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The use of fuzzy logic in adaptive flight control systems

Published online by Cambridge University Press:  04 July 2016

G. Mengali
G. Mengali*
Affiliation:
Dipartimento di Ingegneria Aerospaziale, Università di Pisa, Via Diotisalvi, Pisa, Italy
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Abstract

A two step procedure is proposed for the design of nonlinear aircraft control systems. A classical design is first denned, based on a linearised aircraft model, and easily optimised by means of standard approaches. An outer-loop nonlinear controller is then used to enhance the whole control system. This latter controller is based on fuzzy logic rules and is of fixed structure. Its behaviour is based on the choice of a set of parameters that may be tuned by means a genetic algorithm based routine. The whole methodology is simple to handle and may be effectively used to give quick and efficient responses to the designer. The procedure has been verified with a couple of examples: the obtained results clearly show important improvements with respect to a classical methodology.

Type
Research Article
Information
The Aeronautical Journal , Volume 104 , Issue 1031 , January 2000 , pp. 31 - 37
Copyright
Copyright © Royal Aeronautical Society 2000 

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References

1. Mcruer, D.I., Ashkenas, I. and Graham, D. Aircraft Dymamics and Automatic Control, Princeton University Press, Princeton, NJ, 1973.Google Scholar
2. McLean, D. Automatic Flight Control Systems, Prentice-Hall, New York, 1990.Google Scholar
3. Larkin, L.I. A Fuzzy Logic Controller for Aircraft Flight Control, Industrial Applications of Fuzzy Control, Sugeno, M. (Ed), Amsterdam: North-Holland, 1985, pp 87–104.Google Scholar
4. Nho, K. and Agarwal, R.K. Application of fuzzy logic to wing rock motion control, Proceedings of the AIAA 36th Aerospace Sciences, AIAA Paper 98-0497, Reno, NV, 1988.Google Scholar
5. Nho, K. and Agarwal, R.K. Automatic landing system design using fuzzy logic, AIAA Guidance, Navigation and Control Conference, AIAA Paper 98-4484, Boston, MA, 1998.Google Scholar
6. Lin, C.F. and Ge, J. Integrated fuzzy/Hx control for turbofan engines, AIAA Guidance, Navigation and Control Conference, AIAA Paper 98-4198, Boston, MA, 1998.Google Scholar
7. Zakian, V. and Al-Naib, U. Design of dynamical and control systems by the method of inequalities, Proceedings of the Institution of Electrical Engineers, 120, (11), 1973, pp 1421–1427.Google Scholar
8. Mamdani, E.H. Applications of fuzzy logic to approximate reasoning using linguistic synthesis, IEEE Transactions on Computers, 26, (12), 1977, pp 1182–1191.Google Scholar
9. Driankov, D., Hellendoorn, H. and Reinfrank, M. An Introduction to Fuzzy Control, Springer-Verlag, Berlin, 1993.Google Scholar
10. Holland, J.H. Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, 1975.Google Scholar
11. Goldberg, D.E. Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, New York, 1989.Google Scholar
12. Malki, H.A., Li, H. and Chen, G. New Design and Stability Analisys of Fuzzy Proportional-Derivative Control Systems, IEEE Transactions on Fuzzy Systems, 2, (4), 1994, pp 245–254.Google Scholar
13. Stevens, B. L. and Lewis, F.L. Aircraft Control and Simulation, John Wiley and Sons, New York, 1992.Google Scholar