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.
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;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712803