A system and method for conveyor configuration and testing. The system is configured to execute the method, which includes: receive input data relating to configuration of a conveyor system; prepare a simulation of the configured conveyor system; operate the simulation of the conveyor system; determine at least one operational parameter related to the conveyor system to be monitored; monitor the at least one operational parameter during operation of the simulation of the conveyor system; determine if the configuration of the conveyor system needs to be adjusted based on the monitored operational parameter; if the configuration needs to be adjusted, automatically make an adjustment and return to operate the simulation of the conveyor system; and continue the simulation until otherwise terminated. In some cases, the monitoring operational parameters uses a machine learning model based on actual data from operating conveyors.

Reusable information is extracted from a result of executing a simulation of a plurality of models. A simulation management method for managing data for use in a simulation by a management device having a processor and a memory, the method including: executing a simulation using a model and data, by a simulator; extracting intermediate data indicating that an internal state of the model that is being simulated matches a predetermined state, by the management device; and holding the extracted intermediate data as useful intermediate data, by the management device.

Method and system for validating a control program for an automation system, wherein the control program is created in a first controller programming language and is arranged and setup to control an apparatus or device of the automation system when executed by an automation controller of the automation system, where the system includes a controller environment for executing the control program, an equipment simulation environment for executing a simulation program for simulating behavior of the apparatus or device or parts thereof, whereas the equipment simulation environment is communicatively coupled to the controller environment to enable and/or perform a simulation of the automation system, and whereas the simulation program is created in the first controller programming language or a second controller programming language.

A computer-aided method for training an artificial neuronal network for the simulation of an environment sensor of a driver assistance system includes the following work steps: reading in traffic scenarios of a test journey; deriving test journey data and the sensor data to be output by the environment sensor from the traffic scenarios; generating a data stream which depicts the traffic scenarios from the perspective of the environment sensor; outputting the data stream such that the environment sensor can generate sensor data on the basis of the data stream and can provide same to a data interface at which the test journey data and the sensor data to be output are also provided; and reading the provided data into the artificial neuronal network.

The invention relates to a method for generating an executable simulation program and simulating control device communication (50) between a control device (10) to be tested and a further control device (20, 30, 40), the control device (10) to be tested having a description of its transmitting and receiving interfaces, and the method comprising the following steps: transferring the description of the transmitting and receiving interfaces to a database, identifying, by means of the database, the interfaces of the control device (10) to be tested from the description, generating a receiving interface element as a receiving interface of the one further control device for each identified transmitting interface of the control device to be tested, generating a transmitting interface element as a transmitting interface of the one further control device for each receiving interface of the control device to be tested, storing the generated interface elements (24, 26, 28, 34, 48) in the database, providing, by means of the database, a configuration for the simulation of control device communication (50), the configuration comprising the generated interface elements (24, 26, 28, 34, 48), generating an executable simulation program for control device communication (50) using the configuration.

In order to test an autonomous behavior controller for a technical system, the following are input: a machine model for physically simulating the technical system; an environment model modelling an environment of the technical system; as well as a disruption model modelling potential disruptions in the environment. Disruption data is generated by means of the disruption model, and the environment model is modified according to the disruption data. Environment-specifically simulated sensor data the technical system is then generated by means of the modified environment model and the machine model. According to the simulated sensor data, control data is generated for the technical system by the autonomous behavior controller. An operating behavior of the technical system induced by the control data is then simulated by means of the machine model. Furthermore, a performance value quantifying the operating behavior is determined and output as a test result.

An industrial simulation system exchanges data between a virtualized industrial system and an industrial controller at high frequencies and accuracies without the need for additional network emulation hardware. Rather than timing the sending of emulated device data packets from the simulation to the industrial controller using an operating system clock, the simulation system uses the arrival event of a data packet received from the industrial controller as the clock signal that drives the sending of data packets from the virtual system to the controller. Using the arrival time of data packets from the industrial controller as the clock signal rather than the system clock of the operating system can yield high accuracy, low jitter data exchanges during simulation.

The invention relates to a method for dynamic load simulation, wherein loads are specified by target signals and applied to a test object by a parallel kinematic excitation unit via an end effector, including the following operations: measuring loads at a contact point (200), comparing the measured loads with the target signals (300), and determining target pressures (400) for individual actuators of the parallel kinematic excitation unit for applying the target signals by use of a control algorithm (F.sub.q,ref). This provides a method for dynamic load simulation that reduces the time and cost expenditure compared to previously known methods and at the same time enables hardware-in-the-loop simulations to be used.

A system includes: a camera unit; a control unit; and a test setup for testing the control unit. The test setup comprises a processor and an image output unit. The processor is configured to manipulate image data to simulate an error of the camera unit and to output, on the image output unit, the manipulated image data in the form of an image detectable via camera optics. The camera unit is configured to detect, via the camera optics, the outputted image data simulating the error of the camera unit. The control unit is configured to receive, from the camera unit, camera image data simulating the error of the camera unit.

An electronic control unit (ECU) for transmitting large data in a hardware-in-the-loop (HiL) simulation environment, a system including the same and a method thereof are provided. The electronic control unit for executing a HiL simulation includes an interface transmitting/receiving data associated with a simulation in link with a hardware-in-the-loop (HiL) simulator, a data storing unit storing data generated by executing the simulation, and a transmission agent fragmenting the stored data into multiple data and transmitting the multiple data and transmitting one data segment according to a fragmented order whenever repeatedly executing the simulation.