Model predictive control for nonlinear systems modelled with neutral networks - Hoong, Seng Keng (2017)
Model predictive control (MPC) is a popular and an advance control technique for linear system with hard constraints. However, in the case of non-linear system, using MPC to control may pose difficulties. This is because MPC may not be able to handle the non-linear system’s complexity. With new technologies and ideas emerging, the interest in MPC arises as it has potential to conquer this weakness and exhibits its unique strength. Neural Network (NN) is a type of classifier to predict its output and can be used as process model for many control problems. In addition, the efficient of a non-linear MPC is highly related to the properties of NN.