Neural-network-based multiple feedback long-range predictive control

Abstract

After introducing neural-network-based nonlinear long-range predictive control for processes with time-delay, the paper presents several on-line corrections of long-range predictive outputs and proposes neural-network-based multiple feedback predictive control for nonlinear cascade industrial processes. A variable correction coefficient and its design approaches are presented. The simulation experiments have shown that the algorithm is able to effectively overcome disturbances and improves both the static and dynamic performances of the controlled system.