Gain-scheduled directional guidance controller design using a genetic algorithm for automatic precision landing
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This paper discusses the guidance controller design problem of an aircraft in automatic landing and touchdown flight, subject to dangerous and unpredictable gusts known as wind-shear and to directional crosswind. The associated airplane in the landing flight was statically unstable in this paper. The wind-shear, based on the Dryden gust model, was included in the nonlinear airplane model. A directional guidance control system with gain-scheduling fuzzy logic was proposed in this paper. In fuzzy logic, an even number of exponential membership functions in the output are considered and their shape, decay rate, and scaling factors are optimized using a genetic algorithm. In this control system, the glide slope capture logic and the flare logic were also included for longitudinal and lateral control, respectively. The nonlinear aircraft model simulation illustrated that the proposed guidance control system shows satisfactory performances in accurate touchdowns and is adequately robust to the strong crosswind and wind-shear turbulences.
KeywordsAutomatic landing fuzzy gain-scheduled controller genetic algorithm wind shear
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- National Transportation Safety Board Weather Related Accidents, http://www.asy.faa.gov/safety_analysis/weather_study/totals.
- R. E. Bach and R. C. Wingrove, “The analysis of airline flight records for winds and performance with application to the delta 191 accident,” Proc. of the AIAA Atmospheric Flight Mechanics Conference, pp. 361–373, Aug. 18–20, 1986.Google Scholar
- W. Frost, Flight in Low Level Wind Shear, NASA CR-3678, 1983.Google Scholar
- National Severe Storms Laboratory, URL: http://www.nssl.noaa.gov/ (cited on July 13, 2005).
- B. L. Stevens and F. L. Lewis, Aircraft Control and Simulation, John Wiley & Sons, Inc., New York, 1992.Google Scholar
- M. B. Ghalia and A. T. Alouani, “Robust control design of an auto-landing system,” Proc. of the 25th Southeastern Symposium on System Theory, pp. 248–252, March 1993.Google Scholar
- A. P. Kurdjukov, B. V. Pavlov, and V. N. Timin, “Longitudinal flight control in windshear via H ∞ — methods,” Proc. of AIAA Guidance, Navigation, and Control Conference, AIAA 96-3727, pp. 1–6, 1996.Google Scholar
- S. P. Shue, K. Ramesh, and P. Shi, “Robust aircraft control design for glide slope capture in windshear using gain scheduling,” Proc. of AIAA Guidance, Navigation, and Control Conference, AIAA 98-4299, pp. 1–12, 1998.Google Scholar
- J. Juang, H. Chang, and K. Cheng, “Intelligent landing control using linearized inverse aircraft model,” Proc. of American Control Conference, vol. 4, pp. 3269–3274, 2001.Google Scholar
- J. Juang, K. Chin, and J. Chio, “Intelligent automatic landing system using fuzzy neural networks and genetic algorithm,” Proc. of American Control Conference, Boston, MA, pp. 5790–5795, June 30–July 2, 2004.Google Scholar
- C. Ha and J. Kim, “Automatic landing under wind shear turbulence in adaptive gain scheduled PID control optimized in genetic algorithm,” Proc. of AIAA Guidance, Navigation and Control Conference and Exhibit, AIAA 2005-6346, 15–18 August 2005.Google Scholar
- D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.Google Scholar
- Y. J. Park, H. S. Cho, and D. H. Cha, “Genetic algorithm-based optimization of fuzzy logic controller using characteristic parameters,” Proc. of IEEE International Conference on Evolutionary Computation, pp. 831–836, 1995.Google Scholar
- D. McLean, Automatic Flight Control Systems, Prentice Hall, 1990.Google Scholar
- K. C. Jeong, S. H. Kwon, D. H. Lee, M. W. Lee, and J. Y. Choi, “A fuzzy logic-based gain tuner for PID controllers,” Proc. of IEEE World Congress on Computational Intelligence, pp. 551–554, 4–6 May, 1998.Google Scholar
- S. Hayashi, “Auto tuning fuzzy logic controller,” Proc. of IFSA International Fuzzy Systems Associates, pp. 41–44, 1991.Google Scholar
- D. Whitely, A Genetic Algorithm Tutorial, Technical Report CS-93-103, Colorado State University, 1993.Google Scholar