Robust output feedback controller for discrete-time nonlinear systems based on standard neural network model

Neural networks and T-S fuzzy systems have been widely used in nonlinear system control. Standard neural network model (SNNM) can be used to describe intelligent systems composed of neural networks or T-S fuzzy models, and so provides a common controller synthesis framework for these kinds of systems. This paper investigates robust output feedback controller synthesis of discrete-time nonlinear systems based on SNNM. A new output feedback controller design technique for discrete-time SNNM in terms of linear matrix inequality is proposed. The aforementioned intelligent systems can be transformed into SNNM for controller synthesis in a unified way. The numerical example and simulation result show that the presented method is effective and provide a new approach to the nonlinear system controller synthesis.