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The longitudinal automatic carrier landing system (ACLS) control law is designed based on nonlinear dynamic inversion (NDI), which can reject air wake, decouple lateral states, and track the dynamic desired touchdown point (DTP). First of all, the nonlinear landing model of F/A−18 aircraft in the final approach is established, in which the parameters of the aerodynamic, control surfaces, and limited states are acquired. Second, the strategy of tracking the desired longitudinal trajectory through pitch angle control is adopted. The automatic power compensation system (APCS), pitch angle rate, pitch angle, and vertical position control loops are developed based on the adaptive NDI. The stable analysis and the principal description are derived in detail. Deck motion compensation (DMC) algorithm is designed by frequency response method. Third, the control parameters are optimized through the genetic algorithm. A fitness function integrated with velocity, angle of attack (AOA), pitch rate, pitch angle, and vertical position of the aircraft are proposed. Finally, integrated simulations are conducted on a semi-physical simulation platform. The results indicate that the adopted automatic landing control law can achieve both excellent performance and the ability to reject the air wake and lateral coupling.
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Tom
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art. no. e136217
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Bibliogr. 34 poz., rys., tab.
Twórcy
autor
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China
autor
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China
autor
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China
autor
- AVIC Xi’an Flight Automatic Control Research Institute, Xi’an, 710065, China
Bibliografia
- [1] M. Ryota and S. Shinji, “Modeling of pilot landing approach control using stochastic switched linear regression model”, J. Aircr. 47(5), 1554–1558 (2010).
- [2] J. Tian, Y. Dai, H. Rong, and T.D. Zhao, “Hybrid safety analysis method based on SVM and RST: An application to carrier landing of aircraft”, Saf. Sci. 80, 56–65 (2015).
- [3] L.P. Wang, Q.D. Zhu, Z. Zhang, and R. Dong. “Modeling pilot behaviors based on discrete–time series during carrier-based aircraft landing”, J. Aircr. 53(6), 1922–1931 (2016).
- [4] J.M. Urnes and R.K. Hess, “Development of the F/A−18A automatic carrier landing system”, J. Guid. 8(3), 289-295 (1985).
- [5] Z.Y. Guan, Y.P. Ma, and Z.W. Zheng, “Prescribed performance control for automatic carrier landing with disturbance”, Nonlinear Dyn. 94(2),¸t 1335–1349 (2018).
- [6] Z.Y. Zhen, S.Y. Jiang, and K. Ma, “Automatic carrier landing control for unmanned aerial vehicles based on preview control and particle filtering”, Aerosp. Sci. Technol. 81, 99–107 (2018).
- [7] Z.Y. Zhen, S.Y. Jiang, and J. Jiang, “Preview control and particle filtering for automatic carrier landing”, IEEE Trans. Aerosp. Electron. Syst. 54(6), 2662–2674 (2018).
- [8] R. Lungu and M. Lungu, “Design of automatic landing systems using the H-inf control and the dynamic inversion”, J. Dyn. Syst. Meas. Control-Trans. ASME. 138(2), 1–5 (2016).
- [9] R. Lungu and M. Lungu, “Automatic Landing system using neural networks and radio-technical subsystems”, Chin. J. Aeronaut. 30(1), 399–411 (2017).
- [10] M. Lungu and R. Lungu, “Automatic control of aircraft lateraldirectional motion during landing using neural networks and radio-technical subsystems”, Neurocomputing. 171, 471–481 (2016).
- [11] Q. Bian, B. Nener, T. Li, and X.M. Wang, “Multimodal control parameter optimization for aircraft longitudinal automatic landing via the hybrid particle swarm-BFGS algorithm”, Proc. Inst. Mech. Eng. Part G-J. Aerosp. Eng. 233(12), 4482–4491 (2019).
- [12] F.Y. Zheng, Z.Y. Zhen, and H.J. Gong, “Observer-based backstepping longitudinal control for carrier-based UAV with actuator faults”, J. Syst. Eng. Electron. 28(2), 322–337 (2017).
- [13] Z.Y. Zhen, C.J. Yu, and S.Y. Jiang, “Adaptive super-twisting control for automatic carrier landing of aircraft”, IEEE Trans. Aerosp. Electron. Syst. 56(2), 987–994 (2020).
- [14] Z.Y. Zhen, G. Tao, and C.J. Yu, “A multivariable adaptive control scheme for automatic carrier landing of UAV”, Aerosp. Sci. Technol. 92, 714–721 (2019).
- [15] L.P. Wang, Z. Zhang, Q.D. Zhu, and R. Dong, “Longitudinal automatic carrier landing system guidance law using model predictive control with an additional landing risk term”, Proc. Inst. Mech. Eng. Part G-J. Aerosp. Eng. 233(3), 1–17 (2019).
- [16] L.P. Wang, Z. Zhang, and Q.D. Zhu, “Automatic Flight Control Design Considering Objective and Subjective Risks during Carrier Landing”, Proc. Inst. Mech. Eng. Part I-J Syst Control Eng. 234(4), 446–461 (2020).
- [17] L.P. Wang, Z. Zhang, Q.D. Zhu, X.W. Jiang, “Lateral autonomous carrier-landing control with high-dimension landing risks consideration”, Aircr. Eng. Aerosp. Technol. 92(6), 837– 850 (2020).
- [18] T. Woodbury and J. Valasek, “Synthesis and flight test of an automatic landing controller using quantitative feedback theory”, J. Guid. Control Dyn. 39(9), 1994–2010 (2016).
- [19] B. Xu, D.W. Wang, Y.M. Zhang, and Z.K. Shi, “DOB-based neural control of flexible hypersonic flight vehicle considering wind effects”, IEEE Trans. Ind. Electron. 64(11), 8676–8685 (2017).
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- [21] J.N. Li and H.B. Duan, “Simplified brain storm optimization approach to control parameter optimization in F/A−18 automatic carrier landing system”, Aerosp. Sci. Technol. 42, 187–195 (2015).
- [22] R. Dou and H.B. Duan, “Levy flight based pigeon-inspired optimization for control parameters optimization in automatic carrier landing system”, Aerosp. Sci. Technol. 61, 11–20 (2017).
- [23] K. Lu and C.S. Liu, “A L-1 adaptive control scheme for UAV carrier landing using nonlinear dynamic inversion”, Int. J. Aerosp. Eng. 1–9 (2019).
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- [25] H. Bouadi, F.M. Camino, and D. Choukroun, “Space–Indexed Control for Aircraft Vertical Guidance with Time Constraint”, J. Guid. Control Dyn. 37(4), 1103–1113 (2014).
- [26] P.K. Menon, S.S. Vaddi, and P. Sengupta, “Robust landingguidance law for impaired aircraft”, J. Guid. Control Dyn. 35(6), 1865−1877 (2012).
- [27] W.H. Chen, “Nonlinear Disturbance observer-enhanced dynamic inversion control of missiles”, J. Guid. Control Dyn. 26(1), 161–166 (2003).
- [28] I. Hameduddin and A.H. Bajodah, “Nonlinear generalised dynamic inversion for aircraft manoeuvring control”, Int. J. Control. 85(4), 437–450 (2012).
- [29] R. Lungu and M. Lungu, “Design of automatic landing systems using the H-inf control and the dynamic inversion”, J. Dyn. Syst. Meas. Control-Trans. ASME. 138(2), 1–5 (2016).
- [30] M. Lungu and R. Lungu, “Landing auto-pilots for aircraft motion in longitudinal plane using adaptive control laws based on neural networks and dynamic inversion”, Asian J. Control. 19(1), 302–315 (2017).
- [31] R. Lungu and M. Lungu, “Automatic control of aircraft in lateral-directional plane during landing”, Asian J. Control. 18(2), 433–446 (2016).
- [32] A. Chakraborty, P. Seiler, and G. J. Balasz, “Applications of linear and nonlinear robustness analysis techniques to the F/A-18 flight control laws”, AIAA Guidance, Navigation, and Control conference. Chicago, USA, 2009, pp.10–13.
- [33] A. Chakraborty, P. Seiler, and G. J. Balas, “Susceptibility of F/A−18 flight controllers to the falling-leaf mode: nonlinear analysis”, J. Guid. Control Dyn. 34(1), 57–72 (2011).
- [34] J.M. Urnes, and R.K. Hess, “Development of the F/A-18A Automatic Carrier Landing System”, J. Guid. 8(3), 289–295 (1985).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
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Bibliografia
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bwmeta1.element.baztech-f025b169-6758-45c2-893b-2a8534296782