Abstract
In this paper, a robust stability analysis method for feedback linearization using neural networks is presented. The robust regulation problem of nonlinear system with external disturbance is considered. The feedforward neural networks with one hidden layer are used to approximate the uncertain nonlinear system. The approximation errors are treated as the structured uncertainties with the known bounds. For these external disturbance and structured uncertainties, stability robustness of the closed system is analyzed in both input-output sense and Lyapunov sense.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lee, JB., Park, CW., Sung, HG. (2006). Robust Stability of Nonlinear Neural-Network Modeled Systems. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_59
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DOI: https://doi.org/10.1007/11881070_59
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