Name
Abstract | ||
|---|---|---|
This paper presents a modeling approach to control a vehicle by visual feedback and H∞ control; this approach is based on two models designed using a closed-loop identification. The models are constructed from data for a curved path and straight path. Closed-loop identifications such as Closed-loop subspace model identification method (CL-MOESP) have been proposed recently and validated through simulations. However, consideration based experimental data have rarely been studied. We investigate the most effective identification approach of a vehicle model by experimental data. The most useful vehicle identification using visual feedback control is CL-MOESP. To evaluate its effectiveness, we use the fitting rate (FIT). Next, we design a robust controller based on the constructed models. Specifically, we formulate a model error for each models based on the curved and straight paths and use an H∞ control algorithm for the vehicle controller within a given error. A nominal plant is regarded as the model given by the curve data. The model error is estimated as the difference between the models given by the straight and curved paths. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.3182/20130703-3-FR-4038.00126 | IFAC Proceedings Volumes |
Field | DocType | Volume |
Errors-in-variables models,Control algorithm,Control theory,Subspace topology,Experimental data,Vehicle identification,Control theory,Engineering,System identification,Robust control | Conference | 46 |
Issue | ISSN | Citations |
11 | 1474-6670 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Syunya Kato | 1 | 0 | 0.34 |
| Yuki Igarashi | 2 | 5 | 1.21 |
| K Hidaka | 3 | 3 | 2.58 |