Fuzzy Logic Control Using Matlab

The assumption that all engineering system modeling can be reduced to an exact set of differential equations has been challenged by research that recognizes that process modeling and control can never be exact for real processes. There is a necessity for advanced control techniques that can

• Manage Uncertain Environment
• Incorporate techniques for learning uncertain information

Over the last few years, the application of Artificial Intelligence techniques has become a major research topic in process control. AI techniques allow obtaining efficient controllers that utilize human experience in a more related form than a mathematical approach. Fuzzy Logic (FL) is the main topic of this new field known as Expert Control. It provides an effective framework for dealing with an uncertain and vague environment. It uses Fuzzy Logic Controllers (FLCs) to implement an operator approximate reasoning process in the selection of the control process. According to a survey, 6 of every 10 Americans use a device that employs FLC in some form. In Japan, Fuzzy Logic has been used to control underground railway systems. FLC is also being used extensively in consumer electronics like Air conditioners, Microwave ovens, Cameras, etc.