A Deep Learning Architecture for Predictive Control
A Deep Learning Architecture for Predictive Control is a scholarly work, published in 2018 in ''IFAC Proceedings Volumes''. The main subjects of the publication include optimization problem, deep learning, artificial intelligence, computer science, control engineering, system identification, artificial neural network, irrigation controller, process, control in organization management, fault detection and isolation, model predictive control, machine learning, and control theory. The authors propose a deep neural network (DNN) controller architecture to reduce the computational cost of implementing an MPC.