Abstract
This study proposes a novel discrete-time integral sliding mode control (ISMC) framework for managing pressure in multi-phase flow systems (MPFS), a critical component of hydrocarbon production and transportation. The primary goal is to achieve precise pressure regulation and minimize fluctuations under diverse operational conditions. Unlike traditional approaches, this work employs a Hammerstein nonlinear modeling technique to accurately represent the system dynamics and design the control strategy. The contributions of this research include the development of a data-driven system identification methodology using a single-input, single-output (SISO) Hammerstein model, enabling precise pressure prediction based on experimental data collected from the lab. A robust ISMC algorithm is introduced to address the inherent nonlinearities, disturbances, and uncertainties in multi-phase flow dynamics. The proposed controller is comprehensively validated through numerical simulations and experimental data, demonstrating its capability to reduce pressure fluctuations, enhance stability, and maintain operational efficiency. This novel integration of Hammerstein modeling with discrete-time ISMC offers a scalable and reliable solution to the challenges of pressure control in MPFS. The results demonstrate significant advantages over conventional controllers, such as traditional sliding mode, in terms of robustness and precision, contributing to the safety, efficiency, and sustainability of oil and gas operations.
Original language | English |
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Article number | 104024 |
Journal | Results in Engineering |
Volume | 25 |
DOIs | |
State | Published - Mar 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Author(s)
Keywords
- Data-driven modeling
- Discrete-time control
- Hammerstein model
- Integral sliding mode control (ISMC)
- Multi-phase flow systems (MPFS)
- Nonlinear dynamics
- Pressure regulation
- Robust control
- SISO systems
- System identification
ASJC Scopus subject areas
- General Engineering