Abstract
Hysteresis phenomena can significantly deteriorate the performance when performing servo tasks with piezo-electric actuators. The aim of this paper is to model this non-linear hysteresis effect using a memory element, in particular a MEM-element, and exploit this model to develop a feedforward controller. A one-to-one mapping is established, leading to both a systematic data-driven learning approach of a hybrid-MEM-element capturing the hysteresis phenomena and a unique inverse allowing for an intuitive design of the feedforward controller. The developed approach is experimentally validated on a piezoelectric actuator, revealing a significant performance improvement.
| Original language | English |
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| Title of host publication | 59th IEEE Conference on Decision and Control (CDC 2020) |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 934-939 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728174471 |
| DOIs | |
| Publication status | Published - 11 Jan 2021 |
| Event | 59th IEEE Conference on Decision and Control, CDC 2020 - Virtual/Online, Virtual, Jeju Island, Korea, Republic of Duration: 14 Dec 2020 → 18 Dec 2020 Conference number: 59 https://cdc2020.ieeecss.org/ |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
|---|---|
| Volume | 2020-December |
| ISSN (Print) | 0743-1546 |
| ISSN (Electronic) | 2576-2370 |
Conference
| Conference | 59th IEEE Conference on Decision and Control, CDC 2020 |
|---|---|
| Abbreviated title | CDC |
| Country/Territory | Korea, Republic of |
| City | Virtual, Jeju Island |
| Period | 14/12/20 → 18/12/20 |
| Internet address |