Modeling and control for plant dynamics based on reinforcement learning

The dynamics modeling of a plant was developed by using Q-learning, which is one method of reinforcement learning. We thought the modeling of the dynamical system to be the function approximation problem for the system output response signal, and enhanced reinforcement learning to the modeling method of the dynamical system. We describe that this modeling method guarantee to offer highly accurate dynamics models by numerical samples, which deals with incinerator's combustion. Results of numerical simulation show that the predictive control method using these models has robust tracking property. © 2009 The Institute of Electrical Engineers of Japan.