Advanced control of a reverse osmosis desalination unit

Assef, J.Z.; Watters, James C.; Deshpande, Pradeep B.; Alatiqi, I.M.

doi:10.1016/s0959-1524(97)00004-8

Cited by 39 publications

(13 citation statements)

References 4 publications

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“…Another multivariable transfer function models using plant's input/output data was developed by Assef et al (1995), Riverol and Pilipovik (2005) and Robertson et al (1996). In the first case, model was obtained by fitting step response data into 2nd order transfer function with numerator zero structure as…”

Section: Identificationmentioning

confidence: 99%

“…A model by step response data and fitting where inputs/outputs were defined in a different way was presented by Assef et al (1995). Fully connected multilayer feed forward artificial neural network using the algorithm of back propagation to identify the nonlinear multivariable multistage flash desalination plant was constructed by Selvaraj et al (1995).…”

Section: Identificationmentioning

confidence: 99%

“…But realtime robust control of the RO plant is rare. 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.…”

Section: Identificationmentioning

confidence: 99%

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Review on modelling and control of desalination system using reverse osmosis

Sobana¹,

Panda²

2011

Rev Environ Sci Biotechnol

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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.

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Section: Identificationmentioning

confidence: 99%

Section: Identificationmentioning

confidence: 99%

Section: Identificationmentioning

confidence: 99%

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Review on modelling and control of desalination system using reverse osmosis

Sobana¹,

Panda²

2011

Rev Environ Sci Biotechnol

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“…Several papers were published, for example [1], [9] or [10], where RO system identification is considered. The system interaction can be rewritten for the discrete case with a sample time of T 0 = 0.2 as G 11 (z) = 0.002013z − 2.225 · 10 −5 z 2 − 0.005708z + 0.001273 G 21 (z) = −0.1574z + 0.08829 z 2 − 1.383z + 0.5183 and G 22 (z) = −6.084z + 3.242 z 2 − 1.499z + 0.5488 .…”

Section: E Examplementioning

confidence: 99%

Controller tuning of stochastic disturbed multi-loop control systems

Wellenreuther

Gambier

Badreddin

2008

2008 IEEE International Conference on Control Applications

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A controller tuning method in a game-theoretic framework is extended, to keep the requirements of optimal system performance due to stochastic disturbances. First, a minimum variance controller, known in the literature for use in systems with stochastic disturbances, is applied to a single-loop control system. The extended controller tuning method, derived from game theory, is presented and applied to the single-loop control system as well and finally compared with the simulation results obtained using the minimum variance controller. For multi-loop systems, the authors tried to extend both methods and apply them on an example to show their capabilities as well as their limits. The use of the minimum variance controller in multi-loop system fails, while the proposed extended controller tuning method is successful applicable to such kind of systems.

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“…One advanced control strategy that has gained acceptance in industry is model predictive control (MPC) [9]. It was used in an RO process by Burden et al [10], Assef et al [11] and Deshpande et al [12].…”

Section: Introductionmentioning

confidence: 99%

Techno-economic optimization of SWRO desalination using advanced control approaches

Hossam-Eldin

El-Nashar

Ismaiel

2009

Desalination and Water Treatment

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ab s t r ac tThis paper presents two advanced control techniques that can be used to optimize the operation of seawater reverse osmosis (SWRO) desalination plants to decrease the production cost. The first technique uses the model predictive control (MPC) controller to operate the plant at its optimum operating conditions, while the second technique is based on early detection of membrane fouling. The objective of this work is to compare the SWRO desalination plant optimized performance with the conventional operation and evaluate the optimization effect on the unit production cost as well as conduct adequate economical analysis. Three case studies including three existing SWRO plants were tried and compared using the above technique. The second technique proved to be effective and the results were compared with the existing data and proved to be satisfactory.

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Advanced control of a reverse osmosis desalination unit

Cited by 39 publications

References 4 publications

Review on modelling and control of desalination system using reverse osmosis

Review on modelling and control of desalination system using reverse osmosis

Controller tuning of stochastic disturbed multi-loop control systems

Techno-economic optimization of SWRO desalination using advanced control approaches

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