The dynamic response characteristics of modern unmanned aerial vehicles (UAVs)\ud are highly nonlinear and vary substantially with flight conditions due to their reduced\ud dimensions compared to normal aircraft. In this thesis, design frameworks that are\ud based on parameter dependent Lyapunov functions (PDLFs) are developed for UAV\ud flight control systems. These design frameworks or procedures can systematically\ud deal with aircraft systems with nonlinear and parameter dependent dynamics, and\ud uncertainty in the mathematical models. To this end, we analyse robust stability\ud and performance of LPV systems and present two LPV controller design methods\ud using the PDLF approach: Two-Degree-of-Freedom (2DoF) and loop shaping with\ud coprime factorisation. We formulate and solve the control problem for an LPV plant\ud with measurable parameters and an output feedback structure. The solvability conditions\ud are reduced to LMIs and can be solved approximately using finite-dimensional\ud convex programming. A parameter dependent performance approach is used in a\ud 2DoF/PDLF design and constitutes a flexible generalisation for calibrations of local\ud performance. In loop shaping/PDLF design, a left coprime factorisation is derived by\ud H2 filtering, and then a loop shaping design is implemented in the PDLF framework.\ud We also incorporate pole placement constraints into the LMI synthesis to improve controller\ud performance. To be able to use the robust gain-scheduling synthesis results,\ud an LPV model of the UAV is developed and validated. The gain scheduling controller\ud design of longitudinal/lateral-directional dynamics of the UAV is illustrated in the\ud design example. It is shown that a flight control system can be built with satisfactory\ud robust stability and performance
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