Abstract
This paper presents an intelligent automatic landing system that uses adaptive fuzzy neural network controller to improve the performance of conventional automatic landing systems. Functional fuzzy rules are implemented in neural network. In this study, Lyapunov stability theory is utilized to derive adaptive learning rate in the controller design. Stability of the control system is guaranteed. Simulation results show that the fuzzy neural network controller with adaptive learning rate has better performance than PID controller in guiding aircraft to a safe landing in turbulence condition.
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Juang, JG., Chien, LH. (2010). Adaptive Fuzzy Neural Network Control for Automatic Landing System. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6421. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16693-8_53
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DOI: https://doi.org/10.1007/978-3-642-16693-8_53
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