Comparative Study of Fuzzy Control, Neural Network Control and Neuro-Fuzzy Control

The goal of this work is to compare fuzzy, neural network and neuro-fuzzy approaches to the control of mobile robots. The first part of this paper is devoted to the formal framework of fuzzy controllers. Results of an example of their use for a mobile robot are discussed. As an experimental platform, the Khepera mobile robot is used. The same example is studied using artificial neural networks. For that purpose, fundamentals of artificial neural networks are outlined. Similarities and differences between fuzzy systems and neural networks are discussed as well as the respective advantages and drawbacks, and reasons for merging these two approaches are developed. Three models of fuzzy neurons, the learning methods and an architecture of neuro-fuzzy controller are presented. A learning procedure for the controller is described. To conclude, the application of a neuro-fuzzy controller on Khepera is discussed.

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