An adaptive teleoperate mobile robot controller based on fuzzy neural network

Fuzzy logic and neural networks have gained increased attention as methodologies of control system for managing uncertainty. There is computational equivalence between fuzzy logic and neural network systems. A new model of fuzzy neural network is built. Furthermore, the approach of fuzzy neural network is applied to solving the problem of autonomous control for a teleoperated mobile robot in an unknown environment. The new approach increases the learning speed, fine adjusts the rules, and improves the quality of the system.