基于强跟踪滤波器训练的前向神经网络及其在系统辨识中的应用研究*

给出基于强跟踪滤波器训练前向神经网络的新方法。由于强制残差序列保持相互正交,强跟踪滤波器相对扩展Kalman滤波的收敛速度更快,同时精度更高。最后通过系统辨识仿真实例验证该方法的有效性。     

多关节机器人通用体系结构的研究

结合一个五自由度教学工业两用型机器人应用实例，构造出多关节机器人通用体系结构，包括总体原型、机械结构、关节传动链、伺服驱动元件、电气控制系统、关节坐标系及其运动学方程、通信协议和软件设计思路等。通过实际使用表明，本文提出的通用体系结构是实用的、合理的。     

谈压力容器管理中微机应用

本文介绍一种系统软件在压力容器管理中应用。实践证明,该系统软件运行可靠,操作方便,提高了劳动效率和准确率,降低了劳动强度。     

Variance analysis of identified linear MISO models having spatially correlated inputs,with application to parallel Hammerstein models

This contribution concerns variance analysis of linear multi-input single-output models when the inputs are temporally white but where different inputs may be correlated. An expression is provided for the variance of a linearly parametrized estimate of the frequency response function from one block, i.e. from one input to the output. In particular, this expression reveals that the variance increases in one block when the number of estimated parameters in another block is increased, but levels off when the number of parameters in the other block reaches the number of parameters in the block in question. It also quantifies exactly how correlation between inputs affects the resulting accuracy and a graphical representation is provided for this purpose. The results are applicable to parallel MISO Hammerstein models when the nonlinearities are known and generalize an existing variance expression for this type of model.     

Reasons for bottlenecks in very large-scale system of systems development

ContextSystem of systems (SoS) is a set or arrangement of systems that results when independent and useful systems are to be incorporated into a larger system that delivers unique capabilities. Our investigation showed that the development life cycle (i.e. the activities transforming requirements into design, code, test cases, and releases) in SoS is more prone to bottlenecks in comparison to single systems.ObjectiveThe objective of the research is to identify reasons for bottlenecks in SoS, prioritize their significance according to their effect on bottlenecks, and compare them with respect to different roles and different perspectives, i.e. SoS view (concerned with integration of systems), and systems view (concerned with system development and delivery).MethodThe research method used is a case study at Ericsson AB.ResultsResults show that the most significant reasons for bottlenecks are related to requirements engineering. All the different roles agree on the significance of requirements related factors. However, there are also disagreements between the roles, in particular with respect to quality related reasons. Quality related hinders are primarily observed and highly prioritized by quality assurance responsibles. Furthermore, SoS view and system view perceive different hinders, and prioritize them differently.ConclusionWe conclude that solutions for requirements engineering in SoS context are needed, quality awareness in the organization has to be achieved end to end, and views between SoS and system view need to be aligned to avoid sub optimization in improvements.     

Applying a student modeling with non-monotonic diagnosis to Intelligent Virtual Environment for Training/Instruction

We present a student modeling approach that has been designed to be part of an Intelligent Virtual Environment for Training and/or Instruction (IVET). In order to provide the proper tutoring to a student, an IVET needs to keep and update dynamically a student model taking into account the student’s behaviour in the Virtual Environment. For that purpose, the proposed student model employs a student ontology, a pedagogic diagnosis module and a Conflict Solver module. The goal of the pedagogic diagnosis module is to infer which learning objectives have been acquired or not by the student. Nevertheless, the diagnosis process can be complicated by the fact that while learning the student will not only acquire new knowledge, but he/she may also forget some previously acquired knowledge, or he/she may have some oversights that could mislead the tutor about the true state of the student’s knowledge. All of these situations will lead to contradictions in the student model that must be solved so that the diagnosis can continue. Thus, our approach consists in applying diagnosis rules until a contradiction arises. At that moment, a conflict solver module is responsible of classifying and solving the contradiction. Next, the student ontology is updated according to the resolution adopted by the Conflict Solver and the diagnosis can continue. This paper mainly focuses on the design of the proper mechanisms of the student model to deal with the non monotonic nature of the pedagogic diagnosis.     

Jet bundle formulation of infinite-dimensional port-Hamiltonian systems using differential operators

We consider infinite-dimensional port-Hamiltonian systems described on jet bundles. Based on a power balance relation we introduce the port-Hamiltonian system representation using differential operators regarding the structural mapping, the dissipation mapping and the input mapping. In contrast to the well-known representation on the basis of the underlying Stokes–Dirac structure our approach is not necessarily based on using energy-variables which leads to a different port-Hamiltonian representation of the analyzed partial differential equations. The presented constructions will be specialized to mechanical systems to which class also the presented examples belong.     

基于面向服务的泥石流数值模拟通用平台

对当前泥石流模拟系统的单一性缺点进行了研究,提出了面向服务的泥石流数值模拟的通用平台思想。以有限差分模型为基础,采用面向服务的思想,设计了系统 C/S模式的技术方案并完成了整个系统的设计和实现。经过香港滑坡地形图的验证,证明了本通用平台的可行性和有效性。     

磁盘阵列环境下的取证目标系统重构

封存原始硬盘与业务系统服务的连续性是计算机取证中面临的一对矛盾。在独立硬盘环境中,问题的解决并不困难,但在磁盘阵列(RAID)环境下,目前还缺乏有效的解决办法。为此,为RAID环境下的取证目标系统的重构提出一套解决方案,并设计实现其中关键任务的处理软件。实验表明,该方法可适用于不同RAID等级、不同操作系统下的系统重构,使得用户感受不到重构得到的系统与原系统有任何差异。与数据同步方法相比,该方法可以有效地减少重构的时间开销,且不会破坏原始证据硬盘上的数据。     

使用新混合模糊聚类算法的模糊系统建模方法

为了进一步提高模糊系统建立模型的精度,提出一种新的模糊系统算法ANFIS-HC-QPSO：采用一种混合型模糊聚类算法来对模糊系统的输入空间进行划分,每一个聚类通过高斯函数的拟合产生一个隶属度函数,即完成ANFIS系统的前件参数--隶属度函数参数的初始识别,通过具有量子行为的粒子群算法QPSO与最小二乘法优化前件参数,直至达到停机条件,最终得到ANFIS的前件及后件参数,从而得到满意的模糊系统模型。实验表明,AN-FIS-HC-QPSO算法与传统算法相比,能在只需较少模糊规则的前提下就使模糊系统达到更高的精度。