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Reach Unprecedented Levels of Motion Performance.

With Novel Learning-Based Control Algorithms.

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Surpassing the Limits of Conventional Control

Feedback- and feedforward-based control algorithms can achieve high levels of performance, but have fundamental limitations.

Tracking Error

Preventive Disturbance Compensation

Machine learning control algorithms for high-precision motion systems enable the pre-emptive compensation of disturbances and intelligent real-time optimization of feedback- and feedforward- control laws.

Tracking Error

Multiple Learning Modes for Higher Performance

Learning from different previous execution modes will allow for minimization of move-and-settle time and dynamic following errors, as well as maximization of stability over a wide range of operations.

Learning Based Motion Control software screen 1 PI
Learning Based Motion Control software screen 2 PI
Learning Based Motion Control software screen 3 PI
Laptop front
Learning Based Motion Control visual PI

Enter the next level of motion performance.

“What drove us was achieving motion performance others deemed impossible.”

Engineer Fabian Rudnick gives insights into the development process of PI's learning-based motion control for the future.

Driving Markets & Applications

Using control algorithms based on machine learning from previous executions will make it possible to avoid or compensate for repetitive errors. The accuracy of manufacturing or inspection processes in the fields of automation, semiconductors, photonics, and life sciences can thus be significantly improved.

Photonics market of PI Photonics
Semiconductor market of PI Semiconductor
Microscopy & Life Sciences market of PI Microscopy & Life Sciences
Industrial Automation market of PI Industrial Automation
Learning Based Motion Control visual PI

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We look forward to your projects and challenges to push the limits of what is technically possible together with you.