A bio-inspired robust controller for a refinery plant process

作者：Luis Calvo Rolle Jose; Corchado Emilio

来源：Logic Journal of the IGPL, 2012, 20(3): 598-616.

DOI：10.1093/jigpal/jzr010

• Bio-inspired models
• artificial neural networks
• knowledge-based system
• industrial applications
• robust stability

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.

• 出版日期2012-6