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The processes that take place in industrial reactors are mainly highly nonlinear and, due to this, their controls have become a major factor in determining the aspect of process safety, quality, and productivity of these systems. For this reason, we have designed an inexpensive, practical reactor on a pilot plant scale to conduct such online control studies where the heat of reaction in the reactor is simulated by injecting steam into the reactor system. This paper highlights the development of the pilot plant with its software development to implement advanced control strategies using artificial intelligence approaches such as fuzzy logic and genetic algorithm. The online implementation results conclude that the Genetic Algorithm Model Based Controller (GAMBC) gave similar performance with the Fuzzy Logic Controller (FLC) for the set point tracking studies but in the load disturbance rejection studies, it was found that the FLC performed better. The results obtained show the usefulness and importance of these experimental studies to further understand advanced control applications for a typical industrial chemical process such as a reactor.

An Artificial Intelligence Software-Based Controller for Temperature Control of a Partially Simulated Chemical Reactor System