Abstract
This paper investigates the problem of robust passivity and passification for a class of singularly perturbed nonlinear systems (SPNS) with time-varying delays and polytopic uncertainties via neural networks. By constructing a proper functional and the linear matrix inequalities (LMIs) technique, some novel sufficient conditions are derived to make SPNS passive. The allowable perturbation bound ξ ∗ can be determined via certain algebra inequalities, and the proposed controller based on neural network will make SPNS with polytopic uncertainties passive for all ξ∈(0,ξ ∗). Finally, a numerical example is given to illustrate the theoretical results.
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The work is supported by the Natural Science Foundation of China under Grants 60974021 and 61125303, the 973 Program of China under Grant 2011CB710606, the Fund for Distinguished Young Scholars of Hubei Province under Grant 2010CDA081, and National Priority Research Project NPRP 4-451-2-168, funded by Qatar National Research Fund.
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Wen, S., Zeng, Z., Huang, T. et al. Robust Passivity and Passification for a Class of Singularly Perturbed Nonlinear Systems with Time-Varying Delays and Polytopic Uncertainties via Neural Networks. Circuits Syst Signal Process 32, 1113–1127 (2013). https://doi.org/10.1007/s00034-012-9509-8
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DOI: https://doi.org/10.1007/s00034-012-9509-8