LAUSR

AbstractThis paper proposes a new adaptive proportional–integral–derivative (PID) control method using predictive control and output recurrent fuzzy wavelet neural network (ORFWNN) for a group of nonlinear digital time-delay dynamic systems. The presented controller, called ORFWNN-APPID controller, is rigorously derived and proved by including an ORFWNN identifier with online parameter learning and identification, and an adaptive ORFWNN-based predictive PID controller to achieve precise setpoints tracking and disturbance rejection. The effectiveness and superiority of the constructed ORFWNN-APPID control approach are well demonstrated by performing numerical simulations on step-like disturbance rejection and precise setpoint tracking of two well-known digital nonlinear processes. The practicability of the presented method is illustrated by carrying out two experimental results on a real PET temperature control process.