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Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)

International Association of Computer Science and Information Technology (IACSIT)
International Association of Computer Science and Information Technology (IACSIT)
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This paper will first describe the Linear Quadratic Regulator (LQR) and Fuzzy logic controller when the Proportional-Integral-Derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, LQR and Fuzzy controllers perform better than the PID controllers. The constrained LQR is optimal and stabilizing. The solution algorithm is guaranteed to terminate in finite time with a computational cost that has a reasonable upper bound compared to the minimal cost for computing the optimal solution. The system determines the amount of fuel required from a fuzzy algorithm to arrive at the desired temperature. The parameters of the fuzzy control paradigm were a collection of rules and fuzzy-set membership functions. The output of the Fuzzy controller is defuzzified by two different methods; Middle of Maximum (MOM) and Supremum of Maximum (SOM). Eventually, LQR and Fuzzy logic controllers have been designed for a thermal system, which circulates hot air to keep the temperature of a chamber constant and finally the results are analyzed and compared.

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