Adaptive fuzzy sliding mode control for velocity regulation of subsea pipeline pigs with supervisory fuzzy tuning

Abstract

Stable velocity regulation of subsea pipeline pigs is critical for safe and efficient oil and gas operations, yet remains challenging due to strong nonlinearities and severe external disturbances such as slug flows and friction fluctuations. Therefore, this study proposes an adaptive fuzzy sliding mode control strategy, featuring a supervisory fuzzy mechanism that adaptively tunes the gains of the sliding mode reaching control law. This novel approach integrates a PID-based sliding surface and adaptive fuzzy inference, enhancing the controller’s robustness against system uncertainties and environmental disturbances. Simulations conducted on steeply inclined and curved pipeline scenarios—subjected to abrupt and severe disturbances—demonstrate that the proposed AFSMC exhibits faster regulation, less overshoot, and smoother valve transition compared to conventional controllers. The adaptive structure ensures stable pig velocity even under harsh and unpredictable subsea conditions. These results show that the AFSMC method improves control accuracy and system reliability, providing a practical solution for robust and stable pigging operations in complex offshore pipelines.