Abstract
This work deals with the construction of a nonlinear adaptive trajectory controller, which is easily applicable to a multitude of fixed wing unmanned aircraft. Given a common signal interface, the adaptive trajectory controller is divided into a generic part, which is common for each vehicle, and into a part, which is unique. The generic part of the control architecture bases on a common inversion model which is used for feedback linearization. However, the dynamics of the aircraft and the inversion model differ, thus introducing model uncertainties to the feedback linearized system. The effect of modeling uncertainties is reduced by the application of a concurrent learning model reference adaptive controller, which uses neural networks in order to approximate the uncertainty. Leveraging instantaneous as well as stored data concurrently for adaptation ensures convergence of the adaptive parameters to a set of optimal weights, which minimize the approximation error. Performance and robustness against certain model uncertainties is shown through numerical simulation for two significantly different unmanned aircraft.
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References
Åström, K.J., Wittenmark, B.: Adaptive control, 2nd edn. Dover Publications, Mineola (2008)
Bierling, T., Höcht, L., Holzapfel, F., Maier, R., Wildschek, A.: Comparative analysis of mrac architectures in a unified framework. In: AIAA Guidance, Navigation, and Control Conference, Guidance, Navigation, and Control and Co-located Conferences. American Institute of Aeronautics and Astronautics (2010)
Brockhaus, R., Alles, W., Luckner, R.: Flugregelung, 3rd edn. Springer, Berlin (2010)
Calise, A.J., Rysdyk, R.T.: Nonlinear adaptive flight control using neural networks. IEEE Control Systems Magazine 18(6), 14–25 (1998)
Chowdhary, G.: Concurrent Learning for convergence in Adaptive Control without Persistency of Excitation. PhD thesis, Georgia Insitute of Technology, Atlanta and GA (2010)
Chowdhary, G., Jategaonkar, R.: Aerodynamic parameter estimation from flight data applying extended and unscented kalman filter. Aerospace Science and Technology 14(2), 106–117 (2010)
Chowdhary, G., Johnson, E.: Flight test validation of a neural network based long term learning adaptive flight controller. In: AIAA Guidance, Navigation, and Control Conference. Guidance, Navigation, and Control and Co-located Conferences. American Institute of Aeronautics and Astronautics (2009)
Chowdhary, G., Johnson, E.N.: A singular value maximizing data recording algorithm for concurrent learning. In: American Control Conference, San Francisco, CA (June 2011)
Edwards, C., Lombaerts, T., Smaili, H.: Fault tolerant flight control: A benchmark challenge. Springer, Berlin (2010)
Gelb, A.: Applied optimal estimation. M.I.T. Press, Cambridge (1974)
Holzapfel, F.: Nichtlineare adaptive Regelung eines unbemannten Fluggerätes. PhD thesis, Technische Universität München, Munich (2004)
Ioannou, P.A., Kokotovic, P.V.: Instability analysis and improvement of robustness of adaptive control. Automatica 20(5), 583–594 (1984)
Johnson, E.N.: Limited Authority Adaptive Flight Control. PhD thesis, Georgia Insitute of Technology, Atlanta and GA (2000)
Lewis, F.L.: Nonlinear network structures for feedback control. Asian Journal of Control 1(4), 205–228 (1999)
Monahemi, M.M., Krstic, M.: Control of wing rock motion using adaptive feedback linearization. Journal of Guidance, Control, and Dynamics 19(4), 905–912 (1996)
Mühlegg, M., Johnson, E., Chowdhary, G.: Concurrent learning adaptive control of linear systems with noisy measurements. In: AIAA Guidance, Navigation, and Control Conference, Guidance, Navigation, and Control and Co-located Conferences. American Institute of Aeronautics and Astronautics (2012)
Narendra, K., Annaswamy, A.: A new adaptive law for robust adaptation without persistent excitation. IEEE Transactions on Automatic Control 32(2), 134–145 (1987)
Narendra, K.S., Annaswamy, A.M.: Stable adaptive systems. Dover Publications, Mineola (2005)
Nguyen, N.T., Jacklin, S.A.: Neural net adaptive flight control stability. In: Verification and Validation Challenges, and Future Research, IJCNN Conference (2007)
Park, J., Sandberg, I.W.: Universal approximation using radial-basis-function networks. Neural Computation 3(2), 246–257 (1991)
Sanner, R.M., Slotine, J.-J.E.: Gaussian networks for direct adaptive control. IEEE Transactions on Neural Networks 3(6), 837–863 (1992)
Seanor, B.A.: Flight Testing of a Remotely Piloted Vehicle for Aircraft Parameter Estimation Purposes. PhD thesis, West Virginia University, Morgantown and West Virginia (2002)
Shankar, P., Yedavalli, R.K., Burken, J.J.: Self-organizing radial basis function networks for adaptive flight control. Journal of Guidance, Control, and Dynamics 34(3), 783–794 (2011)
Cong, S., Song, R.: An improved b-spline fuzzy-neural network controller, pp. 1713–1717
Stevens, B.L., Lewis, F.L.: Aircraft control and simulation, 2nd edn. J. Wiley, Hoboken (2003)
Tao, G.: Adaptive control design and analysis. Wiley-Interscience, Hoboken (2003)
Verhaegen, M., Kanev, S., Hallouzi, R., Jones, C., Maciejowski, J., Smail, H.: Fault tolerant flight control - a survey. In: Morari, M., Thoma, M., Edwards, C., Lombaerts, T., Smaili, H. (eds.). LNCIS, pp. 47–89. Springer, Heidelberg (2010)
Volyanskyy, K.Y., Haddad, W.M., Calise, A.J.: A new neuroadaptive control architecture for nonlinear uncertain dynamical systems: Beyond sigma - and e-modifications. IEEE Transactions on Neural Networks 20(11), 1707–1723 (2009)
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Mühlegg, M., Dauer, J.C., Dittrich, J., Holzapfel, F. (2013). Adaptive Trajectory Controller for Generic Fixed-Wing Unmanned Aircraft. In: Chu, Q., Mulder, B., Choukroun, D., van Kampen, EJ., de Visser, C., Looye, G. (eds) Advances in Aerospace Guidance, Navigation and Control. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38253-6_27
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DOI: https://doi.org/10.1007/978-3-642-38253-6_27
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