The construction of rule-base for a nonlinear time-varying system becomes much more complicated because of model uncertainty and parameter variation. Futhermore, fuzzy controller is not able to adjust the rule-base with according to any sudden changes...
The construction of rule-base for a nonlinear time-varying system becomes much more complicated because of model uncertainty and parameter variation. Futhermore, fuzzy controller is not able to adjust the rule-base with according to any sudden changes of the control environment. To overcome such problems, an auto-tuning method for fuzzy rule-base is required.
In this paper, we design the fuzzy-neural network controller. In order to evaluate the performance of the controller, this system was applied to the speed control of a DC servo motor. The proposed controller shows better performance than the conventional fuzzy controller through the hardware implementation.