Neural networks and fuzzy logic have the potential to overcome some of the most difficult problems that occur in the design and implementation of modern Flight Control Systems (FCS). Ultimately, this may yield significant gains in performance, robustness, cost survivability and reliability. However, it is still uncertain what neural network and fuzzy logic functions are both technologically feasible and suitable for flight control system implementation. In this report, an ongoing comprehensive program to develop and assess this technology for Naval FCS applications is described. Currently, this program is focused on the development of a neural network FCS design tool, a neural network flight control law emulator, a fuzzy logic automatic carrier landing system and a neural network flight control configuration management system. For each project, some initial results are given. Also, several new and planned projects are discussed. These include learning augmented adaptive control, neural network augmented nonlinear control, optical neurons and neural augmentation of conventional control systems.


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    Comparison of Neural-Network-Based, Fuzzy-Logic-Based, and Numerical Nonlinear Inverse Flight Controls

    Huang, C. / Tylock, J. / Engel, S. et al. | British Library Conference Proceedings | 1994


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    Villarreal, James A. / Lea, Robert N. / Savely, Robert T. | NTRS | 1992



    Fuzzy logic and neural network technologies

    VILLARREAL, JAMES / LEA, ROBERT / SAVELY, ROBERT | AIAA | 1992