A Distributed, Extensible and Accessible Sensory Control and Data Acquisition System

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自动驾驶汽车控制系统参数辨识与学习

ISSN 1674-8484CN 11-5904/U汽车安全与节能学报, 第9卷第2期, 2018年J Automotive Safety and Energy, Vol. 9 No. 2, 2018Identification and Learning in Autonomous V ehicle Control SystemsWANG Leyi 1, George Yin 2, ZHAO Guangliang 3, LI Shengbo 4, Xu Biao 4, LI Keqiang 4(1. Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA; 2. Department of Mathematics, Wayne State University, Detroit, MI 48202, USA; 3. GE Global Research Niskayuna, NY 12309, USA;4. Department of Automotive Engineering Tsinghua University, Beijing 100084, China)Abstract: System parameters of autonomous vehicles need to be identified and learned during operation to solve the problem that autonomous vehicles encounter many uncertainties that change with time, operating conditions, and environments. By capturing system behavior in a closed-loop setting and using data to learn the related parameters, system reliability and robustness can be quantitatively established. This paper focuses on a basic scenario of an autonomous vehicle following its front vehicle. By integrating control actions with vehicle dynamics, a learning algorithm using operational data and confidence ellipsoids was employed to support robustness and reliability. A simulation case study was used to illustrate the strategies. The results show the proposed method can estimate the vehicle’s parameters accurately.Key words: vehicle control; autonomous vehicle; identification of parameters; learning; robustness自动驾驶汽车控制系统参数辨识与学习（英文）王乐一1，殷刚2，赵广亮3，李升波4，徐彪4，李克强4（1.韦恩州立大学电气与计算机工程系，底特律市 MI 48202，美国；2.韦恩州立大学数学系，底特律市 MI 48202，美国；3.通用电气公司全球科研中心，尼斯卡于纳市 MI 48202，美国；4.清华大学汽车工程系，北京 100084，中国）摘要：针对自动驾驶汽车在行驶过程中会遇到随时间和交通环境变化的不确定性，须对自动驾驶系统参数进行辨识和学习。

FLUENT软件操作界面中英文对照

FLUENT 软件操作界面中英文对照File 文件Read 读取文件：scheme 方案journal 日志 profile 外形 Write 保存文件 Import :进入另一个运算程序 Interpolate :窜改，插入Hardcopy :复制，Batch opti ons —组选项Save layout 保存设计 Grid 网格| F 屆 Grid Define Solve i-Read► Write►Import ► Export-, Interpolate —Hardcopy...Batch Options.^Save LayoutRun...RSF...ExitDefine Models模型：solver解算器Pressure based 基于压力Den sity based基于密度末解用丁 pressure based,雀改用Censity based 岀观不苻合秦相36的摄不，请甸pres 羊WE base d Al density based 慎仆则迢.41刊卜 IS 况？北外.血OC ・EHU ^ cotipled ＞（/^ ptiaw ccupl ed simple 可这孔 & pimple ijEpiso 逞划.--■轟=Sortg 冲-丸布时制* ^jfe-5-6 1844DOden ba&ed 亘工F 吋.压聲血ptessurt ba$«i 适可于那可乐册斤"dens Ply based 把丸“河悴掏t ：至殳嗟之一.刑牛可爪門d 的创R 监當歎1一，般如人锻暮叫人丄有用轴怀，火薩墟迭牛才H5）-0 程：yje8D8-丸布门 1叫；20GS-3-7 10-2ODQ歆；I ：谢PrflSsdrfl-Bawd Soker ^Fluflnt 它星英于压力快的束解孤便丹的圮压力修止畀法"求释旳控制片悝足标联式的，擅K 家鮮不町压縮舐Mb 对于町压砂也可旦索麟；Fk«nl 6-3 tl 前的I 板』冷孵臥 B fjS4^r«^at«d &Olvar fli Cfruptod Solvtr,的实也fltje Pr#4iurft-ea5<KJ ScFvAi 约两种虽幵方ib应理拈Fluent 氐J 眇坝犢型小的.它拈垒于曲喪红旳求聲塞，最辑的出H .也桿艮先■那式的.丰誓■載密式冇Roz AU$hk>谏方法的初和&让Fhwrt 耳有比我甘的求IT 可压胃（说劫謹力，們耳帕榕式淮冇琴加IF 科限闾辉，倒比还丰A 完荐匚Coupted 的算送t 对子慨站何Hh 地们足便用円匕口讷油皿购加£未处為性上世魅端计棒低逢刈趾.擁说的DansJty-Bjiwd Solver F ft St SiMPLEC, P 怡DE 些选以的.闪为進些ffliQl ；力修止鼻袪・不金在这种类崖的我押■中氏现泊I 建址祢匹足整用Fw»ur 护P.sed Solver 堺决昧的利底*implicit 隐式， explicit 显示Space 空间：2D , axisymmetric （转动轴）， axisymmetric swirl （漩涡转动轴）；Time 时间 :steady 定常，unsteady 非定常 Velocity formulatio n 制定速度： absolute 绝对的；relative 相对的Gradient option 梯度选择：以单元作基础；以节点作基础；以单元作梯度的最小正方形。

RS简介

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机器人学基础第6章机器人传感器蔡自兴

Compound Force: detect forces along multiple directions.
Proximity: non-contact detection of objects. Simple Vision: detect feature such as holes, lines, and corners. Compound Vision: recognition of object.
6.1 Introduction to Robot Sensors
5
6.1 Introduction to Robot Sensors 6.2 Internal Sensors（内部传感器）
6.3 External Sensors（外部传感器）
6.4 Robot Sensor Application Considerations
4
6.1.1 Classification of Robot Sensors Most needed sensory abilities for robot:
Simple Touch: detect whether the object is there or not. Compound Touch: detect the size and shape of the object. Simple Force: detect force along one direction.
6.2 Internal Sensors
13
2．Relative Angle Sensor
In this approach, no matter the clockwise (CW) rotation, or counter-clockwise (CCW) rotation, output of the sensing light always alternate between H and L, so we can not get the direction of rotation.

数据中心网络智能运维的带内遥测技术

Technology Analysis技术分析DCW135数字通信世界2021.090 引言随着数字化转型企业对云计算基础架构依赖程度的提高，融合了大数据和人工智能最新发展的智能运维（AIOps ）逐渐成为提高基础架构服务质量的关键[1]。

Gartner 在AIOps 的研究报告[2]中指出，AIOps 平台应由监测（Observe ）、处理（Engage ）和行动（Act ）三个部分结合大数据和机器学习组成一个闭环结构，而监测是触发整个闭环反馈的基础和关键，没有高质量的监测，就缺乏人工智能所需的大数据基础，因而也无法形成智能化的处理和相应的主动运维行为。

但在性能飞速提升的数据中心，数据平面监测是一直以来的难点。

本文将探讨在高速网络环境中进行数据平面监测的方法和发展趋势，为智能运维系统的建设提供参考。

1 传统方法的问题长期以来监测数据中心网络采用的也是传统网络常见的周期轮询、周期探测、事件触发异常告警或事件触发主动探测等手段，其共同特点是采用从一个网管中心出发主动向被管节点拉取（Pull ）数据的模式，能够以最低开销和可控数据规模收集一个管理模型所需的基本数据，SNMP （简单网络管理协议）网管、Syslog 、Ping 、Traceroute 、SLA 探针以及流量镜像分析工具等本质上都属于此类数据收集方式。

其开销低、使用广泛，但缺点是不能展示业务流量的全貌，在轮询周期内或是探测包发送的间隙，都是数据收集的盲点；其次以CPU 运行软件的方式，也无法在高速数据平面中更密集和更多维度的提供测量，导致在大型云数据中心内普遍出现的闪断丢包、流量微突发、延迟抖动等网络异常无法被侦测，累积形成的故障无法预警和溯源，这都对追求极致体验的数字化转型类业务构成了较大的威胁。

2 新兴的带内遥测技术更适合大数据平台的数据采集方式不能以某个数据采集点为中心构建，而应当充分利用大规模分布式处理的思维，把从被管节点被动收集的Pull 模式转变为被管节点主动向收集器推送（Push ）数据的模式。

人工智能英文参考文献(最新120个)

人工智能是一门新兴的具有挑战力的学科。

自人工智能诞生以来,发展迅速,产生了许多分支。

诸如强化学习、模拟环境、智能硬件、机器学习等。

但是,在当前人工智能技术迅猛发展,为人们的生活带来许多便利。

下面是搜索整理的人工智能英文参考文献的分享，供大家借鉴参考。

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Advanced Functional Materials,2020,30(18).[25]Dinesh Visva Gunasekeran,Tien Yin Wong. Artificial Intelligence in Ophthalmology in 2020: A Technology on the Cusp for Translation and Implementation[J]. Asia-Pacific Journal of Ophthalmology,2020,9(2).[26]Fu-Neng Jiang,Li-Jun Dai,Yong-Ding Wu,Sheng-Bang Yang,Yu-Xiang Liang,Xin Zhang,Cui-Yun Zou,Ren-Qiang He,Xiao-Ming Xu,Wei-De Zhong. The study of multiple diagnosis models of human prostate cancer based on Taylor database by artificial neural networks[J]. Journal of the Chinese Medical Association,2020,83(5).[27]Matheus Calil Faleiros,Marcello Henrique Nogueira-Barbosa,Vitor Faeda Dalto,JoséRaniery Ferreira Júnior,Ariane Priscilla Magalh?es Tenório,Rodrigo Luppino-Assad,Paulo Louzada-Junior,Rangaraj Mandayam Rangayyan,Paulo Mazzoncini de Azevedo-Marques. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging[J]. 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英翻汉论文资料

通过以优先权为基础的模糊特性使机器人导航于非常杂乱的环境中摘要：自主地面车辆(自导车辆系统)在应用程序的一个关键挑战是导航在密集杂乱的环境障碍。

在配置其事先不知道的的障碍时机器人的任务变得更加复杂。

这类系统最流行的控制方法是基于精确整合一对机器人传感器信息来反应区域的导航方案。

由于环境的不确定性, 已经提出了模糊的行为系统。

在应用基于模糊控制反应行为的导航控制系统中最困难的问题是,判断或融合个人的反应行为,解决这一问题使用到了优先逻辑。

本文使用多值逻辑框架从而提出了用个性化设计的模糊行为系统控制自动车辆的导航。

仿真和实验结果显示,该方法能够让机器人顺利和有效地导航并穿过杂乱环境，例如茂密的森林。

实验比较了向量场直方图方法(VFH)，证明了该方法即使对于长路径的目标一般也会分析的平滑。

1、介绍安全操纵自主地面车辆(自导车辆系统)在无序复杂的环境、密集杂乱的障碍中行驶，对于自动车辆目标导向应用程序而言仍然是一个重大的挑战。

导航是一个多目标控制问题，旨在确保机器人不仅在不碰到障碍物的前提下到达目标，但也要以确保稳定安全的速度行驶。

问题是特别困难的，因为一些导航目标可能会与另一个相反。

导航控制算法在杂乱的环境下不会太复杂是很重要的，因为这将导致一个迟缓反应。

已经承认传统平面感觉模板行为方法在这样的环境不是有效的，相反，精确整合两传感器信息来控制行动的当地导航策略定会让机器人成功完成其使命。

复杂性控制是通过将导航控制问题分解成可以独立并行控制的更简单和定义明确的子问题来克服。

这些子问题及其控制器被称为反应执行者，这种方法来自运动机器人技术。

这种技术吸引了许多机器人专家的兴趣，甚至被用于工业过程控制的应用程序。

自从它被引入运动机器人后迅速推广，导致用可以处理机器人的不确定性信息的模糊逻辑控制器反应的模糊行为方法的发展。

模糊逻辑还允许控制变量的连续性如航向角和速度的考虑，而不是最新行为所用的离散的数字。

此外，它允许程序使用一个设计师自然思维方式的算法学术语言来编写导航算法。

基于脑电和肌电信号的下肢运动意图识别方法

RESEARCH WORK引言据相关统计，我国老龄化现象极为严峻[1]，同时下肢受到意外伤害的状况也不容乐观，这类人群的下肢生理功能会逐渐衰退，下肢的正常功能受损。

近年来兴起的通过穿戴下肢外骨骼机器人来进行康复助行的方式具有良好的前景，随着神经电信号如脑电图、肌电图等采集检测技术的高速发展，为下肢外骨骼机器人提供了新的控制策略[2]。

人体运动是由大脑产生意志、经脊髓层产生运动相应的模式和反射神经精细化控制的过程[3]。

和物理传感器采集的信号相比，生物电信号能够更及时、主动地反馈穿戴者的运动意图。

人体在进行下肢运动时，是由以大脑为中枢神经系统的中央模式生成器产生运动开始意图，控制下肢骨骼和肌肉执行相应的动作。

通过脑电采集装置，从大脑皮层采集的脑电信号（Electroencephalogram，EEG）直接反映了人体运动的意图决策，脑电信号控制具有初始、全局性的特点但由于大脑控制身体的绝大多数任务活动，从中提取单独动作指令非基于脑电和肌电信号的下肢运动意图识别方法郑长坤，王海贤，顾凌云，张弛，汪丰东南大学生物科学与医学工程学院，江苏南京 210096[摘要] 目的提取EEG的小波特征和EMG的时域、频域、时频域以及样本熵等多种特征进行分析，对人体下肢运动识别进行研究。

方法采集人体站立、行走、上楼梯、下楼梯、上坡和下坡6种下肢运动模式的脑电、肌电信号，并对信号进行预处理、特征提取和模式识别，解析人体下肢运动的意图和具体的下肢运动类型。

结果从时域、频域、时频域和时序复杂度等维度上提取的信号特征能够较好的表征信号；基于支持向量机的脑电信号分类方法对下肢有无运动意图的平均识别率达到93.2%；基于极端梯度提升的肌电信号分类方法对下肢六种运动模式的平均识别率达到93.6%。

结论本文提出的方法能够有效的对人体下肢运动进行识别，准确地识别到人体下肢运动意图，可以为下肢外骨骼机器人提供精准安全的控制策略，提高下肢外骨骼机器人助行助力的效率。

基于ARM9的分散式数据采集系统的研究

ｒｑｉｅｎｔｆｇｎｒｌｉｄｓｒａｅｄｓｅｕｒｍｅｓｏｅｅａｎｕｔｉｌｆｌ．ｉ
Ｋｅｗｏｄｓ：ＤａａａｑｉｉｉｎＤａａｐｒｃｓｉｇＡＲＭ９Ｅｍｂｄｄｓ ห้องสมุดไป่ตู้ｅｙｒｔｃｕｓｔｏｔｏｅｓｎｅｄｅｙｔｍＬｎｘｉｕ
ＰＣ（ｒｇａａｌｏｉｃｎｒｌｒ、Ｓ（ｉｒｕＬｐｏｒｍｍｂｅｌｇｃｏｔｌ）ＤＣｄｓｉ — ｏｅｔｂ
即采用模块化的设计结构，设计了一个智能化的采集
系统。系统主要的设计思路是：业现场中需要测量工
态的准确采集显得尤为重要，这是对设备状态进行分析和预测的前提。目前，据采集系统要求能够适应数较为恶劣的工业现场环境，且可测量多种信号和具有较高的测量精度；同时，数据采集设备要求具有智能化测量前端并且能够分散在工业现场就地安装。
曦纠艳日ｇ相晔方
（北工业大学电气与自动化学院，河天津３０３）０１０
摘
要：针对传统数据采集系统采集精度与数据处理能力的不足，结合当前广泛应用的嵌入式系统技术和总线技术，于ＡＭ基Ｒ９处
理器￥Ｃ４０设计了一种分散式数据采集系统。底层数据采集系统采用了模块化的设计结构，３２４各模块采用统一的总线把数据传送给主控器；最后系统利用ＡＭＲ９强大的数据处理能力对所有数据进行分析、处理。实际试验证明，系统数据处理速度快、该控制精度高，可满足一般工业现场的要求。关键词：数据采集数据处理ＡＭ嵌入式系统Ｒ９

stability of networked control systems

lay) that occurs while exchanging data among devices connected to the shared medium. This delay, either constant (up to jitter) or time varying, can degrade the performance of control systems designed without considering the delay and can even destabilize the system. Next, the network can be viewed as a web of unreliable transmission paths. Some packets not only suffer transmission delay but, even worse, can be lost during transmission. Thus, how such packet
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February 2001
©2000 Image 100 Ltd.
dropouts affect the performance of an NCS is an issue that must be considered. Another issue is that plant Physical Plant outputs may be transmitted using multiple network packets (so-called multiple-packet transmission), due to Sensor 1 ... Sensor n Actuator 1 ... Actuator m the bandwidth and packet size constraints of the network. Because of the arbitration of the network medium with other nodes on the network, chances are Other Control Network Other that all/part/none of the packets could arrive by the Processes Processes time of control calculation. Controller The implementation of distributed control can be traced back at least to the early 1970s when Figure 1. A typical NCS setup and information flows. Honeywell’s Distributed Control System (DCS) was introduced. Control modules in a DCS are loosely connected because most of the real-time control tasks (sensing, sion as asynchronous dynamical systems (ADSs) [11] and calculation, and actuation) are carried out within individual analyze their stability. Finally, we present our conclusions. modules. Only on/off signals, monitoring information, alarm information, and the like are transmitted on the serial net- Review of Previous Work work. Today, with help from ASIC chip design and significant Halevi and Ray [1] consider a continuous-time plant and disprice drops in silicon, sensors and actuators can be crete-time controller and analyze the integrated communicaequipped with a network interface and thus can become in- tion and control system (ICCS) using a discrete-time dependent nodes on a real-time control network. Hence, in approach. They study a clock-driven controller with mis-synNCSs, real-time sensing and control data are transmitted on chronization between plant and controller. The system is repthe network, and network nodes need to work closely to- resented by an augmented state vector that consists of past values of the plant input and output, in addition to the curgether to perform control tasks. Current candidate networks for NCS implementations rent state vectors of the plant and controller. This results in a are DeviceNet [5], Ethernet [6], and FireWire [7], to name a finite-dimensional, time-varying discrete-time model. They few. Each network has its own protocols that are designed also take message rejection and vacant sampling into account. Nilsson [2] also analyzes NCSs in the discrete-time dofor a specific range of applications. Also, the behavior of an main. He further models the network delays as constant, inNCS largely depends on the performance parameters of the dependently random, and random but governed by an underlying network, which include transmission rate, meunderlying Markov chain. From there, he solves the LQG opdium access protocol, packet length, and so on. timal control problem for the various delay models. He also There are two main approaches for accommodating all of points out the importance of time-stamping messages, these issues in NCS design. One way is to design the control which allows the history of the system to be known. system without regard to the packet delay and loss but design In Walsh et al. [3], the authors consider a continuous a communication protocol that minimizes the likelihood of plant and a continuous controller. The control network, these events. For example, various congestion control and shared by other nodes, is only inserted between the sensor avoidance algorithms have been proposed [8], [9] to gain nodes and the controller. They introduce the notion of maxibetter performance when the network traffic is above the limit mum allowable transfer interval (MATI), denoted by τ, that the network can handle. The other approach is to treat the which supposes that successive sensor messages are sepanetwork protocol and traffic as given conditions and design rated by at most τ seconds. Their goal is to find that value of control strategies that explicitly take the above-mentioned isτ for which the desired performance (e.g., stability) of an sues into account. To handle delay, one might formulate conNCS is guaranteed to be preserved. trol strategies based on the study of delay-differential It is assumed that the nonnetworked feedback system equations [10]. Here, we discuss analysis and design strategies for both network-induced delay and packet loss. T &( t ) = A11 x ( t ), x ( t ) = [x p ( t ), x c ( t )] x This article is organized as follows. First, we review some previous work on NCSs and offer some improvements. Then, we summarize the fundamental issues in NCSs and ex- (where x p and x c represent the plant and controller state) is amine them with different underlying network-scheduling globally exponentially stable. Thus, there exists a P such that protocols. We present NCS models with network-induced delay and analyze their stability using stability regions and a (1) AT 11 P + PA11 = − I . hybrid systems technique. Following that, we discuss methods to compensate network-induced delay and present ex- Next, it is assumed that the network’s effects can be comperimental results over a physical network. Then, we model puted by the error, e(t), between the plant output and conNCSs with packet dropout and multiple-packet transmis- troller input. So the networked system’s state vector is

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CE150COMPUTERINTERFACING,SEPTEMBER20011ADistributed,ExtensibleandAccessibleSensoryControlandDataAcquisitionSystem

L.Bernardo,A.CarandangJr.,T.G.Castillo,A.Lee,W.F.TupazJr.andW.S.YuAbstract—TheSensoryControlandDataAcquisition-To-talEnvironmentManagementSystem(SCADA-TEMS)isadistributedmulti-accesscomputercontrolleddataacquisi-tionandcontrolsystem.Thesystemiscomposedofmul-tiplesensoryandcontrolmodulesthatperformtasksrang-ingfromcontrollingremoteequipmenttocollecting,multi-plexingandmanipulatingdata.TheSCADA-TEMSmaincontrolmoduleperformsthenecessarybuﬀering,latchingandmultiplexingofthemultipleinputandoutputhard-waremodulesconnectedtothesystem.ThismoduleisinturninterfacedtotheSCADA-TEMSserver.Theteamde-velopedaFTP-likeTCP/IPprotocolcalledSimpleAccessandControlProtocol(SACP)inwhichtheSCADA-TEMSservercanbeaccessedusingaPHPweb-basedinterface,JavaSwingGUIclientinterface,SMS-to-SACPgatewayorrawsocketconnectiontoport6543.MultipleSCADA-TEMSserverscanbecontrolledbyacentralSACPclienttoprovidedistributedaccess.NewmodulescanbeutilizedbyattachingthemtotheSCADA-TEMSmaincontrolmod-uleandloadingtheappropriatesharedobject.TheseandotherfeaturesallowtheSCADA-TEMStobecomeacriti-caltoolinprovidingacompleteenvironmentalmanagementsolution.

Keywords—SensoryControlandDataAcquisition,Com-puterInterfacing

I.IntroductionInthismodernworld,therehasbeenadrasticincreaseinconnectivity.Itisnowpossibletokeepintouchwithpeo-plearoundtheworldviaglobalroamingmobile/telephonenetworksorviasatellite-basedcommunicationsnetworks.Itisevenpossibletotransactbusiness,makepurchasesandsurfthewebonacellularphone.Itispossibletopurchaseeverythingfrombooks,clothesandotheritemsonthevastoceanoftheInternet.AttheheartofthisdigitalrevolutionisconvergencetotheInternetProtocol(IP).DistributedSystemsinvolatileorremoteenvironmentsarecostlyanddiﬃculttomaintain.Inenvironmentssuchaspowerplants,factoriesandothersimilarfacilities,theywouldhavetodeployalargenumberofsensorydevicestomonitorthestatusoftheentiresystem.Inresearchandde-velopmentfacilities,itwouldbeatedious,costlyandevendangerousendeavortoperformallthemonitoringmanu-ally.Physicalharmcanbebroughtupontheresearchersandoperatorsinthesehazardousenvironments.Inordertoreducemanpowercosts,improvesafetyconditionsandprovidejustintimemonitoringandresponse,SensoryCon-trolAndDataAcquisition(SCADA)systemshavebeendeployed[1].WithallthisadvancesinInformationandCommuni-cationTechnologyandtheSCADAtechnology,wenowhavethenecessarytoolstoprovideacomplete,distributed

DepartmentofElectronics,ComputerandCommunicationsEngi-neering,AteneodeManilaUniversity

andmulti-accesscomputercontrolleddataacquisitionandcontrolsystem.ThiswecalltheSensoryControlandDataAcquisition-TotalEnvironmentManagementSys-tem(SCADA-TEMS).

II.SCADASensoryControlandDataAcquisition(SCADA)systemsisacomputersystemforgatheringandanalyzingrealtimedata.SCADAsystemswereﬁrstusedinthe1960sforelectricaldistributionsystems[2].SCADAsystemsincludehardwareandsoftwarecomponents.ThehardwaregathersandfeedsdataintoacomputersystemthathasSCADAsoftwareinstalled.Thecomputerthenprocessesthisdataandpresentsitinatimelymanner.SCADAwarnswhenconditionsbecomehazardousbysoundingalarms,warningthemaintainersanddoingthenecessaryautoreconﬁgura-tion.AnySCADAsystemmusthaveanumberofbasicele-ments[3].Theseelementsare:󰀁Communicationlinks-beinganetworkdaemontheSCADA-TEMSserverisabletoallowalargenumberofconnectivitymeans.However,thebasicinterfacetothesystemwouldbeanIPnetwork.󰀁Controlfunctions-thesefunctionsareimplementedbyloadablemodules.Eachloadablemodulewillcontainmethodsforaccessingandconﬁguringacorrespondinghardwaredevice.󰀁Dataacquisitionfunctions-similartotheControlfunc-tions.󰀁Historicalarchivingfunctions-sincetheSCADA-TEMSisrunningasaUnixdaemondebuggingandlogginginfor-mationiswrittentotheUnixsyslogserver.SCADAsystemsareusedtomonitorandcontrolaplantorequipmentinindustriessuchastelecommunications,wa-terandwastecontrol,energy,oilandgasreﬁningandtrans-portation.TheprojectaimstobuildaminiaturemodelSCADAsystem.

III.SCADA-TEMSTheSensoryControlandDataAcquisition-TotalEnvi-ronmentManagementSystem(SCADA-TEMS)isacom-prehensivesoftwareandhardwaresolutionforinterfacingdataacquisitionandcontroldevices.Thesystemalsopro-videsaccesstothesedevicesviatheSimpleAccessandControlProtocol(SACP).ThisprotocolistoserverasapresentationlayerprotocolforaccessingtheSCADA-TEMSServer.Thesystemiscomposedofanumberofbasicelements:󰀁SCADA-TEMSServer-providesaccesstotheentiresys-temviaSACP.TheSACPisasimpleFTP[4]-likeproto-