Abstract
This chapter focuses on the application of the methods developed in previous chapters to a common benchmark to compare them (when relevant) regarding their performance and evaluate the easiness of their applicability. The most promising techniques have been further tested in a real industrial context, with more complex requirements to fulfill and using a certified aircraft model as reference. Based on this application an integrated validation strategy is proposed to comply with the industrial validation needs.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Fielding, C., Varga, A., Bennani, S., Selier, M. (eds.): Advanced Techniques for Clearance of Flight Control Laws. LNCIS, vol. 283. Springer, Berlin (2002)
Forssell, L.S., Hyden, A.: Flight control system validation using global nonlinear optimisation algorithms. In: Proc. of the European Control Conference, Cambridge, United Kingdom (2003)
Menon, P.P., Bates, D.G., Postlethwaite, I.: Optimisation-based flight control law clearance. In: Bates, D., Hagström, M. (eds.) Nonlinear Analysis and Synthesis Techniques for Aircraft Control. LNCIS, vol. 365, pp. 259–300. Springer, Berlin (2007)
Menon, P., Bates, D., Postlethwaite, I.: Computation of worst-case pilot inputs for clearance of flight control laws. In: Proc. of the 16 th IFAC World Congress, Prague, Czech Repulic (2005)
Menon, P., Bates, D., Postlethwaite, I.: Hybrid Optimisation Schemes for the Clearance of Flight Control Laws. In: Proc. of the 16 th IFAC World Congress, Prague, Czech Repulic (2005)
Menon, P.P., Kim, J., Bates, D.G., Postlethwaite, I.: Clearance of nonlinear flight control laws using hybrid evolutionary optimisation. IEEE Transactions on Evolutionary Computation 10(6), 689–699 (2006)
Oliveira, R.F., Puyou, G.: Clearance of Flight Control Laws using Multi-objective optimisation. In: Proc. of 2010 International Conference on Genetic and Evolutionary Methods, Las Vegas, USA (2010)
Smith, J.E., Eiben, A.E.: Introduction to Evolutionary Computing. Springer, Berlin (2003)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6(2), 182–197 (2002)
Ferreres, G., Puyou, G.: Flight control law design for a flexible aircraft: Limits of performance. Journal of Guidance Control and Dynamics 29(4), 870–878 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Puyou, G., de Oliveira, R.F., Berard, A. (2012). Evaluation of Clearance Techniques in an Industrial Context. In: Varga, A., Hansson, A., Puyou, G. (eds) Optimization Based Clearance of Flight Control Laws. Lecture Notes in Control and Information Sciences, vol 416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22627-4_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-22627-4_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22626-7
Online ISBN: 978-3-642-22627-4
eBook Packages: EngineeringEngineering (R0)