Design and analysis of based on PNN and FNN controller

Fuzzy neural net(FNN) and predictive neural net(PNN) are new neural net controllers, two neural net controllers based on practical methods from actual control system and self-study. FNN and PNN controllers avoid many shortcomings of usual artificial neural net. Two neural nets for electronic-hydraulic simulating rotary-table′s middle gimbal were used to research their control characteristics and application ranges.FNN controller unites fuzzy control experiences and neural net self-study capability, but control precision only depends on summarize personal experiences; PNN controller uses nonlinear auto regressive moving average (NARMA) model for predictive model, makes real time study and control for all process,but control precisions is lower in start phase. Simulation results of FNN and PNN controllers show that differnet methods for different control objects or unit two methods for different control objects have achieved high precisions.