Adaptive Neural Control of Uncertain Nonlinear Systems Using Disturbance Observer.
IEEE Trans Cybern
; 47(10): 3110-3123, 2017 Oct.
Article
en En
| MEDLINE
| ID: mdl-28362599
This paper studies the problem of prescribed performance adaptive neural control for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems in the presence of external disturbances and input saturation based on a disturbance observer. The system uncertainties are tackled by neural network (NN) approximation. To handle unknown disturbances, a Nussbaum disturbance observer is presented. By incorporating the disturbance observer and NNs, an adaptive prescribed performance neural control scheme is further developed. Then, the expected asymptotically convergent tracking errors between system output signals and desired signals are achieved. Numerical simulation results demonstrate the effectiveness of the proposed control scheme.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Redes Neurales de la Computación
/
Dinámicas no Lineales
Idioma:
En
Revista:
IEEE Trans Cybern
Año:
2017
Tipo del documento:
Article
Pais de publicación:
Estados Unidos