多传感器分层多级变结构组合导航信息融合方法

基于惯性/卫星(全球卫星定位系统(GPS)/北斗双星)/多普勒/星光组合导航系统,提出了一种用于组合导航系统的多传感器分层多级变结构部分优化故障检测、隔离与系统重构(FDIR)的信息融合模型和算法。给出了模型的构成,并讨论了分层多级融合顺序与部分融合对全局估计的影响及其优化。理论分析和仿真试验结果表明,分层多级部分优化融合模型融合后的综合性能优于联邦滤波基本融合模型。     

Optimization design of satellite separation systems based on Multi-Island Genetic Algorithm

The separation systems are crucial for the launch of satellites. With respect to the existing design issues of satellite separation systems, an optimization design approach based on Multi-Island Genetic Algorithm is proposed, and a hierarchical optimization of system mass and separation angular velocity is designed. Multi-Island Genetic Algorithm is studied for the problem and the optimization parameters are discussed. Dynamic analysis of ADAMS used to validate the designs is integrated with iSIGHT. Then the optimization method is employed for a typical problem using the helical compression spring mechanism, and the corresponding objective functions are derived. It turns out that the mass of compression spring catapult is decreased by 30.7% after optimization and the angular velocity can be minimized considering spring stiffness errors. Moreover, ground tests and on-orbit flight indicate that the error of separation speed is controlled within 1% and the angular velocity is reduced by nearly 90%, which proves the design result and the optimization approach.     

Hierarchical Bayesian modeling of ionospheric TEC disturbances as non-stationary processes

We model regular and irregular variation of ionospheric total electron content as stationary and non-stationary processes, respectively. We apply the method developed to SCINDA GPS data set observed at Bahir Dar, Ethiopia $\left(11.6°\text{N,}37.4°\text{E}\right)$. We use hierarchical Bayesian inversion with Gaussian Markov random process priors, and we model the prior parameters in the hyperprior. We use Matérn priors via stochastic partial differential equations, and use scaled $\text{Inv}-{\chi }^2$ hyperpriors for the hyperparameters. For drawing posterior estimates, we use Markov Chain Monte Carlo methods: Gibbs sampling and Metropolis-within-Gibbs for parameter and hyperparameter estimations, respectively. This allows us to quantify model parameter estimation uncertainties as well. We demonstrate the applicability of the method proposed using a synthetic test case. Finally, we apply the method to real GPS data set, which we decompose to regular and irregular variation components. The result shows that the approach can be used as an accurate ionospheric disturbance characterization technique that quantifies the total electron content variability with corresponding error uncertainties.     

Hierarchical model updating strategy of complex assembled structures with uncorrelated dynamic modes

In structural simulation and design, an accurate computational model directly determines the effectiveness of performance evaluation. To establish a high-fidelity dynamic model of a complex assembled structure, a Hierarchical Model Updating Strategy(HMUS) is developed for Finite Element(FE) model updating with regard to uncorrelated modes. The principle of HMUS is first elaborated by integrating hierarchical modeling concept, model updating technology with proper uncorrelated mode treatment, and...     

利用姿态机动的绳系卫星编队系统轨道协同控制

为克服绳系卫星编队系统在轨道机动过程中的系绳摆动现象，提出一种通过调整领航星推力方向进而实现编队系统轨道跟踪的控制算法。由于推力方向角与状态量互相耦合且少于系统自由度个数，轨道协同控制属于典型的非仿射欠驱动控制问题。针对此问题，首先采用升阶法将角速度作为虚拟控制输入；然后为各子系统设计子滑模面后加权得到高层滑模面和等效控制输入律，并设计观测器估计系统非线性项；其次基于模型预测控制算法优化得到最高层滑模面的趋近控制律；最后采用MATLAB/Simulink验证了所提控制算法的有效性。