Residual Gray Predictive Adaptive Smith-PID Control and Its Application

The superheated steam temperature system has the characteristics of high inertia, large delay and time-varying parameters. In this paper, adaptive Smith-PID based on residual gray prediction is used to deal with these problems. Adaline neural network is used to identify the object´s gain and delay in order to overcome the defectiveness of time-varying parameters. Residual gray prediction module in the feedback loop, which can predict multiple steps of the feedback, can regulate the system previously. This adaptive residual gray predictive control can overcome the influences of model mismatch and enhance the robustness of the system. The simulation of superheated steam temperature system proved that the new method has effective control performance.