Performance Analysis of Economic Model Predictive Control on a Solar-Powered Direct Contact Membrane Distillation System

Hichem Bessafa; Ghania Khodja; Chakir Messaoud; Taous Meriem Laleg-Kirati

doi:10.1016/j.ifacol.2022.11.003

Performance Analysis of Economic Model Predictive Control on a Solar-Powered Direct Contact Membrane Distillation System

Hichem Bessafa, Ghania Khodja, Chakir Messaoud, Taous Meriem Laleg-Kirati

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential algebraic equations-based model is used for the design of the EMPC control. Moreover, a nonlinear observer is developed for the estimation of the unmeasured state. A neural network is proposed to predict the unknown solar irradiance for future horizon where a solar model provides temperature predictions. The proposed control design has been validated in simulation using data provided by a partial differential equation-based model mimicking the real plant.

Original language	English (US)
Pages	13-19
Number of pages	7
DOIs	https://doi.org/10.1016/j.ifacol.2022.11.003
State	Published - 2022
Event	2nd IFAC Workshop on Control Methods for Water Resource Systems, CMWRS 2022 - Milan, Italy Duration: Sep 22 2022 → Sep 23 2022

Conference

Conference	2nd IFAC Workshop on Control Methods for Water Resource Systems, CMWRS 2022
Country/Territory	Italy
City	Milan
Period	09/22/22 → 09/23/22

Bibliographical note

Publisher Copyright:
© 2022 Elsevier B.V.. All rights reserved.

Keywords

differential algebraic equations
Direct contact membrane distillation
Economic model predictive control
Long-short term memory neural network
nonlinear observer

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.1016/j.ifacol.2022.11.003

Cite this

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title = "Performance Analysis of Economic Model Predictive Control on a Solar-Powered Direct Contact Membrane Distillation System",

abstract = "This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential algebraic equations-based model is used for the design of the EMPC control. Moreover, a nonlinear observer is developed for the estimation of the unmeasured state. A neural network is proposed to predict the unknown solar irradiance for future horizon where a solar model provides temperature predictions. The proposed control design has been validated in simulation using data provided by a partial differential equation-based model mimicking the real plant.",

keywords = "differential algebraic equations, Direct contact membrane distillation, Economic model predictive control, Long-short term memory neural network, nonlinear observer",

author = "Hichem Bessafa and Ghania Khodja and Chakir Messaoud and Laleg-Kirati, {Taous Meriem}",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.. All rights reserved.; 2nd IFAC Workshop on Control Methods for Water Resource Systems, CMWRS 2022 ; Conference date: 22-09-2022 Through 23-09-2022",

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doi = "10.1016/j.ifacol.2022.11.003",

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Performance Analysis of Economic Model Predictive Control on a Solar-Powered Direct Contact Membrane Distillation System. / Bessafa, Hichem; Khodja, Ghania; Messaoud, Chakir et al.
2022. 13-19 Paper presented at 2nd IFAC Workshop on Control Methods for Water Resource Systems, CMWRS 2022, Milan, Italy.

Research output: Contribution to conference › Paper › peer-review

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PY - 2022

Y1 - 2022

N2 - This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential algebraic equations-based model is used for the design of the EMPC control. Moreover, a nonlinear observer is developed for the estimation of the unmeasured state. A neural network is proposed to predict the unknown solar irradiance for future horizon where a solar model provides temperature predictions. The proposed control design has been validated in simulation using data provided by a partial differential equation-based model mimicking the real plant.

AB - This paper proposes an economic model predictive control (EMPC) design for a Direct Contact Membrane Distillation powered by a solar collector system which aims at enhancing its economical performances. A differential algebraic equations-based model is used for the design of the EMPC control. Moreover, a nonlinear observer is developed for the estimation of the unmeasured state. A neural network is proposed to predict the unknown solar irradiance for future horizon where a solar model provides temperature predictions. The proposed control design has been validated in simulation using data provided by a partial differential equation-based model mimicking the real plant.

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KW - Direct contact membrane distillation

KW - Economic model predictive control

KW - Long-short term memory neural network

KW - nonlinear observer

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T2 - 2nd IFAC Workshop on Control Methods for Water Resource Systems, CMWRS 2022

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Performance Analysis of Economic Model Predictive Control on a Solar-Powered Direct Contact Membrane Distillation System

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Keywords

ASJC Scopus subject areas

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