Online predictive control based trajectory optimization of tethered foils for wind energy generator

Capturing the stable wind energy in the high altitude is a novel green generation approach. Rational trajectory optimization can obtain the maximal power difference between the traction phase and the recovery phase. Receding horizon model predictive control in the offline manner was previously employed to handle this type of problem, however it is time-consuming and lacks of adaptability and flexibility to varying aerodynamic parameters. This paper presents a receding horizon optimization method for the tethered foil generator based on an online searching strategy. The nonlinear optimization problem can be approximately reformulated to a univariate receding horizon sub-optimal issue in a short interval in four phases with different objectives. By using uniform sampling and chaotic search approaches, the sub-optimal solution, subject to the physical constraints, is obtained online. The simulation results demonstrate its effectiveness. This algorithm has the potential to be realized in a parallel pattern.