Dynamic modelling of MSF plants for automatic control and simulation purposes: a survey
The successful development of a control system requires an appropriate definition of the control structure (i.e., selection of output, input and disturbance variables) and an efficient dynamical model on which the design, analysis and evaluation can be carried out. Thus, the confidence in the obtain...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
3 November 2004
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| In: |
Desalination
Year: 2004, Jahrgang: 166, Pages: 191-204 |
| ISSN: | 1873-4464 |
| DOI: | 10.1016/j.desal.2004.06.073 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1016/j.desal.2004.06.073 Verlag: http://www.sciencedirect.com/science/article/pii/S0011916404003005 
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| Verfasserangaben: | Adrian Gambier, Essameddin Badreddin |
MARC
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| 520 | |a The successful development of a control system requires an appropriate definition of the control structure (i.e., selection of output, input and disturbance variables) and an efficient dynamical model on which the design, analysis and evaluation can be carried out. Thus, the confidence in the obtained results depends on the validity of the control structure and of the model used. For multistage flash (MSF) desalination processes, several dynamical models can be found in the literature. However, most of them are not suitable for analysis and control design purposes because they bring too many variables into play. The variables, which are sharing in the control system, normally constitute a reduced subset of the total variables that can be defined in the process. Moreover, a dynamical model suitable for control is simpler than the model derived from the physics of the underlying process. Hence, the selection of variables and the model building from the point of view of control design presents a compromise between the indispensable information contained in the model and the mathematical complexity proper of the design. In this paper, different models from the literature are analysed. Their advantages and drawbacks are described taking into account simulation and automatic control purposes. Moreover, a set of wished modelling facilities from the control engineer point of view is highlighted. Finally, a block-oriented library for Matlab/Simulink is presented, so that different plant configurations can be implemented as block diagram to simulate the system and to test control algorithms. | ||
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