Abstract
AbstractDead time processes exist widely in many types of systems such as chemical processes, and the main steam temperature control system of the thermal power plant. A PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience since the gain of the PID controller has to be manually tuned by trial and error. This paper suggests a tuning method of the PID Controller for a process with long dead time using an immune algorithm typed neural network, through computer simulation. Tuning results of immune algorithms based neural network are compared with the results of genetic algorithm.KeywordsGenetic AlgorithmDead TimeThermal Power PlantImmune AlgorithmTuning MethodThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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