Resumen
A new online identification method is presented. The identified nonlinear systems have partial-state measurement. Their inner states, parameters and structures are unknown. The design is based on the combination of a model-free state observer and a neuro identifier. First, a sliding mode observer, which does not need any information about the nonlinear system, is applied to obtain the full states. A dynamic multilayer neural network is then used to identify the whole nonlinear system. The main contributions of the paper are: a new observer-based identification algorithm is proposed; and a stable learning algorithm for the neuro identifier is given.
Idioma original | Inglés |
---|---|
Páginas (desde-hasta) | 145-152 |
Número de páginas | 8 |
Publicación | IEE Proceedings: Control Theory and Applications |
Volumen | 147 |
N.º | 2 |
DOI | |
Estado | Publicada - 2000 |
Publicado de forma externa | Sí |