06072929

j

06072929 Calvo-Rolle, Jose Luis Corchado, Emilio A bio-inspired robust controller for a refinery plant process. Log. J. IGPL 20, No. 3, 598-616 (2012). 2012 Oxford University Press, Oxford EN bio-inspired models artificial neural networks knowledge-based system industrial applications robust stability

doi:10.1093/jigpal/jzr010

Summary: This research presents a novel bio-inspired knowledge method, based on gain scheduling, for the calculation of Proportional-Integral-Derivative controller parameters that will prevent system instability. The aim is to prevent a transition to control system instability due to undesirable controller parameters that may be introduced manually by an operator. Each significant operation point in the system is identified first. Then, a solid stability structure is calculated, using transfer functions, in order to program a bio-inspired model by using an artificial neural network. The novel method is empirically verified under working conditions in a real refinery plant process.