Title :
Adaptive Neural Control for a Class of Perturbed Time-delay Nonlinear Systems
Author :
Wang, Ruliang ; Li, Jie
Author_Institution :
Comput. & Inf. Eng. Coll., Guangxi Teachers Educ. Univ., Nanning, China
Abstract :
In this paper, an adaptive neural control for a class of time-delay nonlinear systems with perturbed is posed, Based on radius basis function(RBF)neural networks, The radius basis function (RBF) neural networks is employed to estimate the unknown continuous functions. It is shown that the proposed method guarantees the semi-globally uniformly ultimately bounded ness of all signals in the adaptive closed-loop systems. Simulation results are provided to illustrate the performance of the proposed approach.
Keywords :
adaptive control; closed loop systems; delays; neurocontrollers; nonlinear control systems; perturbation techniques; radial basis function networks; adaptive closed loop systems; adaptive neural control; perturbed time delay nonlinear systems; radius basis function neural networks; semiglobally uniformly ultimately boundedness; Adaptive systems; Delay; Educational institutions; Neural networks; Nonlinear systems; Robustness; Vectors; Adaptive control; Nonlinear; RBF neural networks; Time-delay;
Conference_Titel :
Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
Conference_Location :
Hainan
Print_ISBN :
978-1-4577-2008-6
DOI :
10.1109/CIS.2011.86
