| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 411207 | Neurocomputing | 2007 | 8 Pages |
Abstract
An adaptive inverse control algorithm is proposed by combining fast online support vector machine regression (SVR) algorithm with straight inverse control algorithm. Because training speed of standard online SVR algorithm is very slow, a kernel cache-based method is developed to accelerate the standard algorithm and a new fast online SVR algorithm is obtained. Then the new algorithm is applied in straight inverse control for constructing the inverse model of controlled system online, and output errors of the system are used to control online SVR algorithm, which made the whole control system a closed-loop one. Simulation results show that the new algorithm has good control performance.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hui Wang, Daoying Pi, Youxian Sun,