A genetic algorithm based fuzzy logic controller for nonlinear systems

There have been many attempts to design intelligent tracking controllers for nonlinear control applications, such as dynamic fatigue test rigs, industrial robots and flight simulators. An evolutionary, genetic algorithm based tuneable fuzzy logic controller has been designed for such dynamic servomechanisms. Results obtained prove the scheme successful and it yields a robust controller, as well as reduces design complexity.