改进的遗传算法对电液伺服系统PID调节器参数优化方法的研究

遗传算法是一种模拟自然界进化而形成的简单、高效的全局优化算法。本文研究了用改进的遗传算法对某机器人电液位置伺服系统的优化，着重将这种改进后的算法用于PID调节器的参数优化，编制了进化程序，并进行了仿真试验。结果表明用该方法可以有效地解决该电液位置伺服系统PID调节器参数的优化问题。     

低温烧结Zn(Nb0.9V0.1)2O6微波介质陶瓷的结构与性能

对低温烧结Zn(Nb0.9V0.1)2O6微波介质陶瓷进行了研究,讨论了V离子取代Nb离子进入铌酸锌晶格后对材料结构与微波性能的影响以及V5+取代后材料结构与性能之间的关系.实验结果表明少量V5+取代Nb5+后材料的烧结温度可从未取代时的1150℃显著降至取代后的950℃;V离子进入铌酸锌晶格,材料晶体结构仍为铌铁矿结构;低温烧结后ZnNb0.9(V0.1)2O6微波介质材料具有圆柱状微结构和部分玻璃相物质;Zn(Nb0.9V0.1)2O6微波介质材料950℃烧结后具有最佳微波介电性能(介电常数为25,Q×f值为29 500GHz,谐振频率温度系数为-44×10-6/℃).     

超声行波马达环形定子的振动模式

利用傅立叶变换对由环形压电陶瓷片激励的超声行波马达环形定子的振动模式作了分析,说明了在保持为某一振动模式设计的压电陶瓷片塗银电极图形不变的情形下,改变激励电源的频率到某些值时,也能激发起其它一些的振动模式.并实验验证了部分结果.     

不锈钢焊管抛磨新设备

PG圆管和PF方管系列抛光机的抛光质量及效率能满足生产需要。介绍了这种不锈钢圆管及方管抛光机的工作原理。着重分析了抛磨轮的选用。     

全极化SAR影像城区建筑密度分析

针对全极化SAR影像的建筑区特性,提出了一种基于极化特征共生矩阵的城区建筑密度分析方法。首先将极化特征与共生矩阵结合,在考虑建筑区极化散射机理和建筑朝向作用的同时,兼顾了建筑区的空间排列信息,在此基础上为了增强建筑密度的局部区域特性,将共生矩阵特征进行K-means聚类,结合图像分块形成标号直方图统计矢量,进而对该直方图统计矢量进行矢量量化实现SAR影像城区的建筑密度分级。RadarSat-2全极化SAR影像城区建筑密度分析的实验表明,该方法既适用于建筑朝向复杂城区也适用于建筑排列整齐城区的密度信息提取。     

语言竞争社会仿真模型与计算实验

语言竞争传播演化现象是典型的不能假设、无法进行"真实性实验"的社会科学问题,而建立在社会仿真模型基础上的计算实验是可行的方案。利用基于Agent的社会圈子网络理论并引入语言的内部词汇结构给出一种新的动态微观语言竞争社会仿真模型,其能反映语言内部结构演化涌现宏观语言态势的机制。计算实验表明:无干预调控情况下,语言共存的参数空间范围很小,很难达到共存状态,但在合适的时间窗口实施动态的调控政策可以让语言共存的参数空间显著扩大,在社会开放度高的情况下政策调控效果更好,这一发现扩展了之前人们对复杂网络语言竞争模型的认识。     

Ergonomic Analysis of Mobile Cart–Assisted Stocking Activities Using Electromyography

Workers in grocery stores are exposed to numerous musculoskeletal risks that can be reduced using assistive devices while performing stocking tasks. A regional grocery store has recently deployed a mobile cart without comprehension of its ergonomic impact on workers, which this article investigates using normalized electromyography data (%MVC). This article studies not only ergonomic impact based on %MVC values but also work performance represented by a muscle force metric (MFM). The results from this study showed highest muscle groups in %MVC and MFM were the erector spinae and triceps. Interestingly, muscle activations on erector spinae were reduced when mobile cart is used. %MVC and MFM distribution for value‐added‐ and non‐value‐added subtasks were slightly different, with larger differences observed for non‐value‐added tasks. Video recordings revealed higher work performance when the mobile cart is used. In future research, the number of participants will be increased to further validate the results from this study.     

Novel neural network modeling method and applications

Neural networks play an important role for designing the parametric model of electromagnetic structures. The current neural network methods are unfit for a circuit model with many input variables because it is costly to extract a large number of the training data and test data to complete the highly nonlinear mapping approximation. This article proposes a new neural network modeling method—the multidimensional neural network model, which can be used to solve the issue of multivariable radiofrequency and microwave passive device modeling. The entire multidimensional neural network modeling problem is simplified into a set of neural network submodels through decomposition method. Then the submodels are combined into an equivalent model, and the final entire model is produced through the neural‐network mapping model developed with the submodels and equivalent model. A microstrip hairpin filter model is developed using the proposed method. The simulation results show the correctness and the effectivity of the proposed method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:769–779, 2015.     

Parametric Stabilization of Quantized Interconnected Systems with Application to Coupled Inverted Pendulums

This paper studies the analysis of parametric stability and decentralized state feedback control of a kind of quantized interconnected systems. The output of each controller is quantized logarithmically before it is input to the subsystem, and the quantized density would affect the stability of the systems. First, a decentralized state feedback controller is designed for interconnected systems without quantization and the corresponding stable region is obtained. Second, for a given controller, the lower bound of the quantization density is evaluated from parameters of local controllers. Finally, the proposed method is applied to coupled inverted pendulums systems which can be viewed as quantized interconnected systems. The simulation results show that by using the proposed quantized controllers, the interconnected inverted pendulum systems are parametrically stabilized.     

Research on social relations cognitive model of mobile nodes in Internet of Things

Interaction and communication between humans with smart mobile devices are a new trend of development in Internet of Things (IoT). With the powerful sensing capability of smart device and human mobility, various services could be provided by building a trusted chain between service requesters and suppliers. The cognition of social relations between mobile nodes is the basis of final mobile-aware services. It involves many decision factors, such as time, space and activity patterns. Using social network theory, a new cognitive model for social relations of mobile nodes in IoT is proposed. Firstly, nodes' social relations are reasoned and quantified from multiple perspectives based on the summary of social characteristics of mobile nodes and the definition of different decision factors. Then the location factor, interconnection factor, service evaluation factor and feedback aggregation factor are defined to solve the shortcomings in existing quantitative models. Finally, the weight distribution is set up by information entropy and rough set theory for these decision factors; it can overcome the shortage of traditional methods, in which the weight is set up by subjective ways and hence their dynamic adaptability is poor. We compare our cognitive model to existing models using MIT dataset by defining a variety of test indicators, such as network overall density (NOD), the degree center potential (DCP), the network distribution index (EI), etc. Simulation results show that, the cognitive model has better internal structure and significant validity in network analysis, and thus can provide mobile-aware service effectively in dynamic environment.