Linear Motion with Machine Learning

Aug. 25, 2023
Using Beckhoff’s TwinCAT Cogging Compensation software, AL8000 linear motors can increase machine synchronization and decrease lag rate without hardware changes.

Beckhoff’s AL8000 linear motors can now deliver greater accuracy and synchronization with the company’s new TwinCAT Cogging Compensation software. According to Beckhoff, this software enables linear motors to be used in high-precision applications such as milling machines or laser cutting.

Beckhoff explains that cogging forces in linear motors are caused by the magnetic attraction between the iron core in the primary part and the permanent magnets in the secondary part. When cogging of the motor occurs, applications with extremely high accuracy and synchronization requirements can only be executed to a limited extent. With the TwinCAT Cogging Compensation software, the AL8000 linear motor compensates for the cogging forces. The software does this by accounting for magnetic effects as well as other factors related to mechanical design or energy chains.

The software makes use of machine learning, which is integrated into TwinCAT and applied automatically. Here’s how it works: The software independently records the necessary cogging data in the application as part of a reference run over the entire length of the linear motor’s magnetic track. With the help of the data acquired, the software trains a neural network, which ultimately integrates into the control system for current pre-control.

Beckhoff says that, by adapting the current pre-control in this way, the software can reduce the lag error by up to a factor of seven and increase synchronization of the machine by up to a factor of five without any hardware changes to the AL8000.

See this video featuring Fabian Bause explaining Beckhoff’s incorporation of machine learning into TwinCAT.

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