Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

随机库存分配问题的一种求解方法

讨论了在VMI管理思想下对具有随机需求特性的多客户库存分配问题 ,重点论述了有效近似算法的设计过程 ,最后基于一组模拟数据给出了一个算例。     

个性化公开密钥系统的设计

论文提出利用用户提供的个性化信息来随机产生关联大素数,保证了素数选取的随机化、个性化,提高了RSA算法的安全性。     

渤海绥中油田J3井疏水缔合聚合物驱数值模拟研究

为了进一步提高渤海油田J3井区缔合聚合物驱的技术经济效果,在渤海油田室内配方和先导性矿场试验研究基础上,利用化学驱油藏数值模拟软件FAPMS,分析和研究了高浓度缔合聚合物前置段塞、主段塞的大小和浓度以及段塞组合方式对驱油效果的影响,优化设计了渤海绥中油田J3井区块矿场试验的最佳注入程序及段塞大小。结果表明,通过对不同浓度的疏水缔合聚合物注入的前置段塞及主段塞和梯度式后续段塞的优化后,原油采收率比未优化时提高了约10个百分点。研究表明,渤海油田应该高度重视聚合物驱的注入方式和段塞优化设计,进一步提高聚合物的技术经济效果。     

Parameter Uncertainty and Policy Intensity: Some Extensions and Suggestions for Further Work

The effects of parameter uncertainty on optimal policy have been a matter of interest for academics, and even for some policymakers, for a long time. Two lines of literature have developed analytical results on this matter. The first line uses static models and the second dynamic models. In this dynamic line most of the results are confined to models with a single state and a single control variable. In this paper we want to encourage the analysis of more general dynamic cases. To do so, the results in the dynamic line are extended from one-state and one-control finite horizon models to models with a pair of control variables. We then discuss some of the hurdles which must be surmounted for the results to be made more general and suggests some lines for further research. JEL classification: C61; E61     

An original approximate method for estimating the invariant probability distribution of a large class of multi-dimensional nonlinear stochastic oscillators

This paper proposes an original method for obtaining analytical approximations of the invariant probability density function of multi-dimensional Hamiltonian dissipative dynamic systems under Gaussian white noise excitations, with linear non-conservative parts and nonlinear conservative parts. The method is based on an exact result and a heuristic argument. Its pertinence is attested by numerical tests.     

基于主体外部轮廓的照片分割算法

在实际应用中常常需要将人像从照片的背景中有效地分割出来，通常的做法是通过提取照片中人像各部分特征来实现分割，其缺陷是计算复杂度较大，分割效果受各种干扰因素影响很大。现提出了一种基于主体外部轮廓信息的照片分割算法，通过梯度锐化、边缘保护、临近像素点相似度比较来确定图像的边界，该算法对于具有相对均匀背景的照片具有较高的计算效率。     

A robust adaptive pole‐placement controller without strictly positive real condition

This paper considers the adaptive pole‐placement control problem for system (1) with unmodelled dynamics η_n dominated by a small constant ε multiplied by a quantity independent of ε but tending to infinity as the past input, output, and noise grow. Using bounded external excitation and randomly varying truncation techniques, we give a design method of adaptive pole‐placement controller. It is shown that the closed‐loop system is globally stable, the estimation error for the parameter contained in the modelled part is of order ε, and the closed‐loop system under the adaptive pole‐placement control law is suboptimal in the sense of $$\mathop{\lim\sup}\limits_{{n\to\infty }}{1\over n}\mathop{\sum}\limits_{i=0}^n{\left({A^{*}(z)y_{n}‐L(z)C(z)w_{n}‐B(z)R(z)y_{n}^{*}}\right)^{2}{\leq}O({\varepsilon}^{2})+\gamma^{2}\mathop{\sum}\limits_{j=1}^q{b_{j}^{2}}}$$\nopagenumbers\end while the SPR condition used usually in other papers is replaced by a stability condition. Copyright © 2001 John Wiley & Sons, Ltd.     

Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.