Name
Abstract | ||
|---|---|---|
In this paper, we are dealing with the problem of controlling an unknown nonlinear dynamical system. The algorithm is divided into two phases. First a dynamical neural network identifier is employed to perform “black box” identification and then a dynamic state feedback is developed to appropriately control the unknown system. We apply the algorithm to control the speed of a nonlinearized DC motor, giving in this way an application insight. In the algorithm, not all the plant states are assumed to be available for measurement |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1109/21.278990 | Systems, Man and Cybernetics, IEEE Transactions |
Keywords | Field | DocType |
adaptive control,feedback,neural nets,nonlinear control systems,state-space methods,adaptive control,black box identification,dynamic state feedback,dynamical neural networks,nonlinearized DC motor,unknown nonlinear dynamical system | Black box (phreaking),Identifier,Control theory,Computer science,DC motor,Robustness (computer science),Adaptive control,System identification,Artificial neural network,Dynamical system | Journal |
Volume | Issue | ISSN |
24 | 3 | 0018-9472 |
Citations | PageRank | References |
172 | 33.44 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| George A. Rovithakis | 1 | 581 | 52.21 |
| manolis a christodoulou | 2 | 461 | 59.94 |