系统辨识大牛Ljung编写的MATLAB系统辨识使用手册
系统辨识大牛Ljung编写的MATLAB系统辨识使用手册，这本书详细地介绍了在MATLAB已经所属simulink环境下，系统辨识工具箱的一些使用办法，是一本非常经典的教材！Revision Historypril 1988First printingJuly 1991Second printingMay1995Third printingNovember 2000 Fourth printingRevised for Version 5.0(Release 12)pril 2001Fifth printingJuly 2002Online onlyRevised for Version 5.0.2 Release 13)June 2004Sixth printingRevised for Version 6.0.1(Release 14)March 2005Online onlyRevised for Version 6.1.1Release 14SP2)September 2005 Seventh printingRevised for Version 6.1.2(Release 14SP3)March 2006Online onlyRevised for Version 6.1.3(Release 2006a)September 2006 Online onlyRevised for Version 6.2 Release 2006b)March 2007Online onlyRevised for Version 7.0 ( Release 2007a)September 2007 Online onlyRevised for Version 7.1 (Release 2007bMarch 2008Online onlyRevised for Version 7.2(Release 2008a)October 2008Online onlyRevised for Version 7.2.1 Release 2008b)March 2009Online onlyRevised for Version 7.3(Release 2009a)September 2009 Online onlyRevised for Version 7.3.1(Release 2009b)March 2010Online onlyRevised for Version 7. 4 (Release 2010a)eptember2010 Online onlyRevised for Version 7.4.1(Release 2010b)pril 2011Online onlRevised for Version 7.4.2(Release 2011a)September 2011 Online onlyRevised for Version 7.4.3(Release 2011b)March 2012Online onlyRevised for Version 8.0( Release 2012aabout the DevelopersAbout the Developersystem Identification Toolbox software is developed in association with thefollowing leading researchers in the system identification fieldLennart Ljung. Professor Lennart Ljung is with the department ofElectrical Engineering at Linkoping University in Sweden. He is a recognizedleader in system identification and has published numerous papers and booksin this areaQinghua Zhang. Dr. Qinghua Zhang is a researcher at Institut Nationalde recherche en Informatique et en Automatique(INria) and at Institut deRecherche en Informatique et systemes Aleatoires (Irisa), both in rennesFrance. He conducts research in the areas of nonlinear system identificationfault diagnosis, and signal processing with applications in the fields of energyautomotive, and biomedical systemsPeter Lindskog. Dr. Peter Lindskog is employed by nira dynamiAB, Sweden. He conducts research in the areas of system identificationsignal processing, and automatic control with a focus on vehicle industryapplicationsAnatoli Juditsky. Professor Anatoli Juditsky is with the laboratoire JeanKuntzmann at the Universite Joseph Fourier, Grenoble, france. He conductsresearch in the areas of nonparametric statistics, system identification, andstochastic optimizationAbout the developersContentsChoosing Your System Identification ApproachLinear model structures1-2What Are Model objects?Model objects represent linear systemsAbout model data1-5Types of Model objectsDynamic System Models1-9Numeric Models1-11umeric Linear Time Invariant (LTD Models1-11Identified LTI modelsIdentified Nonlinear models1-12Nonlinear model structures1-13Recommended Model Estimation Sequence1-14Supported Models for Time- and Frequency-DomainData,,,,,,,1-16Supported Models for Time-Domain Data1-16Supported Models for Frequency-Domain Data1-17See also1-18Supported Continuous-and Discrete-Time Models1-19Model estimation commands1-21Creating Model Structures at the command Line ... 1-22about system Identification Toolbox Model Objects ... 1-22When to Construct a Model Structure Independently ofEstimation1-23Commands for Constructing Model Structures1-24Model Properties1-25See als1-27Modeling Multiple-Output Systems ......... 1-28About Modeling multiple-Output Systems1-28Modeling Multiple Outputs Directly1-29Modeling multiple outputs as a Combination ofSingle-Output Models.......1-29Improving Multiple-Output Estimation Results byWeighing Outputs During Estimation ....... 1-30Identified linear Time-Invariant models1-32IDLTI Models1-32Configuration of the Structure of Measured and Noise oRepresentation of the Measured and noise Components foVarious model Types1-33Components ....1-35Imposing Constraints on the Values of ModeParameters1-37Estimation of Linear models1-8Data Import and Processing2「Supported Data ...2-3Ways to Obtain Identification DataWays to Prepare Data for System Identification ... 2-6Requirements on Data SamplingRepresenting Data in MATLAB Workspace·····Time-Domain Data Representation2-9Time-Series Data Representation2-10ContentsFrequency-Domain Data Representation ....... 2-11Importing Data into the Gui2-17Types of Data You Can import into the GUi2-17Importing time-Domain Data into the GUI2-18Importing Frequency-Domain Data into the GUI2-22Importing Data Objects into the GUI ......... 2-30Specifying the data sampling interval2-34Specifying estimation and validation Data2-35Preping data Using Quick StartCreating Data Sets from a Subset of Signal Channelo2-362-37Creating multiexperiment Data Sets in the gUi2-39Managing data in the gui ............. 2-46Representing Time- and Frequency-Domain Data Usingiddata object2-55iddata constructor2-55iddata Properties.........2-58Creating Multiexperiment Data at the Command Line .. 2-61Select Data Channels, I/O Data and Experiments in iddataObjects2-63Increasing Number of Channels or Data Points of iddataObjects2-67Managing iddata Objects2-69Representing Frequency-Response Data Using idfrdObiec2-76idfrd Constructor2-76idfrd Properties2-77Select I/o Channels and Data in idfrd Objects ..... 2-79Adding Input or Output Channels in idfrd Objects2-80Managing idfrd Objects2-83Operations That Create idfrd Objects2-83Analyzing Data quality2-85Is your data ready for modeling?2-85Plotting Data in the guI Versus at the command line2-86How to plot data in the gui2-86How to plot data at the command line2-92How to Analyze Data Using the advice Command2-94Selecting Subsets of Data2-96IXWhy Select Subsets of Data?2-96Extract Subsets of Data Using the GUI2-97Extract Subsets of data at the Command Line2-99Handling Missing Data and outliers2-100Handling missing data2-100Handling outliers2-101Extract and Model Specific Data Segments2-102See also2-103Handling offsets and Trends in Data2-104When to detrend data2-104Alternatives for Detrending Data in GUi or at theCommand-Line2-105Next Steps After detrending2-107How to Detrend Data Using the Gui2-108How to detrend data at the Command line2-109Detrending Steady-State Dat109cending transient Dat2-109See also2-110Resampling Data2-111What Is resampling?...,,.,,,,,,,,,,,.2-111Resampling data without Aliasing Effects2-112See also2-116Resampling data Using the GUi.,,,,2-117Resampling Data at the Command line2-118Filtering Data2-120Supported Filters2-120Choosing to Prefilter Your Data2-120See also2-121How to Filter Data Using the gui2-122Filtering Time-Domain Data in the GuI........ 2-122Content
- 2020-12-11下载
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心率检测系统的设计论文
心率检测系统的设计论文，ti杯电子设计大赛优秀论文右手接至低通前置放大电路滤波器输左手入端共模电压右腿驱动屏蔽动右腿退导联屏蔽线图2前置放人电路框图1)前賢放大调理针对心电信号高增益,高输入阻抗,高垬模抑訇比,低噪声,低漂移和合适带宽的采集要求,采用仪表放大器,以获得良好的综合性能。所以采用仪用放大器AD620只要用只外接电阻便可设置放大器的增益,增益G为494人R2)右腿驱动电路将右腿连接到一个辅助的运算放大器的输出端,把混杂于原始心电信号中的共模噪声提取出来,经过一级倒相放大后,再返回到人体,使它们相互叠加,从而减小人体共模干扰的绝对值,提高信噪比。本电路采用高精度运算放大器O217。通过这个负反馈结构,可大大抑制测量过程屮前置敚大器输入端共模电压的影响。此外,右腿驱动电路还可以提供电气上的安全性。3)屏蔽驱动电路屏蔽驱动器是一个同相电压跟随器,将放大器的输出端和屏蔽相连,将屏蔽线和地隔开,并且对于50Ⅳz的共模干扰信号来说,从人体输入的两路信号是相等的导联线和屏蔽线之间的电压差为0,从而消除了其间的电容,提高了输入电路的阻抗,降低人与地之间的漏电流。如图3所小220kTT1点2R图3带屏蔽驱动、右腿驱动的前置放大调理电路经过前置放大器后心电信号被放大的倍数为49.4KG=1+51IK∥(24.9K+24.9K)(2)高通滤波电路的设计电极与皮肤表面之间容易产生直流偏压,为了消除这部分的干扰,需要采取高通滤波电路图4所示予以滤除,其截止频率为≈0.5Hz2丌√RR,CC22x√22X×47K×101×10U4BQPZITT图4二阶高通滤波电路(3)低通滤波电路的设计噪声来源一类是各种电子设备辐射出的高频噪声,一类是市电的50z噪声。通常情况下后者影响尤为明显。对这些噪声的滤波需要用到滤波器。低通滤波器(电路图如图5)通常情况下截止频率选择在100Hz以下。低通截止频率为2兀√RR1CC42√24K×24K×0.047×Dm≈100H2T745TQP2171图5二阶低通滤波电路(4)50Hz陷波电路的设计为了去除人体或测试系统中产生的工频50Hz干扰34,需用带阻滤波器加以抑制。我们采用心电测量没备当前普煸采用的双T陷波电路滤除工频干扰,其参数计R算公式为:2可C其中f为滤去频率,如图6所小。USD图650Hz陷波电路(5)后置放大电路及抬升电路的设计因为wsP430F169模数转换器的范围为0~2.5V,所以要对采集的心电信号进行拾升如此在实现后置放大的过程中,既要考虑信号中平的提升,又要实现信号的放大。放大器芯片用INA217。具体电路如图7所示图7后置放大发抬升电路放大倍数为:G=110K10KRIK抬升电路有对放大信号拾升了1.25V(6)电源电路的设计电源电路的设计是由电平转换器760,线性调节器MX8511,电压基准REF3025及电池盒组成,如图8所示电源电路图8电源电路31.3元件的布局和PCB板的设计在PCB板中,包含多种类型的电路,为了避免各部分电路中信号相互耦合而生千扰,对不同类型的电路部分进行分离布局是PCB板设计的一个基本原则。各部分之间不仅应保持相当距离,还要分开走线。电源系统的布线包括电源线VDD和地线vSs的布线,是系统抗干扰的个重要部分。VDD和wSS应尽可能扩大面积,以防止因电磁能量较强而产生电磁干扰能量的发射,这也是保证高频信号到地之间具有低阻抗的措施3.2软件设计软件设计的关键是对MSP430F169的控制以及LCD显示。所有软件均采用C语言绽写。软件实现的功能是QRS波检测并算出心率,LCD显小波形以及SD卡存储3.2.1软件流程系统软件部分流程图9如下所示,开关按键按下后,屏幕显示L0GO图(江苏省TⅠ杯电子设计大赛),通过对各模块的初始化后,由中断定时服务实现对心电信号QRS波检测,心率计算,波形回放。系统初始化A/D采集LCG0显示N按键显示模块初始化
- 2020-12-01下载
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