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

摘要

This paper describes the self-adjustment of some tuning knobs of the generalized predictive controller (GPC). A three feed forward neural network was utilized to on Line learn two key tuning - knobs of GPC, and BP algo- Rithm 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 eas- Ier condition for the wide applications of GPC on Indus- Trial plants. Simulation results illustrated the effective- Ness of the method.