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Next-gen multi-core motion control avoids limitations
Beckhoff has unveiled a new generation of its TwinCat motion control technology that takes advantage of the latest multi-core and multitasking processing technologies to overcome some of the limitations of earlier generations. At the SPS exhibition in Germany, the company also demonstrated how it is using chatbots to simplify engineering.
Beckhoff has been selling its TwinCat software control platform for more than 25 years and more than half of all applications involve motion control. But, until now, these applications have been limited to a single processor core and could only execute a single task at a time. Applications using the previous NC2 generation have also been limited to a maximum of 255 axes.
With the new modular MC3 generation, these limitations no longer apply. The software can be distributed to several CPU cores with movements synchronised across all of the cores. In addition, axes can operate on the same CPU core at different cycle times, depending on their speed and function. This optimises the use of the core because the fastest axis no longer sets the rate for all of the others.
There is no longer any limit on the number of axes that can be controlled.
TwinCat MC3 can operate in parallel with earlier NC2 systems, and MC3 axes can be coupled to existing NC2 axes. This means that new machine components can be added without having to adapt existing components.
Also at SPS, Beckhoff was showing the latest capabilities of its TwinCAT Chat bot that it announced at the Hannover Fair earlier this year. Large language models (LLMs) such as ChatGPT from OpenAI can now be used to develop projects in the TwinCat XAE engineering environment, simplifying aspects from control programming to corporate management.
For automation engineers, LLMs could revolutionise the development process by generating and completing code automatically, thus saving time. They can also create personal tutorials and help to solve problems.
The models can also help to transfer knowledge in organisations. They can act as a central knowledge base, storing information and making it available when needed. Another potential function is to relieve pressure on support teams by acting as the first point of contact for customer inquiries.
Beckhoff says that TwinCat Chat offers benefits over using ChatGPT in a Web browser. For example, it greatly simplifies the development process, by integrating communications and code exchange.
Beckhoff has tailored LLM initialisation specifically to deal with TwinCat requests. You can ask it questions and don’t need to tell the model that you are using TwinCat, or that you expect code in Structured Text. The generated code can be transferred easily, saving time and avoiding errors that can occur when moving code manually.
Simple pre-tested one-click requests can be used to improve workflows. Beckhoff is working on new uses for TwinCat Chat, including creating HMI controls automatically, and as an interface for documents.
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