Mohamed Ibrahim, Saifudin Bin (2005) The PID controller design using genetic algorithm. [USQ Project]
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Abstract
It is known that PID controller is employed in every facet of industrial automation. The
application of PID controller spans from small industry to high technology industry. For
those who are in heavy industries such as refineries and ship-building, working with the PID
controller is like routine work. Hence how do we optimize the PID controller? Do we
still tune the PID as what we use to for example using the classical technique that has
been taught to us like Ziegler-Nichols method? Or do we make use of the power of the computing world by tuning the PID in a stochastic manner?
In this dissertation, it is proposed that the controller be tuned using the Genetic Algorithm
technique. Genetic Algorithms (GAs) are a stochastic global search method that emulates
the process of natural evolution. Genetic Algorithms have been shown to be capable
of locating high performance areas in complex domains without experiencing the
difficulties associated with high dimensionality or false optima as may occur with
gradient decent techniques. Using genetic algorithms to perform the tuning
of the controller will result in the optimum controller being evaluated for the system
every time.
For this study, the model selected is of a turbine speed control system. The reason for this
is that this model is often encountered in refineries in a form of steam turbine that uses a
hydraulic governor to control the speed of the turbine.
The PID controller of the model will be designed using the classical method and the
results analyzed. The same model will be redesigned using the GA method. The results of
both designs will be compared, analyzed and a conclusion will be drawn out of the
simulation made.
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| Item Type: | USQ Project |
|---|---|
| Refereed: | No |
| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013) |
| Date Deposited: | 11 Oct 2007 00:26 |
| Last Modified: | 02 Jul 2013 22:33 |
| Uncontrolled Keywords: | PID controller, Ziegler-Nichols method, genetic algorithm technique, genetic algorithms, turbine speed control systems |
| Fields of Research (2008): | 09 Engineering > 0906 Electrical and Electronic Engineering > 090601 Circuits and Systems 09 Engineering > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified |
| Fields of Research (2020): | 40 ENGINEERING > 4008 Electrical engineering > 400801 Circuits and systems 40 ENGINEERING > 4008 Electrical engineering > 400899 Electrical engineering not elsewhere classified |
| URI: | https://sear.unisq.edu.au/id/eprint/632 |
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