Passivity and passification for a class of singularly perturbed nonlinear systems via neural networks

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 ξ* can be determined via certain algebra inequalities, the proposed controller based on neural network will make SPNS passive for all ξ* ∈ (0, ξ*). Finally, a numerical example is given to illustrate the theoretical results.