Fuzzy advanced control: Boosting efficiency and economic benefits in offshore gas compression systems

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Authors: Thamires A.L. Guedes, Sergio Andres Castano Giraldo, Marcelo L. de Lima, Mario Cesar Mello Massa de Campos, Daniel Martins Lima, Leonardo D. Ribeiro, Argimiro Resende Secchi
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References: 14

Abstract

In this work, an advanced control system based on fuzzy logic is analyzed and implemented for a gas compression system on an offshore platform. This solution was applied after identifying an operational problem causing substantial economic losses due to unscheduled stops from high-temperature events at the compressor discharge. A detailed analysis of process variables that could be employed within the controller to mitigate this phenomenon was conducted, identifying compressor discharge temperatures as controlled variables and the machine’s discharge pressure setpoint as the primary manipulated variable. Through dynamic simulations and using a digital twin, it was possible to validate the behavior and effect of the variables, along with implementing the control system. Operational tests on the platform were conducted to verify the proposal and confirm the simulation results. The open-loop implementation of the control algorithm, i.e. the computed control action was not sent to the process, allowed the tracking and observation of the control system’s reaction to critical incidents, which validated its expected behavior. The activation of the closed-loop control successfully prevented machine stops, avoiding economic losses in production. This preventive approach avoided operational stops and highlighted the potential of advanced control systems to significantly improve safety, efficiency, and reliability in complex industrial environments. • Fuzzy control provides economic benefits in an offshore gas compression system. • Advanced control system prevents unscheduled compressor shutdowns. • High-temperature events at the compressors discharge were eliminated. • Digital-twin simulation validates gas compression system control.

Fields of Study & Subjects

Fault Detection and Control Systems Advanced Control Systems Optimization Fuzzy Logic and Control Systems

Publication details

Journal / source
Journal of Process Control
Volume
158
Pages
103635–103635
Publication date
19 January 2026
Language
EN