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161.
针对配置电推力器的GEO卫星位置保持问题,提出一种对倾角与偏心率进行联合控制的方法,建立了求解控制方程的优化模型,并针对优化模型变量多、约束复杂的问题进行降维处理,得到两种简化的求解方法,降低了求解复杂度与计算量,适合星上自主计算。采用联合控制方法,仅靠电推力器就能够同时实现卫星倾角和偏心率的高精度控制,有效降低卫星位置保持总的推进剂消耗。仿真算例表明,与电推力器只控倾角的传统方法相比,在保证偏心率控制精度不变的前提下,采用电推力器倾角与偏心率联合控制方法,15年寿命期内节省推进剂质量39kg。 相似文献
针对驱动飞机舵面的机电作动系统在轻载工况下电能浪费量大的问题,提出了多机电作动系统的驱动方案,为保证系统在最优的效率点附近工作,根据电动机效率和负载率之间的非线性关系,建立其功率调度的数学模型。改进了二进制和基本粒子群优化算法,并将2种算法互相嵌套,分别对机电作动系统组合方式和负荷分配进行交替迭代来求模型最优解,全局寻优能力强、收敛速度快;把投入工作的机电作动系统最小序号值引入适应度函数,解决了功率平衡约束,简化了运算;针对备用约束,建立系统启停优先顺序,提高了优化能力。仿真实验表明,改进的粒子群优化算法对飞机机电作动系统的功率调度有效,有助于飞机的能量优化。 相似文献
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介绍一种实现GPS中长基线实时动态(RTK)定位的方法,研究基于M-W组合搜索双频GPS载波相位模糊度的方法,最终使用消电离层LC载波相位组合观测量进行相对定位。车载试验结果表明,对于双频GPS接收机,流动站距离基准站50km以内,使用本方法RTK定位可以达到5cm(RMS)的点位精度。 相似文献
166.
通过对单舰各武器系统抗击反舰导弹的变换系数、对空防御综合因子、火力指数、通道因子等分析,建立各种组合抗击反舰导弹解析作战能力指数模型,结合"费效比"比较,得到选优方案;通过用蒙特卡洛法来对某型舰艇抗击两种型号的反舰导弹进行实例计算,得到各种抗击组合方案的作战能力指数和"费效比";经过仔细比较,提出了电子对抗系统、舰空导弹武器系统和近程防御武器系统的抗击组合是最优抗击组合方案的观点. 相似文献
167.
《中国航空学报》2020,33(3):1006-1015
When non-cooperative body attachment occurs in space, the inertia of the new combination and the change of the system’s momentum are unknown. This uncertainty may lead to the instability of the spacecraft’s attitude control. In order to solve this problem, we propose an adaptive control scheme based on the inertia estimation of the new, combined system of non-cooperative body and satellite. This method can allow the new combination of different situations to reach a stable state with a high level of precision and speed. In this paper, the stability of the adaptive control scheme is proven by constructing a Lyapunov function. A simulation environment in which a non-cooperative body attaches to a satellite attaches to is constructed. The simulation shows that the attitude error converges to a small field when using the control scheme, regardless of unfavorable cases, including unknown inertia parameters, added momentum. In addition, the simulation results show the strong robustness of the control scheme for the new combination. 相似文献
168.
Tamara Bandikova Jakob Flury 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2014
The new release of the sensor and instrument data (Level-1B release 02) of the Gravity Recovery and Climate Experiment (GRACE) had a substantial impact on the improvement of the overall accuracy of the gravity field models. This has implied that improvements on the sensor data level can still significantly contribute to arriving closer to the GRACE baseline accuracy. The recent analysis of the GRACE star camera data (SCA1B RL02) revealed their unexpectedly higher noise. As the star camera (SCA) data are essential for the processing of the K-band ranging data and the accelerometer data, thorough investigation of the data set was needed. We fully reexamined the SCA data processing from Level-1A to Level-1B with focus on the combination method of the data delivered by the two SCA heads. In the first step, we produced and compared our own combined attitude solution by applying two different combination methods on the SCA Level-1A data. The first method introduces the information about the anisotropic accuracy of the star camera measurement in terms of a weighing matrix. This method was applied in the official processing as well. The alternative method merges only the well determined SCA boresight directions. This method was implemented on the GRACE SCA data for the first time. Both methods were expected to provide optimal solution characteristic by the full accuracy about all three axes, which was confirmed. In the second step, we analyzed the differences between the official SCA1B RL02 data generated by the Jet Propulsion Laboratory (JPL) and our solution. SCA1B RL02 contains systematically higher noise of about a factor 3–4. The data analysis revealed that the reason is the incorrect implementation of algorithms in the JPL processing routines. After correct implementation of the combination method, significant improvement within the whole spectrum was achieved. Based on these results, the official reprocessing of the SCA data is suggested, as the SCA attitude data are one of the key observations needed for the gravity field recovery. 相似文献
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