Dynamics and genetic fuzzy neural network vibration control design of a smart flexible four-bar linkage mechanism

In this paper, a dynamic modeling method and an active vibration control scheme for a smart flexible four-bar linkage mechanism featuring piezoelectric actuators and strain gauge sensors are presented. The dynamics of this smart mechanism is described by the Discrete Time Transfer Matrix Method of Multibody System (MS-DTTMM). Then a nonlinear fuzzy neural network control is employed to suppress the vibration of this smart mechanism. For improving the dynamic performance of the fuzzy neural network, a genetic algorithm based on the MS-DTTMM is designed offline to tune the initial parameters of the fuzzy neural network. The MS-DTTMM avoids the global dynamics equations of the system, which results in the matrices involved are always very small, so the computational efficiency of the dynamic analysis and control system optimization can be greatly improved. Formulations of the method as well as a numerical simulation are given to demonstrate the proposed dynamic method and control scheme.     

Optimal Performance in Tracking Stochastic Signal Under Disturbance Rejection

The analysis method of optimal tracking performance is proposed for multiple‐input multiple‐output (MIMO) linear time‐invariant (LTI) systems under disturbance rejection. An H₂ criterion of the error signal between the output of the plant and the reference signal is used as a measure for the tracking performance. Spectral factorization is applied to obtain the optimal solution of the system tracking error. The explicit expressions are derived for this minimal tracking error with respect to random reference signals under disturbance rejection. It is shown that the nonminimum phase zeros, the zero direction, the unstable poles, the pole direction of a given plant, statistical characteristics of the reference input signal, and disturbance signal have a negative effect on a feedback system's ability to reduce the system error with disturbance rejection. The results show that the optimal tracking performance will further be damaged because of disturbance rejection. Some typical examples are given to illustrate the theoretical results.     

变风量空调系统优化控制策略研究

变风量空调系统是多变量,大滞后、非线性和不确定性的系统,普通的模糊神经网络控制已难以满足其多变量动态控制的要求,为改善变风量空调系统控制性能,本文提出了一种小波模糊神经网络预测控制方法,实现变风量空调的温湿度有效控制.通过小波神经网络预测器在线建立被控对象的数学模型,并用模糊RBF神经网络控制器对所得到的信息在线修正,优化控制器参数,从而改善系统的控制效果.仿真结果表明,小波模糊神经网络预测控制具有很强的鲁棒性和自适应能力,控制精度高,控制效果好,安全可靠等优点,具有广泛的应用价值.     

基于内容的静态语义概念视频检索方法研究

本文针对互联网视频检索技术的发展,阐述了目前主流视频搜索引擎的技术现状,分析了互联网视频检索的关键技术,特别是对于视频特征的提取技术。本文的创新点是提出了一种通用的基于内容的静态语义视频检索方法,该方法可以弥补基于文本视频检索的有关不足,并且在TRECVID的视频概念检索数据的静态语义概念中得到验证,运行稳定。     

基于改进神经网络的湖泊水质污染检测法研究

研究采用图像对湖泊水质污染检测的问题,由于水面较大,像素信息量多,造成检测时间长,速度慢。针对图像的污水检测的水域面积较大,造成检测耗费的时间比较长,最终导致湖泊水质污染检测存在较大滞后且准确性差的问题。提出一种改进神经网络的湖泊水质污染检测方式,首先利用神经网络数学模型对图像相关数据进行二进制编码,并对编码后的数据进行压缩处理,计算输出数据的差异系数,最后利用周期性数据压缩补偿算法对数据中的误差进行补偿,提高了湖泊水质污染检测的速度。实验证明,改进的检测方式能够提高湖泊水质污染检测速度,提高了准确性,取得了令人满意的效果。     

分布式计算环境中的协同分配任务调度仿真系统

协同分配是在分布式计算环境中进行资源分配的一种重要技术,用于把一个应用程序分解为多个子作业,然后将其分配到多个资源上同时处理来满足特定的性能要求。本文提出了一个离散事件驱动的网格资源协同分配仿真系统,实现了对用户、调度器、协同分配器、协同预留器等协同分配相关实体的仿真,实现了FCFS、FPFS、Backfill等主要的协同分配调度算法和策略,可用于资源协同分配相关的分布式计算环境的资源管理和调度算法的仿真和研究。     

组态王和VB在远程定位中的应用

为了利用组态王6.53接收远程数据功能和VB(Visual Basic)对MapX控件进行二次开发功能,利用DDE(Dynamic Data Exchange)技术,实现了组态王6.53与VB通信,根据组态王通信使用的MODBUS协议格式和GPS(Global Positioning System)数据格式,来提取经纬度信息,以此控制动态图层中的图元,来而实现远程车辆的定位,同时也扩大了监控中心软件的功能。     

AN EXPRESSION OF STRENGTH OF MARTENSITEFERRITE DUAL PHASE STEELS

考虑到马氏体加铁素体双相钢的组织分布及变形特征与短纤维复合材料的相似性,以剪切滞后分析法为基础,提出一种新的双相钢强度表达式: σ_(bDP)=(β/23~(1/2)+0.65)1/Kσ_(bM)V_M+σ_(bF)(1-V_M)在成分及组织各不相同的各种双相钢上所得的实验数据均与按上式计算的结果符合较好。文中讨论了铁素体向马氏体的载荷传递及马氏体强度利用率。     

Site occupations and ordering behaviour of O phase in Ti2AlNb—based intermetallics

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EFFECT OF WAVY GRAIN BOUNDARY ON CREEP FRACTURE BEHAVIOUR IN ASTROLOY ALLOY

Astroloy合金中弯曲晶界显著改善了材料的蠕变持久塑性和蠕变裂纹生长抗力。通过尖切口根处蠕变裂纹形成寿命分析与试验比较,证实蠕变J~*积分是控制尖切口(和裂纹)场的有效参量。据此由线性损伤模型和HRR奇异性结合,导出与直晶和弯晶试验结果吻合良好的蠕变裂纹扩展速率表达式: da/dt=Be~(k/n+1)D(x_0)J~(*kn/n+1) 从晶界孔洞形成角度讨论了弯曲晶界蠕变损伤的微观机制。