Adaptive Predictive PID Control Using Fuzzy Wavelet Neural Networks for Nonlinear Discrete-Time Time-Delay Systems

This paper presents a novel adaptive predictive proportional–integral–derivative (PID) control using fuzzy wavelet neural networks (FWNN) for a kind of highly nonlinear discrete-time system with time delay. The proposed controller, abbreviated as FWNN-APPID, is composed of an adaptive predictive PID controller with abilities of accurate tracking and disturbance rejection and an FWNN identifier with online parameter tuning and estimation. Several simulations for controlling a highly nonlinear time-delay process show constant disturbances rejection and its performance of setpoint tracking for the proposed FWNN-APPID control method, thus clearly showing its effectiveness and merit. Experimental results on a real PET stretch blow molding machine show the applicability of the proposed method.