This chapter describes the development of evolutionary and deterministic global optimisation methods for the clearance of nonlinear flight control laws for highly augmented aircraft. The algorithms are applied to the problem of evaluating a nonlinear handling qualities clearance criterion for the ADMIRE benchmark model. An optimisation-based approach for computing worst-case pilot input demands is also presented. Hybrid versions of the global algorithms, incorporating local gradient-based optimisation, are shown to significantly reduce computational complexity while at the same time improving global convergence properties. The proposed approach to flight clearance is shown to have significant potential for improving both the reliability and efficiency of the current industrial flight clearance process.
|Title of host publication||Nonlinear Analysis and Synthesis Techniques for Aircraft Control|
|Editors||Declan Bates, Martin Hagström|
|Place of Publication||London|
|Number of pages||360|
|Publication status||Published - 2007|
|Name||Lecture Notes in Control and Information Sciences|