Temperature control of a pilot plant reactor system using a genetic algorithm model‐based control approach
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 pos...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
Wiley
2007
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/7047/ https://doi.org/10.1002/apj.97 |
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| Summary: | 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. |
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