Nonlinear Model-Based Control of an Experimental Reverse-Osmosis Water Desalination System

Bartman, Alex R.; Christofides, Panagiotis D.; Cohen, Yoram

doi:10.1021/ie900322x

Cited by 66 publications

(38 citation statements)

References 21 publications

(42 reference statements)

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“…Data for model development were generated using the UCLA spiral-wound Mini-Mobile-Modular (M3) pilot RO desalination system shown schematically in Figure 1. 3,35,36 The M3 system was designed for permeate water production capacity up to 1.2 m 3 /h (7560 gallons/day) for brackish water (5000 mg/L TDS) operating at 75% recovery and up to 0.64 m 3 /h (4058 gallons/day) for seawater desalination (at recovery of 40%), using up to 18 spiralwound elements in various configurations. In the present study, a configuration of 6 elements (one per pressure vessel) in series was utilized with the system operating in a total recycle mode 35 that adjusted both an electrically actuated needle valve (valve V-1) (model VA8 V-7-0-10, ETI Systems, Carlsbad, CA) on the retentate stream of the M3 RO system and the pump VFD.…”

Section: Methodsmentioning

confidence: 99%

Fault Detection and Isolation in a Spiral-Wound Reverse Osmosis (RO) Desalination Plant

Pascual

Gu²,

Bartman³

et al. 2014

Ind. Eng. Chem. Res.

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Sensor fault detection and isolation (SFDI) approaches, based on support vector regression (SVR) plant sensor models and self-organizing-map (SOM) analysis, were investigated for application to reverse osmosis (RO) desalination plant operation. SFDI-SVR and SFDI-SOM were assessed using operational data from a small spiral-wound RO pilot plant and synthetic faulty data generated as perturbations relative to normal plant operational data. SFDI-SVR was achieved without false negative (FN) detections for sensor deviations of ≳|10%| and FN detections of, at the most, ≲|5%|, and for sensor deviations of ≳|4%| at sensor fault detection (FD) thresholds of up to ∼|4%|. False positive (FP) detections were almost invariant, with respect to sensor FD, being ≲|5%| for sensor deviations of ≳|5%|. Corrections of faulty sensor readings were within SVR model accuracy (AARE < 1%) for SFDI-SVR and ≲|5%| for SFDI-SOM. Although SFDI-SOM has lower detection accuracy, it requires a single overall plant model (or SOM), while providing pictorial representation of plant operation and depiction of faulty operational trajectories.

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Section: Methodsmentioning

confidence: 99%

Fault Detection and Isolation in a Spiral-Wound Reverse Osmosis (RO) Desalination Plant

Pascual

Gu²,

Bartman³

et al. 2014

Ind. Eng. Chem. Res.

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“…In the literature, there are several research works [29][30][31] interested in reverse osmosis. In this paper, our objective is determining the bond graph model of the reverse osmosis component by component in order to facilitate the detection and location of faults.…”

Section: General Description Of the Systemmentioning

confidence: 99%

Diagnosis of reverse osmosis desalination water system using bond graph approach

Sallami¹,

Mzoughi²,

Mami³

2018

Turk J Elec Eng & Comp Sci

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Industrial systems have become quite complicated. It is therefore necessary to look for a reliable supervision system to properly treat the information and make the appropriate decision to stop the system or leave it in operation.Supervision of automated systems goes to the heart of the matter. This paper concerns the design of a new methodology for diagnosis based on bond graph modeling. We apply a diagnostic method by Luenberger observer using the bond graph approach on a desalination unit. Tests are carried out on the water input pressure delivered by the pump and the output flow rates of the reverse osmosis. This method will allow us to test normal and failure operations of an industrial system. The roles of diagnostic systems for industrial processes consist of detecting and locating faults, also called residues, that will affect these processes. In order to be effective, the diagnostic system should be robust for residue analysis and insensitive to false alarms. In this context, the development of the proposed method is described from the step of modeling to the step of generation of certain residues.

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“…Current literatures suggested that the transition from one steady state to another steady state for RO process changes in different applications. Bartman et al altered the flow rate less than ~1 min within a wide range of operation in UCLA experimental RO membrane water desalination system [33]. Sassi et al reported that pseudo steady-state model of RO can be considered for time-step more than 0.25 h [34].…”

Section: Evaluation and Comparison Of Mppt Controllersmentioning

confidence: 99%

Maximum power point tracking (MPPT) control of pressure retarded osmosis (PRO) salinity power plant: Development and comparison of different techniques

Luo

Kiselychnyk

et al. 2016

Desalination

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. (2016) Maximum power point tracking (MPPT) control of pressure retarded osmosis (PRO) salinity power plant : development and comparison of different techniques. Desalination,. Permanent WRAP URL:http://wrap.warwick.ac.uk/78938 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP url' above for details on accessing the published version and note that access may require a subscription. Abstract:This paper presents two new methods for the maximum power point tracking (MPPT) control of a pressure retarded osmosis (PRO) salinity power plant, including mass feedback control (MFC) and fuzzy logic control (FLC). First, a brief overview of perturb & observe (P&O) and incremental mass resistance (IMR) control is given as those two methods have already demonstrated their merit in good control performance. Then, two new methods employing variable-step strategy, MFC and FLC, are proposed to address the trade-off relationship between rise-time and oscillation of P&O and IMR. Genetic Algorithm (GA) is used for finding the optimum parameters of membership functions of FLC. From the case-study of start-up of the PRO adopting MPPT control, MFC and FLC have shown faster convergence to the target performance without oscillation compared with P&O and IMR. These four MPPT techniques are further evaluated in case-studies of state transitions of the PRO due to operational fluctuations. It is proven that the MPPT using FLC and modified MFC has better performance than the other two methods. Finally, the paper reports a comparison of major characteristics of the four MPPT methods, which could be considered as guidance for selecting a MPPT technique for the PRO in practice. IntroductionPressure retarded osmosis (PRO) is a promising method which is potentially capable of producing power and processing water simultaneously because of its nature of combination of the water treatment and renewable energy generation. In other words, it can be used as not only a clean energy generator, but also a water treatment to recycle water. In a PRO plant, chemical potential between the two salinities is converted to hyd...

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Nonlinear Model-Based Control of an Experimental Reverse-Osmosis Water Desalination System

Cited by 66 publications

References 21 publications

Fault Detection and Isolation in a Spiral-Wound Reverse Osmosis (RO) Desalination Plant

Fault Detection and Isolation in a Spiral-Wound Reverse Osmosis (RO) Desalination Plant

Diagnosis of reverse osmosis desalination water system using bond graph approach

Maximum power point tracking (MPPT) control of pressure retarded osmosis (PRO) salinity power plant: Development and comparison of different techniques

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