Trajectory tracking in aircraft landing operations management using the adaptive neural fuzzy inference system

Authors:
D. M. Liu;G. Naadimuthu;E. S. Lee
Affiliations:
Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS 66506, United States;Department of Information Systems and Decision Sciences, Silberman College of Business, Fairleigh Dickinson University, Madison, NJ 07940, United States;Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS 66506, United States
Venue:
Computers & Mathematics with Applications
Year:
2008

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Abstract

The adaptive neural fuzzy inference system is used to simulate trajectory tracking in aircraft landing operations management. The advantage of the approach is that by using the linguistic representation ability of fuzzy sets and the learning ability of neural networks, the approximate linguistic representations can be improved or updated as more data become available. This approach is illustrated by the use of both zero and first order Takagi-Sugeno inference systems [T. Takagi, M. Sugeno, Fuzzy identification of systems and its application to modeling and control, IEEE Transactions on Systems, Man, and Cybernetics 15 (1) (1985) 116-132] with auto-landing flight path data.