Parameter Self - Learning of Generalized Predictive Control Using BP Neural Network

This paper describes the self - adjustment of some tuning - knobs of the generalized predictive controller (GPC). A three feedforward neural network was utilized to on line learn two key tuning - knobs of GPC, and BP algorithm was used for the training of the linking - weights of the neural network. Hence it gets rid of the difficulty of choosing these tuning - knobs manually and provides easier condition for the wide applications of GPC on industrial plants. Simulation results illustrated the effectiveness of the method.