Invertible singleton fuzzy models: application to petroleum production control systems

Abstract

This paper presents an identification approach based on invertible singleton fuzzy models in order to implement a control system for a progressive cavity pump-based petroleum production system, by using the inverse model control scheme. The identification proposal uses input-output process variables measurements and an off-line genetic algorithm, which is designed for guarantying the analytical calculation of the inverse model. Regarding the application of the genetic algorithm, three selection methods are evaluated: tournament selection, roulette wheel selection and linear rank selection. Once the fuzzy singleton model is identified, the controller design is a straightforward procedure. Computer simulations show the potential application of this kind of model in real industrial control processes.