期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2017
卷号：14
期号：1
DOI：10.1177/1729881416687503
语种：English
出版社：SAGE Publications
摘要：For atmospheric entry vehicles, guidance design can be accomplished by solving an optimal issue using optimal control theories. However, traditional design methods generally focus on the nominal performance and do not include considerations of the robustness in the design process. This paper proposes a linear covariance-based model predictive control method for robust entry guidance design. Firstly, linear covariance analysis is employed to directly incorporate the robustness into the guidance design. The closed-loop covariance with the feedback updated control command is initially formulated to provide the expected errors of the nominal state variables in the presence of uncertainties. Then, the closed-loop covariance is innovatively used as a component of the cost function to guarantee the robustness to reduce its sensitivity to uncertainties. After that, the models predictive control is used to solve the optimal problem, and the control commands (bank angles) are calculated. Finally, a series of simulations for different missions have been completed to demonstrate the high performance in precision and the robustness with respect to initial perturbations as well as uncertainties in the entry process. The 3σ confidence region results in the presence of uncertainties which show that the robustness of the guidance has been improved, and the errors of the state variables are decreased by approximately 35%.
关键词：Entry guidance; linear covariance analysis; model predictive control; robustness
Loading...
