This chapter develops a supervisory control approach for burning zone temperature based on Q-learning, in which the signals of human intervention are viewed as the reinforcement learning signals. Section 2 makes brief descriptions of process and supervisory control system architecture. Section 3 discusses the detailed methodology of Q-learning-based supervisory control approach. The implementation and industrial applications are shown in Section 4. Finally, Section 5 draws the conclusion.