The importance of determining the sidereal rotation period of an astronomical object on future investigations pertaining to said object has been well documented in the literature. Researchers, however, have differed i...
详细信息
The importance of determining the sidereal rotation period of an astronomical object on future investigations pertaining to said object has been well documented in the literature. Researchers, however, have differed in their techniques used to estimate and model objects in the space catalog. In this paper, several period-estimation methods will be explored ranging across Fourier and phase-folding techniques. These methods will be tested using ground-based observations of light curve data for various resident space objects that fall under a rigid body context (i.e., asteroids, satellites, probes, rocket bodies) and celestial objects like stars and extrasolar planets. The effect of varying sample size, the inadequacies in unevenly sampled data processing, autonomy of the method, and complexity of parameters are investigated. For the models of artificial space objects that are not open source, a simulation is used to generate synthetic light curves with which all of the above-mentioned techniques are also employed. To account for heterogeneity in method parameters, each technique is tested with a range of values to optimize the rotational period. Results for uniformly sampled asteroid data as well as nonuniformly sampled stellar objects and generic sinusoidal data show variances in accuracy of the methods, but certain methods stand out.
An adaptive controller is developed for a regolith excavation robot to determine the mass of excavated material and to account for the effects of gravity and friction while on the surface of other celestial bodies. A ...
详细信息
ISBN:
(数字)9781624106095
ISBN:
(纸本)9781624106095
An adaptive controller is developed for a regolith excavation robot to determine the mass of excavated material and to account for the effects of gravity and friction while on the surface of other celestial bodies. A data-based integral concurrent learning (ICL) parameter update law accounts for and estimates the unknown mass, gravity, and friction parameters. A Lyapunov-based analysis proves that the trajectory tracking error and the parameter estimate errors exponentially converge to zero. An estimation of the mass of regolith excavated by the robot is calculated from the estimated parameters. A simulation study is performed to show the performance of the developed technique. Simulation results show that for 3 kilograms of excavated material, the mass estimate has an error of 4.9 grams.
暂无评论