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) |
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Pages | 13-19 |
Number of pages | 7 |
DOIs | |
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 |
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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