On-line Trajectory Optimization in Parameter Space for Automatic Pumping Cycle of Airborne Wind Energy System

This paper proposes a practical optimization algorithm for trajectory optimization in airborne wind energy system (AWES). Existing approaches generally implement optimal control approaches to handle model non-linearity and constraints. However, due to dynamic constraints in the optimal control problem, strongly non-convex objective function and numerous decision variables increase the complexity and computational burden of the optimization algorithm. To address this issue, an optimization algorithm with minimized decision variables is proposed based on a high-fidelity AWES model that incorporates a closed-loop flight control system. Utilizing the convex nature of the objective function, the Karush-Kuhn-Tucker (KKT) conditions are applied to derive optimality conditions. The decision variables are updated by a conjugate-descent algorithm with numerically approximated gradient. Computer simulations confirm the superiority of proposed algorithm in terms of computational efficiency and accuracy of the solution.