Method and control device for controlling a technical system

    公开(公告)号:US11340564B2

    公开(公告)日:2022-05-24

    申请号:US16466355

    申请日:2017-12-05

    IPC分类号: G05B13/04 G05B13/02

    摘要: In order to control a technical system, a system state of the technical system is continually detected. By a trained first control model, a subsequent state of the technical system is predicted on the basis of a sensed system state. Then, a distance value is determined for a distance between the predicted subsequent state and an actually occurring system state. Furthermore, a second control model is trained by the trained first control model to predict the distance value on the basis of a sensed system state and on the basis of a control action for controlling the technical system. A subsequent state predicted by the first control model is then modified on the basis of a distance value predicted by the trained second control model. The modified subsequent state is output in order to control the technical system.

    CALIBRATION OF A CAMERA PROVIDED FOR MONITORING AN ADDITIVE MANUFACTURING PROCESS

    公开(公告)号:US20220157346A1

    公开(公告)日:2022-05-19

    申请号:US17602003

    申请日:2020-03-26

    摘要: A method for the calibration of a camera for monitoring additive manufacturing of an object in which material is applied in a plurality of layers is provided. The method includes: a) providing the camera and providing means for additive manufacturing of the object, b) capturing an image of the object being manufactured or already manufactured by the camera, c) comparing the image captured with a model of the object, d) determining a calibration function on the basis of the comparison from step c), which is intended to transform the image captured into a corrected image, wherein the corrected image of the object substantially corresponds to the model of the object, and e) calibrating the camera by the calibration function. Also provided is a computer program comprising commands which, when executed by a computer, cause the computer to execute the steps of the method as well as a related apparatus.

    Controlling a target system
    5.
    发明授权

    公开(公告)号:US10747184B2

    公开(公告)日:2020-08-18

    申请号:US15376794

    申请日:2016-12-13

    IPC分类号: G06N5/04 G05B13/02

    摘要: For controlling a target system, e.g. a gas or wind turbine or another technical system, a pool of control policies is provided. The pool of control policies comprising a plurality of control policies and weights for weighting each of the plurality of control policies are received. The plurality of control policies is weighted by the weights to provide a weighted aggregated control policy. With that, the target system is controlled using the weighted aggregated control policy, and performance data relating to a performance of the controlled target system are received. Furthermore, the weights are adjusted on the basis of the received performance data to improve the performance of the controlled target system. With that, the plurality of control policies is reweighted by the adjusted weights to adjust the weighted aggregated control policy.

    CLASSIFICATION MODEL FOR CONTROLLING A MANUFACTURING PROCESS

    公开(公告)号:US20220198287A1

    公开(公告)日:2022-06-23

    申请号:US17604584

    申请日:2020-03-31

    IPC分类号: G06N5/02 G05B19/418

    摘要: Controlling a manufacturing process by a computer-generated classification model is provided. This is combined with a reward system based on a distributed ledger and smart contracts. The classification model is trained by: Providing data entities being indicative of a property of a manufacturing of a product. Acquiring labels for each of the data entities from an agent. Determining labeling metrics based on the acquiring of the agent. Training the classification model, wherein the training set includes the data entities and their labels. Validating the trained classification model yielding a classifier score. Training a labeling score model based on the data entities, the respective labels, the labeling metrics and the classifier score. Determining a labeling score for the agent based on the labeling score model, the labels and the set of labeling metrics.