Passivity and Passification for a Class of Singularly Perturbed Nonlinear Systems via Neural Networks
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abstract
This paper is concerned with the problem of passivity and passification for a class of singularly perturbed nonlinear systems (SPNS) via neural network. By constructing a proper functional as well as the linear matrix inequalities (LMIs) technique, some novel sufficient conditions are derived to make SPNS passive. The allowable perturbation bound * can be determined via certain algebra inequalities, the proposed controller based on neural network will make SPNS passive for all (0, *). Finally, a numerical example is given to illustrate the theoretical results. 2012 IEEE.
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The 2012 International Joint Conference on Neural Networks (IJCNN)