An enhanced anti-disturbance attitude control law for flexible spacecrafts subject to multiple disturbances

As well-known disturbance rejection methods, active disturbance rejection control and disturbance observer-based control can effectively improve the control performances of complex systems in the presence of disturbances. However, the accurate rejection of multiple disturbances for control systems of practical engineering, for example, the attitude control system of flexible spacecraft, is still a bottleneck problem. In order to further improve the anti-disturbance capability and reduce the conservativeness, this paper proposes a novel enhanced anti-disturbance control law for the attitude control system of flexible spacecraft by combining active disturbance rejection control and disturbance observer-based control in a unified framework. More specifically, the disturbance from flexible vibration is described by an uncertain exogenous system based on the partially known information including elastic damping ratios and modal frequencies. The disturbance observer-based control is utilized to estimate and thereby reject this disturbance. On the other hand, the other disturbances such as external environmental disturbance and complex model nonlinearity are merged into a equivalent disturbance with bounded derivative, which is compensated by using the active disturbance rejection control law. Stability and robustness analysis are carried out for the disturbance observer and extended state observer. Finally, simulation results of low-earth-orbit flexible satellite are presented to verify the effectiveness of proposed methods.     

重力坝模型的尺寸效应

利用两个不同比尺预制缝重力坝模型的试验成果，以有限元富集技术进行非线性断裂分析，建立了极限承载力和长度比尺的确定性尺寸效应公式。混凝土重力坝的断裂尺寸效应满足指数衰减关系，用三次指数衰减公式可以准确地预测原型的极限承载力。断裂过程区的相对长度是引起模型试验尺寸效应的主要原因。数值计算结果表明，断裂过程区相对长度不仅是与材料有关的参数，能否充分发展还取决于结构尺寸和几何形状；断裂过程区相对长度的尺寸效应不同于统计尺寸效应和断裂参数尺寸效应，具有尺寸范围效应。断裂过程区相对长度在小试件、大试件和相对无穷大试件的发展程度不同。     

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.     

Characteristic Features of the Optimal Processing of the Results of Measurements in the Case of a Random Observation Function

An analysis is made of the characteristic features and problems of the optimal processing of the results of measurements in the case of a random observation function utilizing a nonlinear Kalman filter. A method is proposed for increasing the convergence domain of the filter with additional processing of measurements in the frequency domain.     

双频抽运提高SBS相位共轭保真度

相位共轭保真度是相位共轭镜技术用于强激光系统中的一个重要指标。采用四波混频加强SBS的方法 ,其相干拍频驱动声子场 ,能提高SBS相位共轭保真度。对于双频单池结构 ,使用列阵相机测量激光束能量远场角分布 ,在SBS转换效率最佳时 ,对相干驱动SBS相位共轭保真度进行了实验研究     

一种实现最佳用户检测的非线性优化神经网络

本文提出并讨论了实现码分多址（CDMA）系统上最佳多用户检测（MUD）的一种神经网络方法。该方法通过将最佳多用户检测视为非线性优化组合问题，利用神经网络能有效求解非线性优化问题的优势，导出了一种非线性优化神经网络来实现最佳多用户检测，理论分析和计算机模拟表明，所提出的神经网络具有可实时应用的动态性能和较传统方法优越得多的误码率性能和抗多址干扰的性能。     

一类非线性MIMO不确定系统的动态输出反馈镇定

考察其标称系统的相对阶大于{1,1,…,1}同时含匹配和非匹配不确定性的MIMO 非线性系统的动态输出反馈镇定问题.文中直接用Lyaunov方法构造一类输出反馈动态补 偿器,该补偿器可以实现对所论非线性不确定系统的动态输出反馈渐近镇定.     

精细功能陶瓷的若干发展趋势

概括了分析自９０年代初以来精细功能陶瓷的发展趋势，提出了一些相关的研究领域。     

有机极化聚合物材料及电光调制器件

有机极化聚合物材料是一类新型的功能高分子材料，在光电子及集成光学方面具有诱人的应用前景，其电光调制器件已接近实用化，本文综述了有机极化聚合物材料，极化聚合物体系及电光调制器件的研究进展，并指出它们存在的问题和发展方向。     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at