Name
Abstract | ||
|---|---|---|
This paper presents an Adaptive Predictive Control strategy based on Neural Networks for nonlinear systems. In order to train the Neural Network controller, an identification of the system is carried out by the Neural Network Identifier. This second Neural Network provides the training terms related to the nonlinear system dynamics. In this way it is possible to train the Neural Network controller online. The simulation results show a correct online adaptation of the NN controller and the validity of the proposed control strategy. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ETFA.2010.5641348 | 2010 IEEE CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA) |
Keywords | Field | DocType |
neural network,system identification,nonlinear systems,nonlinear system,adaptive control,mathematical model,artificial neural networks,predictive control,control systems,identification | Control theory,Control theory,Stochastic neural network,Recurrent neural network,Probabilistic neural network,Control engineering,Time delay neural network,Types of artificial neural networks,Adaptive control,Engineering,Artificial neural network | Conference |
ISSN | Citations | PageRank |
1946-0740 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mikel Larrea-Sukia | 1 | 2 | 0.71 |
| Eloy Irigoyen | 2 | 38 | 14.23 |
| Vicente Gómez | 3 | 0 | 0.68 |
| Fernando Artaza | 4 | 4 | 1.52 |