Jan 22, 2020   12:23 p.m. Zora
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prof. Ing. Miroslav Fikar, DrSc.
Identification number: 3374
University e-mail: miroslav.fikar [at] stuba.sk
 
Rektor - Vedenie STU (REKP REK)
Profesor DrSc. - Department of Information Engineering and Process Control (IIEAM FCFT)
Director - Department of Information Engineering and Process Control (IIEAM FCFT)
Chancellor - Slovak university of technology in Bratislava
 
External colleague - Institute of Applied Informatics, Automation and Mechatronics (MTF)

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Basic information

Basic information about a final thesis

Type of thesis: Diploma thesis
Thesis title:Advanced Process Control of a Depropanizer Column
Written by (author): Ing. Martin Mojto
Department: Institute of Information Engineering, Automation and Mathematics (FCFT)
Thesis supervisor: prof. Ing. Miroslav Fikar, DrSc.
Opponent:Ing. Martin Klaučo, PhD.
Final thesis progress:Final thesis was successfully defended.


Additional information

Additional information about the final thesis follows. Click on the language link to display the information in the desired language.

Language of final thesis:English

Slovak        English

Title of the thesis:Advanced Process Control of a Depropanizer Column
Summary:This work deals with the APC control of depropanizer column in the Slovnaft refinery. Depropanizer column represents a nonlinear MIMO process with strong interactions between the variables. The control performance of various control configurations (LV, LB, DV, LD and Ryskamp) is investigated in order to minimize interactions and determine the most efficient pairings of variables (MVs and CVs) in the structure of controlled process. The effective method for analysis of steady state properties of controlled process is RGA analysis. The dynamic behaviour is possible to observe in the disturbance rejection control and setpoint tracking analysis. The next part researches the dynamic optimisation of temperature in the distillate and bottom products. Minimized objective function involves control error and increments of control. Control trajectories from the dynamic optimisation predict changes in the process and provide more effective control than the standard PI controller. Inferential sensors are designed to provide continuous measurement of the composition (main impurity) in the distillate and bottom products. The computation of composition within the inferential sensors requires the data from other indicators in the depropanizer column. Designed inferential sensors are based on the historical plant data from the industrial database and the simulated data. The last part describes implementation of APC control in the industrial software. The required inputs are the matrix of identified transfer functions and constraints. The control performance of implemented APC controller is tested in simulation within the same software.
Key words:depropanizer column, configuration, dynamic optimisation, inferential sensors, APC

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Parts of thesis with postponed release:

Final thesis (final thesis appendices) unlimited
Reviews for final thesis unlimited