Abstract: This study is concerned with the design and development of a simple fuzzy system for modeling of ill-defined dynamical systems. This system, which is represented as a feed forward neural network, is able to incorporate qualitative and quantitative information. Supervised linear back propagation learning algorithm has been applied to model a system through identifying the fuzzy parameters. This adaptive fuzzy system is implemented as an identifier of dynamical systems. The system performance has been evaluated for different simulated systems to demonstrate the application of the proposed system to identify the dynamics of linear and nonlinear time-invariant and time-variant systems.
Dr. Kasim M. Al-Aubidy and Mr. Salam A. Al-Ani , 2004. Neural-Network-Based Fuzzy Identifier: Design and Evaluation . Asian Journal of Information Technology, 3: 188-196.