H_∞-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

The fault detection problem for the nonlinear networked control system （NCS） with packet dropout and delay is investigated. A nonlinear stochastic system model is proposed to account for the NCS with random packet dropout and network- induced non-uniformly distributed time-varying delay in both from sensor to controller （S/C） and from controller to actuator （C/A）. Based on the obtained NCS model, employing an observer-based fault detection filter as the residual generator, the addressed fault detection problem is converted into an auxiliary nonlinear H∞ control problem. Then, with the help of Lyapunov functional approach, a sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities, which depend on not only the delay interval but also the delay interval occurrence rate and successful packet communication rate. Especially, a trade-off phenomenon between the maximum allowable delay bound and successful data packet transmission rate is found, which is typically resulted from the limited bandwidth of communication networks. The effectiveness of the proposed method is demonstrated by a simulation example.

Observer-based H-infinity control in multiple channel networked control systems with random packet dropouts

This paper investigates the observer-based H-infinity control problem for networked control systems （NCSs） with random packet dropouts. A general packet dropout model with multiple independent stochastic variables in the multiple channels case is adopted to describe the data missing in the limited communication channels. With the consideration of the sensor-to-controller and controller-to-actuator packet dropouts at the same time, a new method is pro- posed based on a separation lemma to design an observer-based H-infinity controller, which exponentially stabilizes the closed-loop system in the sense of mean square and also achieves a prescribed H-infinity disturbance attenuation level. A numerical example is given to illustrate the effectiveness of the proposed control method.

Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.

A NEW RANDOM PACKET ACCESS PROTOCOL IN WCDMA

In this paper, a new Random Packet Access Protocol (RPAP) is proposed in WCDMA systems. The new proposed RPAP can efficiently prevent unnecessary interference by stopping a transmission if it is bound to be collided with others. Throughput about the new RPAP is deliberated and analyzed. Computer simulation shows that this protocol has better throughput performance compared with conventional one currently used in WCDMA.

Optimal full-order filtering for discrete-time systems with random measurement delays and multiple packet dropouts

This paper is concerned with the estimation problem for discrete-time stochastic linear systems with possible single unit delay and multiple packet dropouts. Based on a proposed uncertain model in data transmission, an optimal full-order filter for the state of the system is presented, which is shown to be of the form of employing the received outputs at the current and last time instants. The solution to the optimal filter is given in terms of a Riccati difference equation governed by two binary random variables. The optimal filter is reduced to the standard Kalman filter when there are no random delays and packet dropouts. The steady-state filter is also investigated. A sufficient condition for the existence of the steady-state filter is given. The asymptotic stability of the optimal filter is analyzed.

Random Access Algorithms in Packet Networks—A Review of Three Research Decades

We present a coherent and systematic review of Random Access Algorithms for packet networks, as developed over three and a half decades. We consider the appropriate user models and we classify the algorithms according to the channel sensing constraints imposed. We also present a review of the analytical methodologies required for the performance analysis of these algorithms.

Performance Characterization and Receiver Design for Random Temporal Multiple Access in Non-Coordinated Networks

Random access is a well-known multiple access method for uncoordinated communication nodes.Existing work mainly focuses on optimizing iterative access protocols,assuming that packets are corrupted once they are collided,or that feedback is available and can be exploited.In practice,a packet may still be able to be recovered successfully even when collided with other packets.System design and performance analysis under such a situation,particularly when the details of collision are taken into consideration,are less known.In this paper,we provide a framework for analytically evaluating the actual detection performance in a random temporal multiple access system where nodes can only transmit.Explicit expressions are provided for collision probability and signal to interference and noise ratio(SINR)when different numbers of packets are collided.We then discuss and compare two receiver options for the AP,and provide detailed receiver design for the premium one.In particular,we propose a synchronization scheme which can largely reduce the preamble length.We also demonstrate that system performance could be a convex function of preamble length both analytically and via simulation,as well as the forward error correction(FEC)coding rate.

金刚石滚轮轮廓圆度误差在线判别

金刚石滚轮形面的修形技术是制造金刚石滚轮的关键技术之一,常采用金刚石砂轮磨削法对其进行精密修形,修形后的轮廓圆度误差是考量滚轮修形合格与否的重要指标。目前的轮廓圆度检测方法是人工停机取下滚轮并放置于轮廓仪上进行,极大地增加了滚轮制作的时间和成本。为此,对在五轴加工机床上的金刚石滚轮,沿其轮廓面横向磨削修形时产生的振动信号,提出基于小波包系数和随机森林的在线检测方法并对其轮廓修形状态进行识别,在修形进行状态时的识别准确率为93.3%,具有实际应用价值。

5G系统中随机接入基带信号生成算法的研究与FPGA实现

针对5G随机接入基带信号生成算法计算量大且难以实现的问题,提出一种分组交织的随机接入基带信号生成算法。将基带信号生成过程中的大点数离散傅里叶逆变换(Inverse Discrete Fourier Transformation,IDFT)划分成多组小点数快速傅里叶逆变换(Inverse Fast Fourier Transform,IFFT)分别乘以对应的修正系数,对各小组数据进行IFFT运算和交织。仿真表明,该算法与直接使用IDFT生成的信号之间均方误差仅为1.66×10^(-32),且相较于传统算法,算法复杂度更低。在FPGA平台上验证了该方案的可行性和有效性。

基于主轴电机电流信号的表面粗糙度检测

针对表面粗糙度不能及时检测造成的工件浪费问题,首次提出根据主轴电机电流信号进行表面粗糙度检测分类。通过实验采集不同表面粗糙度加工时的主轴电机电流信号,采用小波包分解将电流信号分解成不同频段,借助能量特征和裕度因子对不同频段电流信号进行评估,过滤低相关性频段,再通过随机森林筛选特征,降低特征的冗余性。总谐波失真特征实现了积屑瘤检测,仅依赖构建的电流信号特征工程表面粗糙度检测准确率高达95%以上,并且检测时间在2 s以内,基本实现了工件表面粗糙度的快速准确检测。

基于随机森林算法的V2G充电桩故障诊断研究

针对V2G直流充电桩开关模块的故障诊断问题,提出一种基于随机森林算法的诊断方法。该方法使用小波包分析提取故障电流信号中的特征信息,使用核主成分分析降维以降低样本数据的复杂程度,使用随机森林算法训练出适用于直流充电桩开关模块的故障诊断器。实验验证表明,采用随机森林故障诊断器可以有效诊断开关模块故障。该方案在直流充电桩开关模块故障诊断方面具有现实意义。

截止期限下的无线随机接入网络性能研究

随着实时物联网场景需求的增加,无线数据的传输需要确定性的保障。因此,研究了在有截止期限约束下的无线随机接入的时效性和包接收情况。具体来说,首先考虑多用户时隙ALOHA,其中每个活跃用户在随机接入的信道上传输有截止期限的数据包,未能成功传输则被丢弃;其次建立数学模型研究截止期限下不同传输概率和重传机制对系统时效和包接收的影响。结果表明,引入重传机制和根据用户规模调整传输概率能够提高系统的包接收率和时效性。

基于深度融合模型的气膜密封端面状态识别方法

气膜密封装置是工业领域应用广泛的一种密封技术,其可靠的密封性能对于设备正常运行至关重要。气膜密封装置的动静密封环接触端面相对运动会产生摩擦,摩擦过程会产生复杂的声发射信号,这些信号往往隐含密封端面运行状况的重要信息。采用传统的方法往往难以准确识别和分类这些微弱的特征信号,因此需要开发更高精度的故障诊断方法。针对机械密封动、静环端面摩擦状态难以识别这一问题,以气膜密封装置为研究对象,提出了一种基于深度融合模型的气膜密封端面状态识别方法。首先,采用声发射传感器及采集设备,对密封端面的声发射信号进行了采集;其次,利用小波包变换方法对采集到的信号进行了滤波处理,并提取了时域和频域的微弱特征;然后,将深度随机森林(DRF)作为分类层融入卷积神经网络(CNN)形成了融合模型,对预先处理过的密封装置运行状态的特征信息进行了识别和分类;最后,根据实验的泄漏量,使用混淆矩阵和受试者工作曲线分析了两种模型的特征提取能力。研究结果表明:CNN-DRF融合模型对于密封端面声发射信号的两种特征识别精度分别为96%和98%,与传统的CNN模型相比,其可以充分提取信号特征信息,具有更出色的故障诊断能力。

具有随机丢包的一类网络控制系统的故障检测

针对存在随机数据包丢失的网络环境,研究了一类网络控制系统的故障检测问题.考虑随机丢包同时发生在传感器与控制器以及控制器与执行器之间,将网络控制系统建模为含有4个模态的马尔可夫跳变线性系统.基于此类模型,构造了系统的残差发生器,相应的故障检测问题转化为H∞滤波问题.利用马尔可夫跳变线性系统理论,设计了故障检测滤波器,使得残差动态系统均方稳定,且满足一定的扰动抑制水平.数值算例表明,在发生随机数据包丢失的情况下,上述故障检测滤波器不仅对故障敏感,同时对外界扰动具有鲁棒性.

一种用于异常检测的网络流量抽样方法

为了减小抽样数据对网络异常检测的影响,提出了一种新的可变抽样率的网络流量抽样方法.通过利用哈希模式匹配算法,将到达的数据报文按流标识分类并记录下该报文在流中的位置,然后根据报文所属流的位置顺序减函数来设置不同的报文抽样概率.实验结果表明,所提方法增加了短流报文的抽样概率,解决了由于随机报文抽样方法偏向于长流抽样而导致的网络异常丢弃的问题,从而提高了异常检测的正确性.

具有一步随机时滞和多丢包的网络系统H_∞滤波器设计

在网络系统中由于连接传感器和滤波器的网络带宽有限,系统测量数据在传输中会出现随机时延甚至丢失.本文讨论了具有一步随机时延和丢包的网络系统的H∞滤波器设计问题.基于新近提出的同时描述随机时延和丢包的模型,利用线性矩阵不等式方法设计线性滤波器,使得滤波误差系统均方指数稳定,并具有给定的H∞性能.滤波器参数通过求解一个线性矩阵不等式得到.仿真研究说明了所提出算法的有效性.

基于FNN的污水处理过程数据丢包补偿方法研究

针对污水处理数据传输过程具有随机丢包的问题,提出一种基于模糊神经网络的数据丢包预测补偿方法。该方法利用模糊神经网络的自适应特点,结合缓冲区、事件-时间混合驱动以及时间标志信息,通过利用已知的数据包预测出当前丢失的数据包,对污水处理过程网络传输丢包数据进行了实时补偿,解决了污水处理数据传输过程的随机丢包问题。实验结果显示,该方法能够有效地实现丢包数据的预测和补偿,与其他方法的比较结果显示该方法具有较好的性能。

基于小波包分解多信息融合的配电网故障选线保护方法

为了解决配电网混合线路频发单相接地故障导致选线困难的问题,提出了一种新的保护方法。该方法通过db10小波包对配电网每条出线的零序电流进行第5层分解得到零序电流小波低频重构系数,运用Hausdorff距离算法将每条出线的低频重构系数进行计算得到不匹配度特征值;再结合小波包能量特点得到每条出线归一化后的综合小波能量特征值,将两种故障特征量作为输入量,结合随机森林算法具有数据融合和无需设定阀值的特性,建立配电网故障选线判别模型。通过将不同工况下得到的256组训练样本数据对模型进行训练获得判别模型的最优参数,再将剩余不同的48组测试数据进行模型验证,结果表明该方法在不同的故障条件下故障判别准确率高,具有较强的适用性。同时将所提出的方法与BP神经网络、ELM信息融合选线方法进行了对比,仿真结果表明,在加入信噪比为40 dB和20 dB的高斯白噪声的工况下,所提出的故障选线方法无论是分类准确率还是收敛时间都具有显著的优势。

网络控制系统动态量化H∞控制

基于线性矩阵不等式技术,采用状态反馈控制,考虑同时带有网络诱导随机丢包和量化的H∞控制问题。考虑信号经网络从传感器到控制器和从控制器到执行器的传输中存在通信诱导随机丢包,并采用动态量化器量化信号。设计H∞控制器的同时,提出量化的控制策略,使得闭环系统在量化器的量化范围条件下指数均方稳定且具有指定的H∞性能指标。通过数值仿真例子表明设计方法的有效性。

随机丢包时延网络控制系统动态输出反馈控制

针对传感器与控制器、控制器与执行器之间具有随机丢包和时延的网络控制系统,研究统一建模及动态输出反馈控制问题.采用多个马尔可夫链分别描述前向通道和反馈通道的随机丢包与时延过程,将闭环网络控制系统建模成具有多个模态的马尔可夫随机跳变系统.利用增广矩阵技术和李雅普诺夫方法得到闭环系统随机稳定的充分条件,给出动态输出反馈控制器的设计方法.通过倒立摆系统验证动态反馈控制的有效性.