Application of hybrid modeling and control techniques to desalination plants

Gambier, Adrián; Badreddin, Essameddin

doi:10.1016/s0011-9164(02)01060-3

Cited by 27 publications

(14 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Comparison the performances of constrained model predictive control (CMPC) and PI controller was carried out by Assef et al (1997); Burden et al (2001) and Abbas (2006) who concluded that the former is better for maximizing throughput. A hybrid model was presented by Gambier and Badreddin (2002) by combining continuous and discrete dynamics of RO systems which was decoupled and used for control purpose. But these control techniques are quite complex as they involve complicated analysis and design tools.…”

Section: Identificationmentioning

confidence: 99%

Review on modelling and control of desalination system using reverse osmosis

Sobana¹,

Panda²

2011

Rev Environ Sci Biotechnol

View full text Add to dashboard Cite

Dissolved salts in seawater or brackish water are reduced to a potable level through separation techniques, like, distillation, multiple effect vapor compression, evaporation, or by membrane processes such as electro-dialysis reversal, nanofiltration, and reverse osmosis (RO). RO is the most widely used desalination process. Recent advances in RO technology has led to more efficient separation and now is the most cost effective process to operate. The performance of the reverse osmosis process is dependent on concentration of dissolved solids in the feed-water, feed-water pressure, and the membrane strength to withstand system pressure, membrane solute rejection, membrane fouling characteristics, and the required permeate solute concentration. RO is a promising tool that uses cellulose acetate (or) polyamide membrane and is widely chosen as the cost of production is reduced by the use of energy efficient and process control techniques. This paper presents a review on modelling, identification of parameters from single input-outputs and multi input/ output lumped systems, dynamic modelling and control of desalination systems in the past twenty years by collecting more than 60 literatures.

show abstract

Section: Identificationmentioning

confidence: 99%

Review on modelling and control of desalination system using reverse osmosis

Sobana¹,

Panda²

2011

Rev Environ Sci Biotechnol

View full text Add to dashboard Cite

show abstract

“…Furthermore, control methods using model-predictive control (MPC) and Lyapunov-based control have also been evaluated using computer simulations [5], [6], [7], [8]. Reverse osmosis system analysis using linear models and data-based models using step-tests to create approximate linear models have also been demonstrated [9].…”

Section: Introductionmentioning

confidence: 99%

Minimizing energy consumption in reverse osmosis membrane desalination using optimization-based control

Bartman

Zhu

Christofides

et al. 2010

Proceedings of the 2010 American Control Conference

View full text Add to dashboard Cite

This work focuses on the design and implementation of an optimization-based control system on an experimental reverse osmosis (RO) membrane water desalination process in order to facilitate system operation at an energy optimal condition. A dynamic nonlinear lumped-parameter model for the RO process is derived using first principles and the model parameters are computed from experimental data to minimize the error between model predictions and actual system response. This model, along with several equations for reverse osmosis system energy analysis, are combined to form the basis for the design of a nonlinear optimization-based control system. The proposed control system is implemented on UCLA's experimental RO system and its energy optimization capabilities are evaluated.

show abstract

“…Several model-based methods, such as model-predictive control (MPC) and Lyapunov-based control, have been evaluated via computer simulations for use in RO desalination. [5][6][7]13 Experimental system identification and MPC applications can also be found in the literature. 8,9 Model-based control methods have also been used in conjunction with fault detection and isolation schemes to improve robustness of control methods in the presence of sensor and actuator failures.…”

Section: Introductionmentioning

confidence: 99%

“…O p ) µ ln e vr +(11)O p ) -84.428 ln(e vr ) + 459.21(12) O p ) -2.0473 ln(e vr ) + 18.141(13) O p ) -0.0778 ln(e vr ) + 0.9476(14) …”

mentioning

confidence: 99%

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

Bartman

Christofides

Cohen

2009

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

This work focuses on the design and implementation of a nonlinear model-based control system on an experimental reverse-osmosis (RO) membrane water desalination system to address large set-point changes and variations in feedwater salinity. A dynamic nonlinear lumped-parameter model is derived using firstprinciples, and its parameters are computed from experimental data to minimize the error between model predictions and experimental RO system response. This model then is used as the basis for the design of a nonlinear control system, using geometric control techniques. The nonlinear control system is implemented on the experimental RO system, and its set-point tracking and disturbance rejection capabilities are successfully evaluated.

show abstract

Application of hybrid modeling and control techniques to desalination plants

Cited by 27 publications

References 15 publications

Review on modelling and control of desalination system using reverse osmosis

Review on modelling and control of desalination system using reverse osmosis

Minimizing energy consumption in reverse osmosis membrane desalination using optimization-based control

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

Contact Info

Product

Resources

About