Data-Driven Time-Delay Optimal Control Method for Roller Kiln Temperature Field

Abstract

In the industrial roller kiln, the time-delay characteristic in heat transfer causes the temperature field to be affected by both the current and historical temperature states. It presents a poor control performance and brings a significant challenge to the process precise control. Considering high complexity of precise modeling, a data-driven time-delay optimal control method for temperature field of roller kiln is proposed based on a large amount of process data. First, the control challenges and problem description brought by time-delay are demonstrated, where the cost function for the time-delay partial differential equation system is constructed. To obtain the optimal control law, the policy iteration in adaptive dynamic programming is adopted to design the time-delay temperature field controller, and neural network is used for the critic network in policy iteration to approximate the optimal time-delay cost function. The closed-loop system stability is proved by designing the Lyapunov function which contains the time-delay information. Finally, through establishing the time-delay temperature field model for roller kiln, the effectiveness and convergence of the proposed method is verified and proved.