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Limited flight range is a common problem for multicopters. To alleviate thisproblem, we propose a method for finding the optimal speed and heading of amulticopter when flying a given path to achieve the longest flight range. Basedon a novel multivariable extremum seeking controller with adaptive step size,the method (a) does not require any power consumption model of the vehicle, (b)can adapt to unknown disturbances, (c) can be executed online, and (d)converges faster than the standard extremum seeking controller with constantstep size. We conducted indoor experiments to validate the effectiveness ofthis method under different payloads and initial conditions, and showed that itis able to converge more than 30% faster than the standard extremum seekingcontroller. This method is especially useful for applications such as packagedelivery, where the size and weight of the payload differ for differentdeliveries and the power consumption of the vehicle is hard to model.

In-flight range optimization of multicopters using multivariable extremum seeking with adaptive step size