiple sensors associated with the vehicle. Optimum thresholds for classifications of the sensor data can be changed based injecting signals into the powertrain system and receiving responsive signals. Expected priorities for the sensor signals can be altered based upon attributes of the signals and confirming actual priorities for the signals. Look-up tables for engine management can be modified based upon injecting signals into the powertrain system and measuring a utility of the responsive signals. The methods can thus dynamically alter and modify data for powertrain management, such as look-up tables, during vehicle operation under a wide range of conditions.

    SYSTEMS AND METHODS FOR SUPERVISION OF LOCAL ANALYTICS

    公开(公告)号:US20200019128A1

    公开(公告)日:2020-01-16

    申请号:US16335280

    申请日:2017-11-03

    Abstract: Systems and methods for dynamically optimizing models used for sensor data analytics. An action is taken based on an analytics determination by systematically varying parameters of the analytical model using actions taken based on the analytics to determine the relative frequencies of hits, misses, false alarms, and correct rejections for particular model parameters. The model parameters for local analytics are selected based upon on signal detection theory analysis and the value or cost of each hit, miss, false alarm, or correct rejection.

    IDENTIFICATION OF LOW-EFFICACY PATIENT POPULATION

    公开(公告)号:US20180322959A1

    公开(公告)日:2018-11-08

    申请号:US15773207

    申请日:2016-10-28

    CPC classification number: G16H70/20 G06F19/00 G06Q10/10 G06Q50/22 G16H50/70

    Abstract: A method of evaluating a plurality of patient protocols associated with a medical context, the method including, with a computer system, accessing a database including medical information for a plurality of patients associated with the medical context items. For each of the patients, the medical information includes an indication that one of the patient protocols is associated with the patient. The method further includes, with the computer system, evaluating each of the patient protocols based on medical information associated with patients within a patient population, the patient population representing a subset of the patients, to estimate an efficacy of each of the patient protocols for the patient population, and identifying the patient population represents a low-efficacy patient population based on the efficacy estimates for the patient population. The method further includes storing, within the database, an indication that the patient population represents the low-efficacy patient population.

Patent Agency Ranking