Flapping wing aerial vehicles rely heavily on accurate models for a variety of different tasks. There have been significant efforts in creating both analytical and data-driven models for many of these types of vehicles including ornithopters and small aerial vehicles mimicking insects. However, very few works have explored modeling for aerial vehicles with a skeletal structure throughout the wings and a single flexible membrane that covers the wings and tail such as is found in robots with bat morphology. In this paper, we build upon previous efforts to model a bat robot using a combination of first-principles and data-driven tools. We record a series of load cell tests and free-flight experiments, and we optimize the model parameters to improve long-term flight prediction. We introduce several extra terms in the model including a term explaining the coupling between wings and tail in order to maximize the effectiveness of collected flight data. The result is a model that performs well in prediction for a range of different tail actuator configurations as demonstrated by our flight results using a bat robot.
