Tail-Sitter UAV Transition Trajectory Optimization Through a Multi-objective Evolutionary Algorithm

Vertical takeoff and landing (VTOL) tail-sitter unmanned aerial vehicles (UAVs) with advantages of multirotor UAVs and fixed-wing UAVs, facing the challenge of transition control, attracts much attention. The typical formulation to represent the transition optimization, which consists of a single-objective function and several constraints functions, is inflexible and rigid. This article designs a three-objectives function to minimize the change of height, the transition endurance and the cost of energy. A multi-objective evolutionary algorithm (MOEA) is applied for the transition optimization of a simplified three-degree-of-freedom dynamic model. The simulation results include the solutions by the typical formulation through an open-source software “OptimTraj” and the solutions by the proposed three-objective formulation through the MOEA. The latter performs better at the change of height with little more energy consumption, compared with the former.