Neural network model-based multivariable predictive control algorithms with application in thermal power plant control

摘要

Two neural network (NN) model-based multivariable nonlinear model predictive control (NMPC) algorithms along with appli- cation to more efficient thermal power plant control are presented in this paper. The first algorithm uses a global nonlinear NN model and a nonlinear programming (NLP) routine for optimization to compute optimal control moves. With the help of suitable observer polynomials, modelling errors and other disturbances are given a proper and consistent treatment to achieve offset-free closed-loop behaviour.