Abstract
In this paper, a novel control parameter design method is presented for the automatic carrier landing system. To overcome difficulties in the manual parameter adjustment task, the pigeon-inspired optimization algorithm is utilized by converting the parameter design problem to an optimization problem. The modified version is proposed to avoid the lack of the diversity of pigeon population in the basic version. Parameters in the inner loop are optimized by computing the fitting difference between an ideal frequency response curve and the frequency response curve of the optimized control system. To optimize control parameters in the H-dot autopilot and the approach power compensation system, a weighted linear cost function in the time domain is adopted. Series of experiments are conducted to demonstrate the feasibility and effectiveness of our method. Comparative results indicate that out method is much better than other methods.
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Martorella, P., Kelly, C., Nastasi, R.: Precision flight path control in carrier landing approach—a case for integrated system design. AIAA Aircraft Systems and Technology Conference, Dayton, Ohio, USA, AIAA-81-1710, pp. 1–10 (1981)
Urnes, J.M., Hess, R.K.: Development of the F/A-18A automatic carrier landing system. J. Guid Control Dyn 8(3), 289–295 (1985)
Urnes, J.M., Hess, R.K., Moomaw, R.F., Huff, R.W.: Development of the navy H-dot automatic carrier landing system designed to give improved approach control in air turbulence. AIAA Guidance and Control Conference, New York, USA, AIAA-79-1772, pp. 491–501 (1979)
Craig, S.J., Ringland, R.F., Ashkenas, I.L.: An analysis of navy approach power compensator problems. J. Aircr. 9(10), 737–743 (1972)
Zhu, Q., Wang, T., Zhang, W., Zhou, F.: Variable structure approach power compensation system design of an automatic carrier landing system. Control and Decision Conference, Guilin, China, pp. 5517–5521 (2009)
Urnes, J.M., Hess, R.K., Moomaw, R.F., Huff, R.W.: H-dot automatic carrier landing system for approach control in turbulence. J. Guid. Control Dyn. 4(2), 177–183 (1981)
Prickett, A.L., Parkes, C.J.: Flight testing of the F/A-18E/F automatic carrier landing system. In: Proceedings of IEEE Aerospace Conference, Montana, USA vol. 5, pp. 2593–2612 (2001)
Steinberg, M.L.: Development and simulation of an F/A-18 fuzzy logic automatic carrier landing system. In: Proceedings of the Second IEEE International Conference on Fuzzy Systems, San Francisco, USA, vol. 2, pp. 797–802 (1993)
Subrahmanyam, M.B.: H-infinity design of F/A-18A automatic carrier landing system. J. Guid. Control Dyn. 17(1), 187–191 (1994)
Crassidis, J.L., Mook, D.J.: Robust control design of an automatic carrier landing system. AIAA Astrodynamics Conference, Hilton Head Island, USA, AIAA-92-4619, pp. 1471–1481 (1992)
Steinberg, M.L., Page, A.B.: A comparison of neural, fuzzy, evolutionary, and adaptive approaches for carrier landing. AIAA Guidance, Navigation, and Control Conference and Exhibit, Montreal, Canada, AIAA-2001-4085, pp. 1–11 (2001)
Baker, W.L., Farrell, J.A.: Learning augmented flight control for high performance aircraft. AIAA Guidance, Navigation, and Control Conference, New Orleans, USA, AIAA-91-2836, pp. 347–358 (1991)
Steinberg, M.L., Page, A.B.: Nonlinear adaptive flight control with genetic algorithm design optimization. Int. J. Robust Nonlinear Control 9(14), 1097–1115 (1999)
Lan, X., Wang, Y., Liu, L.: Dynamic decoupling tracking control for the polytopic LPV model of hypersonic vehicle. Sci. China Inf. Sci. 58(9), 1–14 (2015)
Akay, B., Karaboga, D.: A modified artificial bee colony algorithm for real-parameter optimization. Inf. Sci. 192, 120–142 (2012)
Qian, C., Yu, Y., Zhou, Z.: Variable solution structure can be helpful in evolutionary optimization. Sci. China Inf. Sci. 58(11), 1–17 (2015)
Brest, J., Zumer, V., Maucec, M.S.: Self-adaptive differential evolution algorithm in constrained real-parameter optimization. IEEE Congress on Evolutionary Computation, Vancouver, Canada, pp. 215–222 (2006)
Duan, H., Wang, X.: Biologically adaptive robust mean shift algorithm with Cauchy predator–prey BBO and space variant resolution for unmanned helicopter formation. Sci. China Inf. Sci. 57, 112202:1–112202:13 (2014)
Krishnakumar, K., Goldberg, D.E.: Control system optimization using genetic algorithms. J. Guid. Control Dyn. 15(3), 735–740 (1992)
Li, J., Duan, H.: Simplified brain storm optimization approach to control parameter optimization in F/A-18 automatic carrier landing system. Aerosp. Sci. Technol. 42, 187–195 (2015)
Duan, H., Qiao, P.: Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. Int. J. Intell. Comput. Cybernet. 7(1), 24–37 (2014)
Zhao, J., Zhou, R.: Pigeon-inspired optimization applied to constrained gliding trajectories. Nonlinear Dyn. 82(4), 1781–1795 (2015)
Li, C., Duan, H.: Target detection approach for UAVs via improved pigeon-inspired optimization and edge potential function. Aerosp. Sci. Technol. 39, 352–360 (2014)
Zhang, B., Duan, H.: Three-dimensional path planning for uninhabited combat aerial vehicle based on predator–prey pigeon-inspired optimization in dynamic environment. IEEE/ACM Trans. Comput. Biol. Bioinf. doi:10.1109/TCBB.2015.2443789 (in press, 2016)
Duan, H., Wang, X.: Echo state networks with orthogonal pigeon-inspired optimization for image restoration. IEEE Trans. Neural Netw. Learn. Syst. in press, doi:10.1109/TNNLS.2015.2479117 (2016)
Yuan, Y.: A dynamic games approach to H\(\infty \) control design of DoS with application to longitudinal flight control. Sci. China Inf. Sci. 58(9), 1–10 (2015)
Duan, H., Sun, C.: Pendulum-like oscillation controller for micro aerial vehicle with ducted fan based on LQR and PSO. Sci. China Technol. Sci. 56(2), 423–429 (2013)
Zhao, Z., Wu, X., Lu, C., Glotin, H., Gao, J.: Optimizing widths with PSO for center selection of Gaussian radial basis function networks. Sci. China Inf. Sci. 57(5), 1–17 (2014)
Guilford, T., Roberts, S., Biro, D., Rezek, I.: Positional entropy during pigeon homing II: navigational interpretation of Bayesian latent state models. J. Theor. Biol. 227(1), 25–38 (2004)
Bischoff, D.: The definition of short-period flying qualities characteristics via equivalent systems. J. Aircr. 20(6), 494–499 (1983)
Pires, E.J.S., Machado, J.A.T., de Moura Oliveira, P.B., et al.: Particle swarm optimization with fractional-order velocity. Nonlinear Dyn. 61(1–2), 295–301 (2010)
Li, X., Yin, M.: Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm. Nonlinear Dyn. 77(1–2), 61–71 (2014)
Yang, X.S.: A New Metaheuristic Bat-Inspired Algorithm. Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Springer, Berlin (2010)
Acknowledgments
This work was partially supported by National Natural Science Foundation of China under grant #61425008, #61333004 and #61273054, National Key Basic Research Program of China (973 Project) under grant #2014CB046401, and Aeronautical Foundation of China under grant #2015ZA51013. The authors would like to thank the editors and reviewers for their critical review of this manuscript.
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Deng, Y., Duan, H. Control parameter design for automatic carrier landing system via pigeon-inspired optimization. Nonlinear Dyn 85, 97–106 (2016). https://doi.org/10.1007/s11071-016-2670-z
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DOI: https://doi.org/10.1007/s11071-016-2670-z