Relaxed fuzzy Lyapunov approach for dynamic local model networks

This paper deals with the problem of stability analysis of dynamic local model networks. Established methods in this context are mainly based on Lyapunov stability theory and are targeted to be as little conservative as possible. In this respect it is essential to take into account the transitions between the different local models. For that purpose this paper presents and discusses a method to determine possible model transitions of such dynamic local model networks utilizing identification or simulation data. The effectiveness of the proposed method is shown by a simulation example in connection with the fuzzy Lyapunov approach as a stability criterion. The example demonstrates how identification data can be used to reduce the conservatism compared to standard approaches.