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Temperature control of a pilot plant reactor system using a genetic algorithm model‐based control approach
Author(s) -
Khairi Abdul Wahab Ahmad,
Azlan Hussain Mohamed,
Omar Rosli
Publication year - 2007
Publication title -
asia‐pacific journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.348
H-Index - 35
eISSN - 1932-2143
pISSN - 1932-2135
DOI - 10.1002/apj.97
Subject(s) - exothermic reaction , pid controller , control theory (sociology) , controller (irrigation) , heat exchanger , set point , control system , temperature control , process (computing) , pilot plant , genetic algorithm , control engineering , process control , continuous stirred tank reactor , engineering , chemical reactor , computer science , control (management) , mechanical engineering , chemistry , chemical engineering , agronomy , electrical engineering , organic chemistry , artificial intelligence , machine learning , biology , operating system
The work described in this paper aims at exploring the use of an artificial intelligence technique, i.e. genetic algorithm (GA), for designing an optimal model‐based controller to regulate the temperature of a reactor. GA is utilized to identify the best control action for the system by creating possible solutions and thereby to propose the correct control action to the reactor system. This value is then used as the set point for the closed loop control system of the heat exchanger. A continuous stirred tank reactor is chosen as a case study, where the controller is then tested with multiple set‐point tracking and changes in its parameters. The GA model‐based control (GAMBC) is then implemented experimentally to control the reactor temperature of a pilot plant, where an irreversible exothermic chemical reaction is simulated by using the calculated steam flow rate. The dynamic behavior of the pilot plant reactor during the online control studies is highlighted, and comparison with the conventional tuned proportional integral derivative (PID) is presented. It is found that both controllers are able to control the process with comparable performance. Copyright © 2007 Curtin University of Technology and John Wiley & Sons, Ltd.