The first and most imperative step when designing a biologically inspired robot is to identify the underlying mechanics of the system or animal of interest. It is most common, perhaps, that this process generates a set of coupled nonlinear ordinary or partial differential equations. For this class of systems, the models derived from morphology of the skeleton are usually very high dimensional, nonlinear, and complex. This is particularly true if joint and link flexibility are included in the model. In addition to complexities that arise from morphology of the animal, some of the external forces that influence the dynamics of animal motion are very hard to model. A very well-established example of these forces is the unsteady aerodynamic forces applied to the wings and the body of insects, birds, and bats. These forces result from the interaction of the flapping motion of the wing and the surround- ing air. These forces generate lift and drag during flapping flight regime. As a result, they play a significant role in the description of the physics that underlies such systems. In this research we focus on dynamic and kinematic models that govern the motion of ground based robots that emulate flapping flight. The restriction to ground based biologically inspired robotic systems is predicated on two observations. First, it has become increasingly popular to design and fabricate bio-inspired robots for wind tunnel studies. Second, by restricting the robotic systems to be anchored in an inertial frame, the robotic equations of motion are well understood, and we can focus attention on flapping wing aerodynamics for such nonlinear systems. We study nonlinear modeling, identification, and control problems that feature the above complexities. This document summarizes research progress and plans that focuses on two key aspects of modeling, identification, and control of nonlinear dynamics associated with flapping flight. / Ph. D.

We employ the empirical potential function Airebo to computationally model free-standing Carbon-12 graphene in a classical setting. Our objective is to measure the mean square displacement (MSD) of atoms in the system for different average temperatures and Carbon-13 isotope concentrations. From results of the MSD we aim to develop a technique that employs Transmission Electron Microscopy (TEM), using high-angle annular dark filed (HAADF) detection, to obtain atomic-resolution images. From the thermally diffusive images, produced by the vibrations of atoms, we intent to resolve isotopes types in graphene. For this, we establish a relationship between the full width half maximum (FWHM) of real-space intensity images and MSD for temperature and isotope concentration changes. For the case of changes in the temperature of the system, simulation results show a linear relationship between the MSD as a function of increased temperature in the system, with a slope of 7.858×10-6 Å2/K. We also note a power dependency for the MSD in units of [Å2] with respect to the FWHM in units of [Å] given by FWHM(MSD)=0.20MSD0.53+0.67. For the case of increasing isotope concentration, no statistically significant changes to the MSD of 12C and 13C are noted for graphene systems with 2,000 atoms or more. We note that for the experimental replication of results, noticeable differences in the MSD for systems with approximately 320,000 atoms must be observable. For this, we conclude that isotopes in free-standing graphene cannot be distinguished using TEM.