A bio-inspired robust controller for a refinery plant process
Fecha de publicación
Oxford University Press (OUP)
Logic Journal of IGPL. Volumen 20 (3), pp. 598-616. Oxford University Press (OUP).
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.
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