Second order sliding mode for MIMO nonlinear uncertain systems based on a neural identifier

Author

Alanis, Alma Y. ; Sanchez, Edgar N.

Author_Institution

Dept. de Cienc. Computacionales, Univ. de Guadalajara, Zapopan, Mexico

fYear

2010

Firstpage

1

Lastpage

6

Abstract

This paper deals with adaptive tracking for discrete-time nonlinear systems in presence of disturbances. A high order neural network structure is used to identify the plant model and based on this model, a discrete-time high order sliding mode, control law is derived. The paper also includes the respective stability analysis, for the whole system with a strategy. In order to show the applicability of the proposed scheme, simulation results are included for a Van der Pol oscillator.

Keywords

MIMO systems; discrete time systems; neural nets; nonlinear systems; stability; uncertain systems; variable structure systems; MIMO nonlinear uncertain systems; adaptive tracking; discrete-time nonlinear systems; high order neural network structure; neural identifier; second order sliding mode; stability analysis; Adaptation model; Algorithm design and analysis; Artificial neural networks; Kalman filters; Nonlinear systems; Sliding mode control; Training; Discrete-time nonlinear systems; Discrete-time second order sliding modes; Extended Kalman filtering learning; Neural control;

fLanguage

English

Publisher

ieee

Conference_Titel

World Automation Congress (WAC), 2010

Conference_Location

Kobe

ISSN

2154-4824

Print_ISBN

978-1-4244-9673-0

Electronic_ISBN

2154-4824

Type

conf

Filename

5665637