Robust integral sliding mode control for pressure management in multi-phase flow systems
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 u...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025001124 |
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| Summary: | 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. |
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| ISSN: | 2590-1230 |