Abstract
Piezo-stepper actuators are used in many nanopositioning systems due to their high resolution, high stiffness, fast response, and the ability to position a mover over an infinite stroke by means of motion reminiscent of walking. The aim of this paper is to develop a control approach for attenuating disturbances that are caused by the walking motion and are therefore repeating in the commutation-angle domain. A new iterative learning control approach is developed for the commutation-angle domain, that addresses the iteration-varying and non-equidistant sampling that occurs when the piezo-stepper actuator is driven at varying drive frequencies by parameterizing the input and error signals. Experimental validation of the framework on a piezo-stepper actuator leads to significant performance improvements.
Original language | English |
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Pages (from-to) | 8585-8590 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 53 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2020 |
Event | 21st World Congress of the International Federation of Aufomatic Control (IFAC 2020 World Congress) - Berlin, Germany Duration: 12 Jul 2020 → 17 Jul 2020 Conference number: 21 https://www.ifac2020.org/ |
Keywords
- Feedforward control
- Iterative learning control
- Micromechantronic systems
- Motion control systems
- Piezo actuators