Design of T-S Fuzzy & RBF Controller and Application in Monitoring System Optimization

Structural safety monitoring system uses an array of sensors to continuously monitor a structure to provide an early indication of problems such as damage to the structure from fatigue, corrosion or impact. The system is a large sensor network containing about two hundred nodes, each of which contains multiple sensors. So the sensor fault diagnosis is getting more and more important. A fuzzy-neural method is suggested in this paper. Based on the function equivalence between T-S fuzzy inference and RBF network, a kind of fuzzy neural controller based on RBF network with full-net structure is put forward. This paper proposes a real code GA to optimize all factors including scaling factors, membership functions and fuzzy rules. The RBF network with two inputs-one output model is used as fuzzy controller, the result of the simulation illustrates that the controller has good dynamic performance and strong robust.