Multiobjective evolutionary-based optimization methods for trajectory planning of a quadrotor UAV

Abstract

This thesis describes the main research activity developed in a three years PhD program on flight dynamics. Optimization and UAVs flight control have been the main focus with methodological contributions on optimization, numerical and experimental work. Unmanned Aerial Vehicles (UAV) captured the attention of both research and industrial worlds as a replacement for expensive human-piloted vehicles. In the last decade, they became widely used for several applications in which humans could be unnecessary or in some cases too in danger. Many laboratories in the area of flight control, but also in the areas of robotics and control engineering in general, made significant research experiences on quadrotors. A collaboration between University of Naples Parthenope and the Second University of Naples is aimed at designing and using UAVs for educational and research purposes. More than one quadrotor was built, tested in flight and used as a platform for testing flight control and navigation systems. Several optimization problems may be encountered in the design of an UAV. During the design phase, they arise from the choice of the hardware, the design and layout of the structure, the aerodynamics. On the other hand, for the Guidance Navigation and Control system, the management of single or fleets of UAVs requires the solution of many non-linear optimization problems. For this reason a multi-objective general purpose optimization software has been developed, integrating evolutionary methods, as genetic algorithm and ant colony, with game theory paradigms, as Nash and Stackelberg equilibria. These methods have been primarily used to solve trajectory optimization problems with the scope of searching efficient flight trajectories in the presence of constraints. The thesis is developed around the flight control of a quadrotor UAV. The following are the main steps of the work described in this thesis: - dynamic and aerodynamic modelling oriented to flight control design; - development of a distributed general purpose optimization software implementing Game Theory based paradigms and Ant Colony algorithm hybridization; - Application of the above optimization methods to trajectory planning; - Numerical simulations and flight experiments. In Chapter 2, the quadrotor platform is described, together with the mathematical modelling and the design of the low level flight control system (attitude and speed control). In Chapter 3 the structure of the general purpose optimization software, mainly focused on the game theory layer and the ant colony algorithm is presented. In Chapter 4 the objectives of the optimization software are described and solved. Finally, in the Chapter 5, numerical simulations and flight tests are are shown.