Name
Title | ||
|---|---|---|
Accommodating Trial-Varying Tasks In Iterative Learning Control For Lpv Systems, Applied To Printer Sheet Positioning |
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. |
Year | Venue | Field |
|---|---|---|
2018 | 2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | Feedforward systems,Nonlinear system,Task analysis,Control theory,Computer science,Radio frequency,Control engineering,Basis function,Iterative learning control,Trajectory |
DocType | ISSN | Citations |
Conference | 0743-1619 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robin de Rozario | 1 | 2 | 1.07 |
| Remy Pelzer | 2 | 0 | 0.34 |
| Sjirk H. Koekcbakker | 3 | 0 | 0.34 |
| Oomen, T. | 4 | 95 | 17.42 |