Intelligent Temperature Control of Ceramic Shuttle Kiln Based on Improved DQN Algorithm
Aiming at the characteristics of large delay,nonlinear,slow time varying and strong coupling,an intelligent temperature control method based on improved DQN algorithm was proposed.Firstly,the model of ceramic shuttle kiln based on BP neural network was established.Then an intelligent control method based on improved DQN algorithm is proposed.Finally,the pro-posed method is simulated.The simulation results show that the relative error of the improved PRDQN algorithm is between 0 ℃ and 5 ℃,and the temperature control effect is relatively good.Therefore,the proposed method is effective and feasible.
ceramic shuttle kilnmulti-agent deep reinforcement learningBP neural networkimproved DQN algorithm
万方数据
维普
