Integrating dynamic neural network models with principal component analysis for adaptive model predictive control

This work addresses one aspect of the overparameterization problem in using artificial/recurrent neural networks (ANN/RNN) based dynamic models for model predictive control (MPC) implementations. The manuscript presents an approach to handle situations where the training data may not be sufficiently rich, and in particular, for handling historical data with correlated inputs. Two approaches are proposed. The key idea in the first method is to …