Robust Stability Analysis for Indirect Neural Adaptive Control
نویسندگان
چکیده
This paper investigates robust adaptive control for unknown nonlinear systems with fully connected recurrent neural networks. On-line weights updating law and closed loop performance are derived from the Lyapunov approach. Mathematical proof for the robust stability under the parametric uncertainties due to disturbances of the overall system is provided. This analysis is concerned by combining Lyapunov approach and linearization around the nominal parameters to establish analytical sufficient conditions for the global robust stability of adaptive neural network controller. Advantages of the proposed algorithm are suggested according to simulation examples. Copyright © 2006 USTARTH
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تاریخ انتشار 2006