Abstract
Many control applications are nonlinear and have to perform a range of different tasks. Iterative Learning Control (ILC) enables high performance for a single task, but is highly sensitive to task variations. The aim of this paper is to develop an ILC framework for Linear Parameter Varying (LPV) systems, which encompasses a large class of nonlinear systems, which allows for trial-varying reference signals. This is achieved by exploiting parameter varying basis functions, such that perfect tracking is enabled for LPV systems. The proposed approach is applied to a printer sheet positioning unit, thereby validating that the tracking performance is significantly enhanced with respect to existing approaches.
| Original language | English |
|---|---|
| Title of host publication | 2018 Annual American Control Conference, ACC 2018 |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 5213-5218 |
| Number of pages | 6 |
| ISBN (Print) | 9781538654286 |
| DOIs | |
| Publication status | Published - 9 Aug 2018 |
| Event | 2018 American Control Conference (ACC 2018) - Hilton Milwaukee City Center Hotel, Milwaukee, Wisconsin, United States Duration: 27 Jun 2018 → 29 Jun 2018 http://acc2018.a2c2.org/ |
Conference
| Conference | 2018 American Control Conference (ACC 2018) |
|---|---|
| Abbreviated title | ACC 2018 |
| Country/Territory | United States |
| City | Milwaukee, Wisconsin |
| Period | 27/06/18 → 29/06/18 |
| Internet address |
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