A bio-knowledge based method to prevent control system instability

Author

Calvo-Rolle, Jose Luis ; Couce, Antonio ; Corchado, Emilio ; Sanchez, Ma Araceli ; Gil, Ana

Author_Institution

Dept. de Ing. Ind., Univ. of A Coruna, A Coruña, Spain

fYear

2010

fDate

15-17 Dec. 2010

Firstpage

430

Lastpage

436

Abstract

This study presents a novel bio-inspired method, based on gain scheduling, for the calculation of Proportional-Integral-Derivative (PID) 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 firstly identified. 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 liquid-level laboratory plant.

Keywords

neurocontrollers; scheduling; stability; three-term control; transfer functions; artificial neural network; bioinspired method; bioinspired model; bioknowledge; control system instability; controller parameters; gain scheduling; liquid level laboratory plant; proportional-integral-derivative controller; solid stability structure; transfer functions; Robustness; Valves; artificial neural networks; bio-inspired models; industrial applications; knowledge-based system; robust stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on

Conference_Location

Fukuoka

Print_ISBN

978-1-4244-7377-9

Type

conf

DOI

10.1109/NABIC.2010.5716342

Filename

5716342