Buffer System Control for Hybrid Plants

The use of multimodal control techniques for batch dynamic systems offers a promising alternative to successfully perform tasks of supervision and control in industrial processes. These techniques seek to integrate different control strategies with partial objectives or "behaviors" using Lebesgue automatons overlooking achieve certain operational objectives. These automatons can identify optimal sequences of modes, also called control programs, using system simulations. Multimodal control programs consist of a sequence of modes, each of which comprises a feedback control law (x) and relevant termination conditions (x,T). In this paper the use of a reinforcement learning algorithm is described via to find, by simulations, optimal control program aligned to maximize productivity in a buffer system composed of two tanks.