DocumentCode
3548809
Title
Neural Sliding Mode Control for Systems with Hysteresis
Author
Li, Chuntao ; Tan, Yonghong
Author_Institution
Coll. of Autom., Nanjing Univ. of Aeronaut. & Astronaut.
fYear
2005
fDate
27-29 June 2005
Firstpage
467
Lastpage
472
Abstract
In this paper, a neural network based sliding model control scheme for systems with unknown hysteresis is proposed. In the control scheme, a neural network model is utilized to describe the behavior of hysteresis. Comparing with the Preisach model, the proposed model can be easily adjusted on-line to adapt the change of operation conditions. Then, an adaptive neural sliding mode controller based on the proposed neural model is presented for a class of single-input nonlinear systems with unknown hysteresis non-linearity
Keywords
adaptive control; control nonlinearities; hysteresis; neurocontrollers; nonlinear control systems; variable structure systems; adaptive control; neural network model; neural sliding mode control; single-input nonlinear system; unknown hysteresis; Adaptive control; Extraterrestrial measurements; Hysteresis; Intelligent control; Inverse problems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Sliding mode control;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation
Conference_Location
Limassol
ISSN
2158-9860
Print_ISBN
0-7803-8936-0
Type
conf
DOI
10.1109/.2005.1467060
Filename
1467060
Link To Document