Direct Adaptive Dynamic Recurrent Fuzzy Neural Network Control and Its Application

For the characteristics that derivative relations exist between states of some affine nonlinear systems,a direct adaptive dynamic recurrent fuzzy neural network(DRFNN)control algorithm is proposed,which takes some measurable state variables as the DRFNN inputs and describes the system inner dynamic relation by the DRFNN feedback matrix. The unrealizable problem caused by some system unmeasurable state variables in traditional fuzzy neural network(TFNN) which takes all the state variables as its inputs is overcome.The results of its application to electro-hydraulic servo system show that direct adaptive DRFNN control algorithm has an advantage over the TFNN control method in improving the steady state characteristics of the system.