A Comparison of Neural Network and Fuzzy Logic Control Systems

Neural network and fuzzy logic control systems share many common characteristics and properties. They can be implemented into Practical applications either independently or in combined network topologies. This paper will compare and constrast their differences with emphasis on control system applications. It will also consider some of the benefits that can be derived by integrating the two network configurations into combined systems. The combination of systems resonbles an adaptive system with sensory and cognitive components as the neural perameter estimators embed directly in an overall fuzzy architecture.