中国空间科学技术2017，Vol.37Issue(1)：1-10,10.DOI:10.16708/j.cnki.1000-758X.2017.0002
基于自适应迭代学习的小行星绕飞容错控制
Adaptive iterative learning based fault tolerant control for asteroid orbiting
摘要
Abstract
Considering the probe actuator failures, parametric uncertainties and external disturbances,an adaptive iterative learning based fault tolerant control method was designed for asteroid orbiting. The controller was divided into two parts:robust iterative learning component and neural network iterative learning component.For the robust iterative learning component,a sliding-mode-like strategy with adaptive iterative learning law was applied to maintain the stability and improve the attitude tracking accuracy in case of actuator failures. For the neural network iterative learning component,a radial basis function (RBF) neural network based adaptive approximation was introduced to estimate the system uncertainty, with parameters adapted online to maintain dynamic performance. In addition, numerical simulations show that the method achieved the error in the order of 10-2 magnitude under the actuator failure conditions, highlights the robust and high precision attitude tracking performance.关键词
小行星探测器/容错控制/自适应迭代学习/神经网络/执行器故障Key words
asteroid probe/fault tolerant control/adaptive iterative learning/neural network/actuator failures分类
航空航天引用本文复制引用
黄怡欣,李爽,江秀强..基于自适应迭代学习的小行星绕飞容错控制[J].中国空间科学技术,2017,37(1):1-10,10.基金项目
国家自然科学基金(61273051,11672126) （61273051,11672126）
上海航天科技创新基金(SAST2015036) （SAST2015036）
中国科学院太空应用重点实验室开放基金(LSU-2016-04-01,LSU-2016-07-01) （LSU-2016-04-01,LSU-2016-07-01）
江苏省普通高校研究生科研创新计划(SJLX15_0136) （SJLX15_0136）
