Intelligent control using a neuro-fuzzy network
نویسندگان
چکیده
Intelligent control techniques have emerged to overcome some deeciencies in conventional control methods in dealing with complex real-world systems. These problems include knowledge adaptation, learning, and expert knowledge incorporation. In this paper, a hybrid network that combines fuzzy inferencing and neu-ral networks is used to model and to control complex dynamic systems. The network takes advantage of the learning algorithms developed for neural networks to generate the knowledge base used in fuzzy inferenc-ing. The network is used to model and to control a robot arm with exible pneumatic actuator. Comparison with a nonlinear control technique used for the robot joints is also presented.
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