Letters: Adaptive neural control for a class of output feedback time delay nonlinear systems

Authors:
Qing Zhu;Tianping Zhang;Shumin Fei;Kanjian Zhang;Tao Li
Affiliations:
College of Information Engineering, Yangzhou University, Jiangsu, Yangzhou 225009, China;College of Information Engineering, Yangzhou University, Jiangsu, Yangzhou 225009, China;School of Automation, Southeast University, Jiangsu, Nanjing 210096, China;School of Automation, Southeast University, Jiangsu, Nanjing 210096, China;School of Automation, Southeast University, Jiangsu, Nanjing 210096, China
Venue:
Neurocomputing
Year:
2009

Citing 11
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Abstract

An output feedback control scheme combined with backstepping, radial basis function (RBF) neural networks, and adaptive control is proposed for the stabilization of nonlinear system with input delay and disturbances. A filter and a virtual observer are constructed to substitute the immeasurable system state. By using state transformation, the original system is converted to the system without input delay. Neural networks are employed to estimate the unknown continuous functions. The control scheme ensures that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB).