Wing Optimization for High Endurance Applications Using Teaching Learning Based Optimization

The advancement in the field of aerospace has increased manifold over the past 4 decades with UAV design optimization being no exception. UAV Design and Optimization is a game of compromise. We cannot obtain a design which is best in each and every aspect. Over the years people have been using natured inspired algorithms to solve design optimization problems. This paper presents the application of a new advanced algorithm – Teaching Learning Based Optimization for optimizing wing of an Unmanned Aerial Vehicle for High Endurance applications. The results of this single objective problem are obtained taking four parameters i.e. aspect ratio, taper ratio, maximum thickness to chord ratio and maximum lift coefficient as design variables and an attempt has been made to understand the efficiency and robustness of TLBO over GA – the most widely used aircraft design optimizer.