RNN Based Auto-tuning of PID Control Gains in Hot StripLooper Controller

In this study, auto tuning of PID control gains in hot strip looper controller is made based on RNN model. Neuro emulator is employed to model the characteristics of looper dynamics. Combining neuro emulator and RNN model, auto tuning system of PID control gains is constructed. As the inputs to RNN, plural evaluation functions which reflect individual preference of human experts. Further, Self learning mechamism is embeded to RNN model which enables adaptation to the change in rolling chracteristics. Through numerical experiments, the effect of the proposed method is ascertained.