改进Elman网络的污水处理过程建模

污水处理过程具有多变量、非线性、大滞后和强耦合的特点,建立精确的数学模型十分困难,为了精确的描述污水处理过程,本文将1种改进型的递归神经网络应用在污水处理过程建模中,建立了污水处理过程关键水质参数的智能模型。Elman网络作为1种动态神经网络,网络的动态特性可以很好的反映系统的内部动力学特征,但是标准的Elman网络只对隐含层的输出进行了反馈,并且只反馈给了隐含层的输入,反馈信息较少。针对此问题,本文提出1种改进型的Elman网络(OAF Elman网络),增加了输出层的反馈信息,将反馈信息既传给隐含层输入又传给输出层的输入,同时将隐含层的反馈也作为输入层的输入,使网络的输出包含更多的输入信息,能够更好的反映系统的时变、非线性等特征。采集污水处理厂生化反应过程实际运行数据,取对COD影响较大的MLVSS、进水COD、pH值、氨氮4个种指标作为递归神经网络模型的输入,对污水出水的关键水质参数COD进行建模,网络的训练误差达到0.011,测试误差达到0.4875。实验结果表明:与传统的Elman网络和其他几种改进型的Elman网络相比,本文提出的OAF Elman网络具有更丰富的动力学特性,建立的污水处理模型达到...     

4U平行四边形机构的一类新用途——整体设计为两足步行机构

提出了将4U平行四边形机构整体设计为两足步行机构的一类新用途.此类两足步行4U平行四边形机构均由4个构件和4个万向铰组成,能够实现平面运动.根据万向铰布置方式的不同,分为3种构型.在针对构型Ⅰ的前期研究基础之上,应用螺旋理论分析了构型Ⅱ和Ⅲ的自由度,并分别对其进行了运动学分析、步态分析和稳定性分析.此外,还将3种构型的性能与应用作了进一步的分析与比较.运用ADAMS软件建立3种构型的动力学模型,仿真其运动的全过程,验证该类构型及其运动的可行性.制作出2台样机,实现了预期的运动.     

伺服问题的二自由度镇定控制器参数化

对于多输入多输出四块线性系统,本文研究了存在跟踪和干扰抑制约束的二自由度镇定控制器参数化问题,给出了一般条件下的伺服问题二自由度镇定控制器参数化表示。     

电力系统结线分析的有色Petri网方法

从离散事件动态系统角度考虑电力系统结线分析问题,提出了基本分析单元的有色Petri网模型以及基于该Petri网的结线分析算法,Petri网中的令牌代表结线分析中的结点,令牌的颜色表示连接在同一个结点上的元件,变迁将包含相同元件的结点连接在一起,论文对基于Petri网的结线分析算法及传统的算法进行了比较,并计算了一个模型系统各变电站的结点及网络的结线,表明了该方法的可行性及有效性。     

Experimental research on air film formation behavior of air cushion belt conveyor with stable load

In this paper, the air film formation behavior of air cushion belt conveyor with stable load is studied. The air cushion field is analyzed by means of theoretical derivation, numerical simulation and experimental research. An intelligent experiment platform is developed. Three dimensional pressure distribution of air film and the air film thickness distribution along the conveyor belt in the width direction are obtained. The experimental result is analyzed by comparing with theoretical calculation and numerical simulation. The numerical and theoretical results are in good agreement with those obtained from experiments. The air film formation behavior pattern of air cushion belt conveyor with stable load is presented. The optimized film thickness and pore distribution are obtained based on the comprehensive energy consumption. This study provides a basis for the optimization design of air cushion belt conveyor.     

Distributed estimation via iterative projections with application to power network monitoring

This work presents a distributed method for control centers to monitor the operating condition of a power network, i.e., to estimate the network state, and to ultimately determine the occurrence of threatening situations. State estimation has been recognized to be a fundamental task for network control centers to operate safely and reliably a power grid. We consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltage phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state, given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is used, whereas, in the second method, a diffusive interaction is implemented. Our procedures, which require each control center to know only the measurements and the structure of a subpart of the whole network, are computationally efficient and scalable with respect to the network dimension, provided that the number of control centers also increases with the network cardinality. Additionally, a finite-memory approximation of our diffusive algorithm is proposed, and its accuracy is characterized. Finally, our estimation methods are exploited to develop a distributed algorithm to detect corrupted network measurements.     

基于IMEMS传感器的汽车行驶姿态检测系统设计

为了给汽车安全控制系统提供准确的行驶姿态数据,设计了基于集成微机电系统(IMEMS)传感器的虚拟仪器检测系统。系统采用IMEMS传感器采集车身姿态参数,在虚拟仪器平台下对数据进行分析处理,使用卡尔曼滤波器对测量值进行估计,并在实车工况下对检测系统进行测试。结果表明:系统能够很好地满足汽车行驶姿态检测的要求,具有可靠的实时性。     

基于改进LP变换及自适应PCNN的多聚焦图像融合方法

提出一种抗噪声多聚焦图像融合方法.首先,采用改进拉普拉斯金字塔（LP）变换构造图像的塔形数据结构.每层数据经脉冲耦合神经网络（PCNN）迭代运算生成相应的点火次数矩阵;然后,以此为依据经判决算子完成数据融合;最后,采用伪逆重构算法生成融合图像.实验结果表明,所提出的方法具有抗加性噪声及JPEG压缩系统噪声的能力,融合图像的客观评价指标较高,且能有效减弱原LP算法融合图像边缘的＂Gibss＂伪影现象.