Robust Adaptive Control via Neural Linearization and Compensation
We propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a neural identifier-based feedback linearization controller is first used. Dead-zone and projection techniques are applied to assure the stability of neural identification. Then fo...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2012/867178 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850172605564190720 |
|---|---|
| author | Roberto Carmona Rodríguez Wen Yu |
| author_facet | Roberto Carmona Rodríguez Wen Yu |
| author_sort | Roberto Carmona Rodríguez |
| collection | DOAJ |
| description | We propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a neural identifier-based feedback linearization controller is first used. Dead-zone and projection techniques are applied to assure the stability of neural identification. Then four types of compensator are addressed. The stability of closed-loop system is also proven. |
| format | Article |
| id | doaj-art-d0b224fd40ae4d619898e3dfd8da0185 |
| institution | OA Journals |
| issn | 1687-5249 1687-5257 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-d0b224fd40ae4d619898e3dfd8da01852025-08-20T02:20:02ZengWileyJournal of Control Science and Engineering1687-52491687-52572012-01-01201210.1155/2012/867178867178Robust Adaptive Control via Neural Linearization and CompensationRoberto Carmona Rodríguez0Wen Yu1Departamento de Control Automatico, CINVESTAV-IPN, Avenue.IPN 2508, 07360 Mexico City, DF, MexicoDepartamento de Control Automatico, CINVESTAV-IPN, Avenue.IPN 2508, 07360 Mexico City, DF, MexicoWe propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a neural identifier-based feedback linearization controller is first used. Dead-zone and projection techniques are applied to assure the stability of neural identification. Then four types of compensator are addressed. The stability of closed-loop system is also proven.http://dx.doi.org/10.1155/2012/867178 |
| spellingShingle | Roberto Carmona Rodríguez Wen Yu Robust Adaptive Control via Neural Linearization and Compensation Journal of Control Science and Engineering |
| title | Robust Adaptive Control via Neural Linearization and Compensation |
| title_full | Robust Adaptive Control via Neural Linearization and Compensation |
| title_fullStr | Robust Adaptive Control via Neural Linearization and Compensation |
| title_full_unstemmed | Robust Adaptive Control via Neural Linearization and Compensation |
| title_short | Robust Adaptive Control via Neural Linearization and Compensation |
| title_sort | robust adaptive control via neural linearization and compensation |
| url | http://dx.doi.org/10.1155/2012/867178 |
| work_keys_str_mv | AT robertocarmonarodriguez robustadaptivecontrolvianeurallinearizationandcompensation AT wenyu robustadaptivecontrolvianeurallinearizationandcompensation |