News
Interviews on Cutting Edge Motion Control and Positioning Technologies
POSTED 07/18/2023
The latest developments in motion control, automation and nanopositioning were presented at the 2023 LASER World of Photonics conference in Munich, Germany, at the PI booth.
Watch the five technology leadership talks here
Machine Learning - Learning Algorithms
How is it possible to overcome the limitations of feedback and feedforward-based control? PI's Israeli subsidiary ACS is focusing its research about controllers on learning algorithms. Using machine learning, the controller software should independently transfer knowledge from all previous motions to future tasks, therefore preventing known errors.
New Controller Architecture
Developers will also report on the status of PI’s future controller architecture. This will cover various drive and sensor technologies, software solutions, operating modes, and communication standards. PI engineers are paying particular attention to customizing the architecture to meet individual application needs, rapid commissioning, and programming.
Magnetic Levitation
Magnetic levitation deals with contactless stages supported solely by magnetic fields and freely positionable in space in six degrees of freedom. In combination with special drive and sensor technologies, this technology should enable resolutions down to the picometer range with high dynamics and without generating particles.
Active Damping and Vibration Compensation
To improve exploiting the potential of high-precision positioning technologies, it is necessary to damp or compensate vibrations in mechanical setups. A smart actuator and drive concept for active damping and vibration compensation will be presented with the aim of developing solutions for demanding scientific and industrial applications.
Surface Shaping
Another focus of research is the high-resolution active shaping of optical component or substrate surfaces. Combining different actuator designs, modes of operation, and arrangements enables amplitudes and deformations with smallest feature sizes and high dynamics.