ABSTRACT
Fuzzy logic controllers serve the same function as the more conventional controllers, but they manage complex control problems through heuristics and mathematical models provided by fuzzy logic, rather than via mathematical models provided by differential equations. This is particularly useful for controlling systems whose mathematical models are nonlinear or for which standard mathematical models are simply not available. The implementations of fuzzy control are, in some sense, imitations of the
control laws that humans use. Creating machines to emulate human expertise in control gives us a new way to design controllers for complex plants whose mathematical models are not easy to specify. The new design techniques are based on more general types of knowledge than differential equations describing the dynamics of the plants.
