摘要：讨论了一类严格反馈型不确定非线性系统的输出反馈跟踪问题 .所讨论的不确定性不满足线性增长条件 .先设计高增益观察器估计输出偏差的微分 ,并将由此获得的信号的符号用于变结构观察器 ,随后用backstepping过程设计输出反馈控制器 .得到的控制器可以保证闭环系统的所有信号都是有界的 ,且跟踪误差可以任意地小 .

摘要：基于神经网络所具有的定性推理和定量数值并行计算能力 ,以及学习记忆能力 ,集成非线性系统的多个特征模型和控制器 ,实现了控制系统的多模态智能控制 .该方法充分结合系统的定性知识和定量数学描述信息 ,实现了参数大范围变化时变系统的良好控制 .最后用该方法对某型激光制导炸弹设计了一多模态控制器 ,仿真结果表明了该方法的优良性能 .

摘要：The identification of design pattern instances is important for program understanding and software maintenance. Aiming at the mining of design patterns in existing systems, this paper proposes a subgraph isomorphism approach to discover several design patterns in a legacy system at a time. The attributed relational graph is used to describe design patterns and legacy systems. The sub-graph isomorphism approach consists of decomposition and composition process. During the decomposition process, graphs corresponding to the design patterns are decomposed into sub-graphs, some of which are graphs corresponding to the elemental design patterns. The composition process tries to get sub-graph isomorphism of the matched graph if sub-graph isomorphism of each subgraph is obtained. Due to the common structures between design patterns, the proposed approach can reduce the matching times of entities and relations. Compared with the existing methods, the proposed algorithm is not linearly dependent on the number of design pattern graphs. Key words design pattern mining - attributed relational graph - subgraph isomorphism CLC number TP 311.5 Foundation item: Supported by the National Natural Science Foundation of China (60273075) and the Science Foundation of Naval University of Engineering (HGDJJ03019)Biography: LI Qing-hua (1940-), male, Professor, research direction: parallel computing.

摘要：建立1种本构模型,用于研究形状记忆合金(SMA)结构和复合材料的力学响应。首先,该本构模型在单轴应力状态和多轴应力状态下得到考核;其次,给出了移植到ABAQUS的用户子程序umat的求解格式。利用有限元方法分析了SMA的CT(紧凑拉伸)和TPB(三点弯曲)试样以及SMA—纤维增强复合材料和常规金属合金增强SMA基复合材料的力学响应。在CT和TPB裂纹前端,有不同的相变规律,SMA复合材料的相变取决于应力状态和两相材料的材料性质等。

摘要：给出一种新的感应电动机转子磁链自适应观测器的设计方案 ,以克服电动机参数发生变化时矢量控制系统性能的下降 .这种设计方案不依赖于感应电动机的定转子参数 ,算法的稳定性和收敛性由正实误差传递函数条件下的参数调整算法保证 ,数字仿真结果说明了它的有效性 .

摘要：研究含时变滞后的不确定系统的控制综合问题 .基于Lyapunov方法提出了一种含滞后补偿的鲁棒控制设计方法 .闭环稳定性条件由一组线性矩阵不等式表示 .在这些条件中给出了稳定性和滞后以及其导数之间的关系 .实例显示 ,利用提供的方法所给出的结果比以往文献给出的结果保守性小 .

摘要：Current design method for circular sliding slopes is not so reasonable that it often results in slope (sliding.) As a result, artificial neural network (ANN) is used to establish an artificial neural network based inverse design method for circular sliding slopes. A sample set containing 21 successful circular sliding slopes excavated in the past is used to train the network. A test sample of 3 successful circular sliding slopes excavated in the past is used to test the trained network. The test results show that the ANN based inverse design method is valid and can be applied to the design of circular sliding slopes.

摘要：示教学习是机器人运动技能获取的一种高效手段.当采用摄像机作为示教轨迹记录部件时,示教学习涉及如何通过反复尝试获得未知机器人摄像机模型问题.本文力图针对非线性系统重复作业中的可重复不确定性学习,提出一个迭代学习神经网络控制方案,该控制器将保证系统最大跟踪误差维持在神经网络有效近似域内.为此提出了一个适合于重复作业应用的分布式神经网络结构.该神经网络由沿期望轨线分布的一系列局部神经网络构成,每一局部神经网络对对应期望轨迹点邻域进行近似并通过重复作业完成网络训练.由于所设计的局部神经网络相互独立,因此一个全程轨迹可以通过分段训练完成,由起始段到结束段,逐段实现期望轨迹的准确跟踪.该方法在具有未知机器人摄像机模型的轨迹示教模仿中得到验证,显示了它是一种高效的训练方法,同时具有一致的误差限界能力.

摘要：This paper first gives the general solution of two-dimensional orthotropic media expressed with two harmonic displacement functions by using the governing equations. Then, based on the general solution in the case of distinct eigenvalues, a series of beam problems, including the problem of cantilever beam under uniform loads, cantilever beam with axial load and bending moment at the free end, cantilever beam under the first, second, third and fourth power ofx tangential loads, is solved by the superposition principle and the trial-and-error methods.

摘要：提出一种基于AVSC(近似变结构控制 )及FLCN(模糊局部控制器网络 )的鲁棒增益调度控制设计方法 .利用AVSC ,对于一般的工作点选择合适的滑动模及其趋近率 ,得到局部鲁棒AVSC控制律 ,使局部系统尽快进入滑动模 ,并具有期望的性能 ,同时能够克服一般VSC(变结构控制 )的控制信号抖动现象 .当然 ,任意一个局部控制器一般只能保证在其相应工作点附近的工作性能 .为此 ,引入了模糊控制技术的隶属函数 ,将它当作增益调度控制器的有效度函数 ,得到FLCN .仿真研究验证了所提出控制器设计方法的有效性 .