Fuzzy Theory has shown good control performace for non-linear system that is difficult to be controlled by the conventional controller. Backpropagation neural network can interpolate output without the priori knowledge of its dynamics. In this paper, ...
Fuzzy Theory has shown good control performace for non-linear system that is difficult to be controlled by the conventional controller. Backpropagation neural network can interpolate output without the priori knowledge of its dynamics. In this paper, we proposes a Fuzzy-Neural Controller. The Fuzzy Control by deterministic Rule may not be sensitive for uncertain conditions and has a disadvantage of setting the rule by repeatedly experience. To solve such problems, we construct Self organizing Fuzzy-Neural Controller which can reorganize the fuzzy rule according to the state of System. Experimental results show that proposed Fuzzy-Neural Controller has better performance than conventional controller(PID) has especially rising time and overshoot characteristics.