Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Fuzzy control and fuzzy systems (2nd, extended ed.)
Fuzzy control and fuzzy systems (2nd, extended ed.)
Fuzzy logic control for a petroleum separation process
Engineering Applications of Artificial Intelligence
Optimization of Fuzzy If-Then Rule Bases by Evolutionary Tuning of the Operations
ISMVL '09 Proceedings of the 2009 39th International Symposium on Multiple-Valued Logic
Modeling of unmanned small scale rotorcraft based on Neural Network identification
ROBIO '09 Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics
A numerical optimization approach for tuning fuzzy logiccontrollers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In this research, the simulation of the landing and descent of a Boeing 747 in its linearized landing configuration model are controlled using fuzzy logic controllers (FLCs). The rule bases for the FLCs are functions of the linearized model's inputs, the Boeing 747's vertical velocity and altitude. The crisp FLC outputs, as determined by the centroid method, are the elevator and throttle deflections. Different types of membership functions are tested with the FLCs to determine the efficacy of the tested membership types for the given application for landing an aircraft. Future work will involve comparing the FLCs to more conventional controllers.