A case study in intelligent vs. conventional control for a process control experiment

While intelligent control methods such as direct, adaptive, and supervisory fuzzy control have shown some success, there is a significant need to evaluate their performance relative to conventional control approaches, particularly in an experimental setting. Such evaluations help to determine the value of the new intelligent control methods and provide the engineer with general guidelines on how to apply them to more complex real-world applications. In this work we conduct a case study where we compare conventional and intelligent controllers for a process control experiment in our laboratory. We study nominal and disturbance conditions