Non-linear control algorithms for de-oiling hydrocyclones

Vallabhan, Mishiga; Holden, Christian

doi:10.1109/med48518.2020.9183115

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…Discharge concentration: the discharge concentration denoted as C u is a natural choice of CV to comply with the discharge concentration limits, as studied in [6,8,18,19].…”

Section: Oil-in-water Based Controlled Variablesmentioning

confidence: 99%

“…The authors approximated the separation efficiency for a fixed underflow valve opening degree as a second-order polynomial function of the overflow flow rate and derived mass balances to describe the separation dynamics. A PI controller was developed using the Skogestad internal model control (SIMC) tuning rules, and later, a sliding mode, feedback linearization, feedforward, cascade, and model predictive controller (MPC) were designed to track a constant discharge concentration reference in simulation [6,18,19]. These models have proven to be capable of representing the steady-state efficiency behavior of hydrocyclones, but the dynamic features have not been validated or have been insufficient to describe the data [4,6].…”

Section: Introductionmentioning

confidence: 99%

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Hammerstein–Wiener Model Identification for Oil-in-Water Separation Dynamics in a De-Oiling Hydrocyclone System

Jespersen,

Yang,

Hansen

et al. 2023

Energies

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To reduce the environmental impact of offshore oil and gas, the hydrocarbon discharge regulations tend to become more stringent. One way to reduce the oil discharge is to improve the control systems by introducing new oil-in-water (OiW) sensing technologies and advanced control. De-oiling hydrocyclones are commonly used in offshore facilities for produced water treatment (PWT), but obtaining valid control-oriented models of hydrocyclones has proven challenging. Existing control-oriented models are often based on droplet trajectory analysis. While it has been demonstrated that these models can fit steady-state separation efficiency data, the dynamics of these models have either not been validated experimentally or only describe part of the dynamics. In addition to the inlet OiW concentration, they require the droplet size distribution to be measured, which complicates model validation as well as implementation. This work presents an approach to obtain validated nonlinear models of the discharge concentration, separation efficiency, and discharge rate, which do not require the droplet size distribution to be measured. An exhaustive search approach is used to identify control-oriented polynomial-type Hammerstein–Wiener (HW) models of de-oiling hydrocyclones based on concentration measurements from online OiW monitors. To demonstrate the effectiveness of this modeling approach, a PI controller is designed using the Skogestad internal model control (SIMC) tuning rules to control the discharge OiW concentration directly. The identification experiment emulates an offshore PWT system with installed OiW monitors, which is realistic with the legislative incentive to include online OiW discharge measurements. The proposed approach could enable the application of OiW-based control on existing offshore PWT facilities, resulting in improved de-oiling performance and reduced oil discharge.

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“…Discharge concentration: the discharge concentration denoted as C u is a natural choice of CV to comply with the discharge concentration limits, as studied in [6,8,18,19].…”

Section: Oil-in-water Based Controlled Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hammerstein–Wiener Model Identification for Oil-in-Water Separation Dynamics in a De-Oiling Hydrocyclone System

Jespersen,

Yang,

Hansen

et al. 2023

Energies

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“…If the droplet size distribution and inlet concentration are known, the separation efficiency can be calculated. Such approaches have been extended with models describing the pressure-flow relationship in the hydrocyclone to calculate the fluid velocity fields needed for the droplet trajectory models [58,59]. As the pressure-flow relationship and the droplet trajectory analysis methods are generally static considerations, the separation dynamics are either based on the valve dynamics [59] or mass balances [58].…”

Section: Motivation For Hydrocyclone Modelingmentioning

confidence: 99%

“…Such approaches have been extended with models describing the pressure-flow relationship in the hydrocyclone to calculate the fluid velocity fields needed for the droplet trajectory models [58,59]. As the pressure-flow relationship and the droplet trajectory analysis methods are generally static considerations, the separation dynamics are either based on the valve dynamics [59] or mass balances [58]. While such approaches have been seen to reasonably describe the steady-state separation efficiency, the dynamics remain invalidated.…”

Section: Motivation For Hydrocyclone Modelingmentioning

confidence: 99%

“…In order to develop control solutions of the hydrocyclone's OiW dynamics, some reasonably precise and control-oriented models are needed. Although some grey-box approaches based on droplet-trajectory analysis have been seen to fit reasonably well to steady-state efficiency data, the dynamics have either not been validated or still need some improvement [15,58]. These models require measurements of the droplet size distribution, which complicates the model validation as well as the implementation.…”

Section: Motivation For Paper C and Dmentioning

confidence: 99%

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Modeling and Control of Offshore Produced Water Treatment Systems Using Online Oil-in-Water Monitors

Jespersen

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