Evolution of neural networks for active control of tethered airfoils

Abstract

Recent development in tethered airfoil i.e. kite technology allows the possibility of exploitation of wind energy at higher altitudes than achievable with traditional wind turbines, with greater efficiency and reduced costs. This study describes the use of evolutionary robotics techniques to build neurocontrollers that maximize energy recoverable from wind by kite control systems in simulation. From initially randomized starting conditions, neurocontrollers rap-idly develop under evolutionary pressure to fly the kite in figure eight trajecto-ries that have previously been shown to be an optimal path for power genera-tion. Advantages of this approach are discussed and data is presented which demonstrates the robustness of trajectory control to environmental perturbation. © Springer-Verlag Berlin Heidelberg 2007.