  Fluidic locomotion of flapping Micro Aerial Vehicles (MAVs) can be very
complex, particularly when the rules from insect flight dynamics (fast flapping
dynamics and light wings) are not applicable. In these situations, widely used
averaging techniques can fail quickly. The primary motivation is to find
efficient models for complex forms of aerial locomotion where wings constitute
a large part of body mass (i.e., dominant inertial effects) and deform in
multiple directions (i.e., morphing wing).
  In these systems, high degrees of freedom yields complex inertial, Coriolis,
and gravity terms. We use Algorithmic Differentiation (AD) and Bayesian filters
computed with cubature rules conjointly to quickly estimate complex
fluid-structure interactions. In general, Bayesian filters involve finding
complex numerical integration (e.g., find posterior integrals). Using cubature
rules to compute Gaussian-weighted integrals and AD, we show that the complex
multi-degrees-of-freedom dynamics of morphing MAVs can be computed very
efficiently and accurately. Therefore, our work facilitates closed-loop
feedback control of these morphing MAVs.
