Siemens Aktiengesellschaft

Siemens Industry Software Nv

Technische Universitát Dresden

Andrés Botero Halblaub

Dragan Obradovic

Hermann Georg Mayer

Ingo Thon

Tim Schenk

Till Heinzerling

Jan Christoph Wehrstedt

Jan Richter

Harald Held

Heiko Patzlaff

Mathias Maurmaier

Jan Götz

Jan Fischer

Andreas Stutz

Leon Urbas

Christoph Wincheringer

Stephan Hensel

Jonathan Maedler

Anselm Klose

Veronica Brandstetter

Markus Graube

Matthias Herz

Wilhelm Oswald

Veronika Brandstetter

Manuel Röhrl

A method and a device for configuring a controller and to a method and a controller for controlling a technical system by means of a data-based control model is provided, in particular a model based on reinforcement learning. This data-based control model is configured using a model-predictive control model. Configuration parameters of the data-based control model are set by mapping the model-predictive control model onto the data-based control model in such a way that the data-based control model reproduces the output data of the model predictive control model depending on state data of the technical system read in, and determines optimized control parameters configured in this way. A computationally intensive training procedure for configuring the data-based control model can thus be avoided.

Controlling a technical system by data-based control model

A method and an apparatus for generating sensor data for controlling an autonomous vehicle in an environment is provided, such as driverless transport vehicles in a factory for example. Sensor positions of static sensors and the sensors of autonomous vehicles are defined in a global coordinate system on the basis of an environment model, such as a BIM model for example. Sensor data is centrally generated in this global coordinate system for all sensors as a function of these sensor positions. The sensor data is then transformed into a local coordinate system of an autonomous vehicle and transferred for controlling the autonomous vehicle.

Sensor data generation for controlling an autonomous vehicle

A method including a) receiving a computer generated data set of sequencing constraints describing a software system to be executed on an automation system and including software components and runnable function entities distributed over the number of computing nodes; b) generating a transition matrix from the data set of sequencing constraints, the transition matrix having a plurality of matrix elements each of them describing, by a transition value, a transition from a runnable function entity to another runnable function entity; c) receiving a computer generated communication matrix describing communication links between the computing nodes in the automation system; d) generating a Markov chain out of the data set of sequencing constraints and the communication matrix; e) generating a distribution function from the Markov chain describing used resources of the computing nodes by the software components and runnable function entities; and f) optimizing the allocation of resources.

Optimized allocation of resources to nodes of an automation system based on monte carlo simulation

To automate alarm management in modular production installations, provided is, with respect to a modular production installation, for which, for its modular, manufacturer-independent construction and operation, 'process equipment assembly' modules, controlled by a programmable PEA controller and simulated by means of a configurable PEA simulation, are integrated into the production installation, by means of a “module type package <MTP>” mechanism for the PEA module description, in the course of a process orchestration which is standardized the following is carried out in the alarm management: —all states of the modular production installation with respect to triggered faults of possible fault cases of the production installation are virtually run through and simulated; —simulation faults that occur are logged concomitantly by means of alarms, which provide identification and an alarm message log is created and/or alarm chains are identified and alarm relationships in the alarm chains are determined.

Method and system for managing alarms in modular production installations

The invention relates to a method for producing a test data record () for an algorithm (), comprising the following steps: 1.1 a trained artificial intelligence () is provided. 1.2 the artificial intelligence () is stimulated, particularly using a random signal () and/or using a quasi linearity property for visual concepts, and 1.3 the artificial intelligence () produces at least one test data record (), which comprises image data () and action regions () associated with the image data () and/or sensor data and action regions associated with the sensor data. The invention furthermore relates to a method for operating a system for the automated, image-dependent control of a device and an apparatus for carrying out the aforementioned method. Finally, the invention relates to a control system for a device which comprises such an apparatus, and a computer program product, a computer-readable medium, the production of a data storage device and the use of an artificial intelligence ().

Method for producing a test data record, method for testing, method for operating a system, apparatus, control system, computer program product, computer-readable medium, production and use

A method and a device for the computer-assisted simulation of a modular technical system, wherein for each real module of the modular technical system, a corresponding virtual module is generated, is provided. The virtual module includes a controller for controlling a module-specific process and at least one module-specific simulation model, to which model type information is assigned, for simulating the model-specific process. The virtual module is designed to simulate the module-specific process that is controlled by the controller by means of the module-specific simulation model and/or the controller of the real module, and is provided for a computer-assisted simulation of the modular technical system as a data container. In particular, the following allows a virtual start-up of modular process systems.

Method and apparatus for computer aided simulation of a modular technical system

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Kirchseeon, Germany

Andrés Botero Halblaub