DocumentCode
2727485
Title
Neural Networks Variable Structure Control for Nonlinear Time-delay Systems Based on Robust Control
Author
Shao, Keyong ; Gao, Hongyu ; Yu, Xianli ; Yang, Yuanyuan ; Zhang, Huizhen ; Liu, Sheng
Author_Institution
Sch. of Electr. & Inf. Eng., Daqing Pet. Inst.
Volume
1
fYear
0
fDate
0-0 0
Firstpage
2461
Lastpage
2464
Abstract
Combined neural networks, sliding model variable structure control with robust Hinfin control theory, the control problems of complex systems were studied. A new control strategy is proposed for a class of nonlinear time-delay systems. By adding a neural networks sliding model compensate controller, this scheme can guarantee the systems, which have uncertain terms and disturbance, to be stable. Made use of nonlinear approximate ability of neural networks, the control problems of complex systems - existing unrestricted nonlinear disturbance is solved very well. Compared with the existing the research findings, this control scheme has better adaptivity and robustness. The simulation results indicate that the controller is effective
Keywords
Hinfin control; delays; large-scale systems; neurocontrollers; nonlinear control systems; robust control; uncertain systems; variable structure systems; complex systems; neural network sliding model compensate controller; neural network variable structure control; nonlinear time-delay systems; robust Hinfin control theory; sliding model variable structure control; unrestricted nonlinear disturbance; Automatic control; Automation; Control systems; Control theory; Electric variables control; Linear matrix inequalities; Neural networks; Nonlinear control systems; Robust control; Sliding mode control; Robust; adaptivity; neural networks; nonlinear time-delay systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1712803
Filename
1712803
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