Abstract
In this paper, we consider different approaches for the neural network controller tuning in the flight control system. Two of the most common tuning approaches in the adaptive control theory are applied. The first one uses parameter identification technique and consists in solving a real-time regression problem for the control law. The second approach is based on the Lyapunov direct method, which utilizes a tracking error as an absolute measure of tuning performance. The neural network control law are designed for the three-axis flight control problem and tested on the full nonlinear model of a fighter aircraft. Closed loop simulation results are presented and two adaptation algorithms are compared in the case of abrupt change of aircraft dynamics.
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Aerodinamika, ustoichivost’ i upravlyemost’ sverkhzvukovykhh samoletov (Aerodynamics, Stability and Controllability of Supersonic Aircraft), Byushengens, G.S., (Ed.), Moscow: Nauka, Fizmatlit, 1998.
Sonneveldt, L., Nonlinear F-16 Fighter Model, Matlab Central — An Open Exchange for the MATLAB and Simulink User Community, URL: http://www.mathworks.com/matlabcentral.
Sastry, S. and Bodson, M., Adaptive Control: Stability, Convergence, and Robustness, Englewood Cliffs, New Jersey: Prentice Hall, 1989.
Miroshnik, I.V., Nikiforov, V.O., and Fradkov, A.L., Nelineinoe i adaptivnoe upravlenie slozhnymi dinamicheskimi sistemami (Nonlinear and Adaptive Control of Complex Dynamic Systems), St. Petersburg: Nauka, 2000.
Astrom, K. J. and Wittenmark, B., Adaptive Control, New Jersey: Prentice Hall, 1994.
Ioannou, P. A. and Sun, J., Robust Adaptive Control, New Jersey: Prentice Hall, 1995.
Farrell, J. A. and Polycarpou, M.M., Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches, N.Y.: John Wiley & Sons, 2006.
Spooner, J. T., Maggiore, M., Ordonez, R., and Passino, K.M., Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques, N.Y.: John Wiley & Sons, 2002.
Terekhov, V.A., Efimov, D.V., and Tyukin, I.Yu., Neirosetevye sistemy upravleniya (Neural Network Control Systems), Moscow: IPRZHR, 2002.
Kim, B.S. and Calise, A.J., Nonlinear Flight Control Using Neural Networks, AIAA Guidance, Navigation, and Control Conference, Scottsdale, Arizona, 1994.
Nakanishi, J. and Schaal, S., Feedback Error Learning and Nonlinear Adaptive Control, Neural Networks, 2004, no. 17, pp. 1453–1465.
Sonneveldt, L., Van Oort, E. R., Chu, Q. P., de Visser, C.C., and Mulder, J. A., Lyapunov-based Fault Tolerant Flight Control Designs for a Modern Fighter Aircraft Model, AIAA Guidance, Navigation, and Control Conference, Chicago, Illinois, 2009.
Burken, John J., Nguyen, Nhan T., and Griffin, Brian J., Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model, AIAA 2019-3364, NASA Dryden Flight Research Center, 2010.
Neural Systems for Control, Omidvar, O.M. and Elliott. D.L., Academic Press, 1997. 358 p.
Haykin, Simon S., Neural Networks, Prentice Hall Int., 2006.
Narendra, K.S. and Parthasarathy, K., Identification and Control of Dynamic Systems Using Neural Networks, IEEE Trans. on Neural Networks, 1990, vol. 1, no. 1, pp. 4–27.
Hagan, M.T., De Jesus O, and Schultz, R., Training Recurrent Networks for Filtering and Control, Recurrent Neural Networks: Design and Applications. USA: CRC Press, 1999. Chapter 12. P. 311–340.
Psaltis, D., Sideris, A., and Yamamura, A.A., A Multilayered Neural Network Controller, IEEE Control Systems Magazine, 1988, vol. 8, no. 2, pp. 17–21.
Spravochnik po teorii avtomaticheskogo upravleniya (Handbook on Automatic Control Theory), Krasovskii, A.A., Ed., Moscow: Nauka, 1987.
Tsypkin, Ya.Z., Adaptatsiya i obuchenie v avtomaticheskikh sistemakh (Adaptation and Training in Automatic Controls), Moscow: Nauka, 1968.
Kondrat’ev, A.I. and Tyumentsev, Yu.V., Neural Network Adaptive Fail-Safe Control of Maneuverable Aircraft Motion, Trudy vsepossiiskoi nauchno-tekhnischeskoi konferentsii “Neiroinformatika-2010” (Proc. All-Russian Sc.-Tech. Conf. “Neural Automatics-2010”, Moscow: Izd. MIFI, 2010.
Kalman Filtering and Neural Networks, Haykin, S., Ed., N.Y.: John Wiley & Sons, 2001.
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Original Russian Text © A.I. Kondrat’ev, Yu.V. Tyumentsov, 2013, published in Izvestiya VUZ. Aviatsionnaya Tekhnika, 2013, No. 3, pp. 34–39.
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Kondrat’ev, A.I., Tyumentsev, Y.V. Application of neural networks for the design of flight control algorithms. II Adaptive tuning of neural network control law. Russ. Aeronaut. 56, 257–265 (2013). https://doi.org/10.3103/S1068799813030070
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DOI: https://doi.org/10.3103/S1068799813030070