Nonsmooth identification of mechanical systems with backlash-like hysteresis

Backlash-like hysteresis is one of the nonsmooth and multi-valued nonlinearities usually existing in mechanical systems. The traditional identification method is quite difficult to be used to model the systems involved with such complex nonlinearities. In this paper, a nonsmooth recursive identification algorithm for the systems with backlash-like hysteresis is proposed. In this method, the concept of Clarke subgradient is introduced to approximate the gradients at nonsmooth points and the so-called bundle method is used to obtain the optimization search direction in nonsmooth cases. Then, a recursive algorithm based on the idea of bundle method is developed for parameter estimation. After that, the convergence analysis of the algorithm is investigated. Finally, simulation results to validate the proposed method on a simulated mechanical transmission system are presented.     

A Recommendation System Keeping Both Precision and Recall by Extraction of Uninteresting Information

A recommendation system which recommends interesting information to the target user must guarantee high precision and recall. However, there is trade-off between precision and recall. In this paper, we propose a web page recommendation method balancing both of them by take advantage of uninteresting information. The proposed method extracts the interest and uninterest indicators from not only historical interesting web pages but also uninteresting ones in a target genre. The historical interesting and uninteresting information is derived based on the browsing time and bookmarking. The proposed method can keep precision and recall by excluding the uninteresting information from the recommended ones based on the interest and uninterest indicators. The experimental result proved that the proposed method can improve the precision and recall than an existing method.     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

Quantized H∞ Control for Networked Systems with Communication Constraints

The problem of quantized H_∞ control for networked control systems (NCSs) subject to time‐varying delay and multiple packet dropouts is investigated in this paper. Both the control input and the measurement output signals are quantized before being transmitted and the quantized errors are described as sector bound uncertainties. The measurement channel and the control channel packet dropouts are considered simultaneously, and the stochastic variables satisfying Bernoulli random binary distribution are utilized to model the random multiple packet dropouts. Sufficient conditions for the existence of an observer‐based controller are established to ensure the exponential mean‐square stablility of the closed‐loop system and achieve the optimal H_∞ disturbance attenuation level. By using a globally convergent algorithm involving convex optimization, the nonconvex feasibility can be solved successfully. Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed method.     

核电站数字化反应堆保护系统停堆响应时间分析

为了评价出核电站数字化反应堆保护系统停堆响应的最大时间,根据数字化反应堆保护系统结构,分析出保护系统的响应过程须经过AI输入、IO总线通讯、CPU运算、网络通讯、DO输出处理。并基于DCS定周期扫描的运行方式,得出了各处理过程所需最大响应时间的计算方法,DCS停堆响应时间的评价值就是各部分最大响应时间的累加。最后提出了可缩短响应时间的改进方法。     

论职业学校计算机应用教学优化与整合

课程体系是计算机教学目标实现的重要保证,职业计算机应用专业课程体系要以为社会培养计算机应用性专业人才这一根本任务而进行设计。本文对计算机应用专业课程设置进行一定的探讨。     

基于以太网络的数据传输系统设计研究

随着电子通信技术的发展,分布式测控系统也应运而生,并且规模在逐渐的扩大。在大的发展趋势前提下,监测数据在远距离传输的时候,如何保证其高效、安全、可靠地传输,已经成为计算机产业热议的话题。嵌入式以太网的实现为数据传输系统的设计创造了有利条件。     

高职计算机专业学生评价体系的探索

在德国职业教育的影响下,高职计算机专业教育开始推行任务驱动,工作过程导向的教育模式,但是其教育评价体系还没有与教学模式相统一,实现与对应就业岗位需求的完美结合。高职计算机专业教育评价体系包含了很多方面,本文主要从学生学习效果的评价体系进行探索。     

基于四层的数据交换体系结构的实现与性能分析

随着信息数据处理的要求不断提高,目前以三层体系结构为主的信息系统逐渐不能满足其需要,新增了数据预处理层地四层体系结构是未来发展的趋势。本文在概述四层系统结构理论的基础上,具体阐述了顸处理层的具体实现,并对其性能进行分析。     

PSO和K均值混合分类算法在远程教学系统中的应用

现行的多数网络教学系统在学生按需学习和＂因材施教＂上存在局限性,本文用PSO和K均值的混合分类算法对传统的网络教学系统进行改进,根据获取的用户基本信息和兴趣特征进行聚类,充分体现＂以学习者为中心＂个性化教学模式。实验结果表明,该算法具有较好的全局收敛性,寻优能力明显提升。