This dissertation addresses the future trend in high aspect-ratio wing designs, which are strongly synergetic with the structural weight savings that can be gained from Gust Load Alleviation systems. Therefore, this research explores modelling capabilities for the design and performance testing of such active control systems in flexible vehicles with geometric nonlinearities and rigid/elastic couplings. The nonlinear aeroelastic simulation toolbox SHARPy is utilized to capture these effects.

Enhancements made to SHARPy's nonlinear aeroelastic solver are verified and exercised on a very flexible wind tunnel wing and a representative flexible aircraft configuration. This includes a fuselage model, sectional force corrections, and a wake convection scheme. The gust response prediction capabilities have been compared with experimental data of the very flexible wing, resulting in a good match for steady and dynamic structural deformations. Possible limitations of computational gust models, used in large aircraft certification, are explored for large structural deformations with a gust vane model. Additionally, geometrical nonlinearities are assessed and become apparent for this wing because of the nonlinear aeroelastic equilibrium but not the gust excitation itself.

A framework is proposed in which, first, linear and reduced-order models are obtained for a representative aircraft configuration to design a linear quadratic Gaussian controller. Second, the performance of this controller is assessed with SHARPy's nonlinear aeroelastic solver, as linear methods may overlook important complex dynamics introduced by large deformation. The designed controller succeeded in its gust alleviation and stabilization objective. Cost-effective control surface and sensor layouts were identified. A degradation of the control performance due to less aggressive control action was identified with the nonlinear full-order model in closed-loop. This degradation could not be linked to structural nonlinearities but likely to a mismatch between the linear and nonlinear models. The findings in this dissertation underscore the challenges of modelling complex physics for control.