Robust feedback passivity via dynamic neural networks

In this paper we propose a novel feedback passive controller which uses a two-neuro dynamic neural network. It is robust for a wide class of nonlinear systems with a priory incomplete model description. By means of a Lyapunov-like analysis, both identification and passivation effects are guaranteed. Based on this neuro model we design an feedback passive controller. The example illustrate the effectiveness of the suggested approach.