Kamran Turkoglu
San Jose State University, USA
Posters & Accepted Abstracts: J Appl Mech Eng
When nature is observed, it is possible to see that birds are capable of taking advantage of wind currents not only to minimize their energy consumption, but also to maximize their endurance. One important aspect of this is, they do not hold any information and the ability to estimate the weather conditions on the path they y (and/or going to y through). All decisions are solely based on with respect to local and instantaneous wind conditions. This is a simple, yet, inspiring mechanism to learn and incorporate into flight dynamics through the mechanics of flight. Ideally, if the regional wind information is completely known in advance (with the help of a pre-determined (forecasted) weather/wind maps over the flight region), optimal flight/trajectory planning can be used to determine flight paths that minimize the total power consumption over a specified time interval, subject to various constraints. However, the main challenge for such a pre-determined map approach is that (due to the highly complex, stochastic, coupled and nonlinear nature of the atmosphere) weather forecasting related prediction errors also propagate into the optimization routine. Therefore, instead of making decisions based on pre-determined weather maps, with this methodology, we propose real-time guidance strategies that will make local, in-situ decisions using available on-board instruments to benefit from the existing local wind conditions and minimize power consumption during the flight.
Email: kamran.turkoglu@sjsu.edu