Name
Title | ||
|---|---|---|
Enhancing Feedforward Controller Tuning Via Instrumental Variables: With Application To Nanopositioning |
Abstract | ||
|---|---|---|
Feedforward control enables high performance of a motion system. Recently, algorithms have been proposed that eliminate bias errors in tuning the parameters of a feedforward controller. The aim of this paper is to develop a new algorithm that combines unbiased parameter estimates with optimal accuracy in terms of variance. A simulation study is presented to illustrate the poor accuracy properties of pre-existing algorithms compared to the proposed approach. Experimental results obtained on an industrial nanopositioning system confirm the practical relevance of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1080/00207179.2016.1219921 | INTERNATIONAL JOURNAL OF CONTROL |
Keywords | Field | DocType |
Feedforward control, system identification, data-driven control, precision motion systems | Control theory,Control theory,Instrumental variable,Control engineering,Motion system,System identification,Mathematics,Feed forward | Journal |
Volume | Issue | ISSN |
90 | 4 | 0020-7179 |
Citations | PageRank | References |
4 | 0.46 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frank Boeren | 1 | 5 | 0.85 |
| Dennis Bruijnen | 2 | 24 | 5.59 |
| Oomen, T. | 3 | 95 | 17.42 |