Analysis of predictive entry guidance for a Mars lander under high model uncertainties |
| |
| Authors: | Alexander I Kozynchenko |
| |
| Institution: | 1. Department of Electrical Engineering, College of Engineering Trivandrum, Kerala, India;2. Electrical and Electronics Engineering Department, Mohandas College of Engineering and Technology Thiruvananthapuram, Kerala, India;3. Department of Electrical Engineering, Indian Institute of Technology Kharagpur, West Bengal, India;1. School of Automation, Beijing Institute of Technology, Beijing 100081, PR China;2. State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, Beijing 100081, PR China;1. School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan, China;2. Collaborative Innovation Center for Geospatial Technology, 129 Luoyu Road, Wuhan, China;1. Beijing Institute of Control Engineering, Beijing 100190, China;2. Science and Technology on Space Intelligent Control Laboratory, Beijing 100190, China;1. Department of Physics, The Pennsylvania State University Lehigh Valley, Center Valley, PA, USA;2. Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA |
| |
| Abstract: | The problem of precision landing on Mars is now considered to be an essential challenge in the planned Mars missions. The paper focused on the guided atmospheric entry as a predominant phase in achieving a desired target state, as compared with the following parachute and powered descent. The predictive algorithms for the longitudinal guidance of a low-lift entry vehicle are treated. The purpose is to investigate applicability of the predictive strategy under possible high discrepancies between the on-board dynamic model and real environment while in entry trajectory. The comparative performance analysis based on computer simulation has been made between the standard one-parametric “shooting” predictive algorithm and a more complex two-parametric algorithm providing lower final velocity and, thus, expanding the interval of admissible downrange. However, both algorithms display considerable degradation of downrange accuracy in the cases when the actual drag force is larger than the modelled one. An acceptable solution has been found by including to both predictive guidance schemes an identification algorithm that repeatedly adapts the on-board model to varied environment in real time scale. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
