wncsbed: a wsan based testbed for networked control systems
TRANSCRIPT
Computer Standards & Interfaces 36 (2014) 585–591
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Computer Standards & Interfaces
j ourna l homepage: www.e lsev ie r .com/ locate /cs i
WNCSbed: A WSAN Based Testbed for Networked Control Systems
Faruk Aktaş a,⁎, Celal Çeken b, Kadir Erkan c
a Networked Control Systems Laboratory, Kocaeli University, Kocaeli, Turkiyeb Computer Engineering Department, Sakarya University, Sakarya, Turkiyec Dijital Tanima Sistemleri, Istanbul Technocity, Istanbul University, İstanbul, Turkiye
⁎ Corresponding author.E-mail addresses: [email protected], ncs@koca
[email protected] (C. Çeken), [email protected] (K
0920-5489/$ – see front matter © 2013 Elsevier B.V. All rihttp://dx.doi.org/10.1016/j.csi.2013.10.005
a b s t r a c t
a r t i c l e i n f oArticle history:Received 15 June 2012Received in revised form 13 September 2013Accepted 15 October 2013Available online 24 October 2013
Keywords:TestbedWireless Sensor and Actuator NetworksNetworked Control Systems
In this study, a new testbed which has a WSAN structure and is utilized for monitoring and controlling of indus-trial systems is designed and implemented. In order to investigate the performance of the testbed developed, afirst order plus dead time process control system is testedusing both of on-offwith hysteresis and PID algorithms,respectively. In the light of the discussion given through the study, it can easily be deduced that, experiments re-lated to monitoring and controlling of industrial systems can be realized by the testbed, easily, and lots of timecan be saved from creating an experimental environment.
© 2013 Elsevier B.V. All rights reserved.
1. Introduction
In the last decade, rapid progress in embedded data processingand wireless communications has given rise to use these technolo-gies in control engineering. In a traditional Wireless Sensor Network(WSN) system, sensing nodes (SNs) get the data measured from thevicinity and transmit it to a central processing node throughwirelessmedium. SNs in the network are small in size and have local process-ing and wireless transmission abilities. Nowadays, WSNs are de-ployed in plenty of areas since they are flexible, have low cost andself organizing capability. They are commonly deployed in industrial,medical, military, and environmental areas for especially monitoringand tracking purposes [1]. As well as their prominent deploymentoptions, nowadays, they can also be employed in the field ofnetworked control systems in order for industrial systems to be con-trolled over wireless medium. This new approach is referred asWireless Sensor and Actuator Network (WSAN).
There are a few standardization bodies commonly used in WSNcommunications. Some of them are given below in brief.
1.1. ZigBee
ZigBee is based on an IEEE 802.15 standard and is a specificationfor a suite of high level communication protocols used to createwireless personal area networks. Low powered devices using ZigBeeprotocol stack are capable of creating mesh network that allows longdistance communications with low power. ZigBee can operate in
eli.edu.tr (F. Aktaş),. Erkan).
ghts reserved.
868 MHz (Europe), 915 MHz (USA and Australia) and 2.4 GHz(worldwide) ISM bands. Data rates may vary from 20 Kbps in thelower ISMbandsmentioned above to 900Kbps in the 2.4GHz frequencyband [2]. In this study, WSAN part of the testbed introduced employsZigBee protocol suit.
1.2. WirelessHART
It is another wireless sensor networking technology basedon the Highway Addressable Remote Transducer Protocol (HART).WirelessHART utilizes mesh architecture, operates in the2.4 GHz ISM band using IEEE 802.15.4 standard radios and wasdefined for the requirements of process field device networks[3].
1.3. ZigBee IP
It aims at providing seamless Internet connections in order tomonitor and control low-power, low-cost devices. ZigBee IP wasemerged to support the forthcoming ZigBee Smart Energy version 2standard [4].
1.4. 6LoWPAN
IPv6 over Low power Wireless Personal Area Networks is thename of a working group in the Internet area of the IETF and suggeststhat low-power devices with limited processing capabilities shouldbe able to connect to the Internet. Encapsulation and header com-pression mechanisms defined through this standard allow IPv6packets to be sent to and received from over IEEE 802.15.4 based net-works [5].
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The goal of this study is to design and implement a WSAN basedtestbed, called WNCSbed (testbed for Wireless Networked ControlSystems), in order for industrial systems to be controlled over wirelessmedium. The study also includes experiments related to control of afirst order plus dead time system (process control trainer) using bothof on–off with hysteresis and PID methods, so that the performance ofthe testbed can be validated. In the case studies, the proposed system,initially, gets the reference value, i.e. desired temperature value, fromthe user as an input by a user interface running on the PC. This valueis then forwarded to the MDA 320 data acquisition board (DAQ) bymeans of XServe software and MIB520 access point, respectively, overthe wirelessmedium using ZigBee protocol stack. After it gets the refer-ence temperature, MDA 320 delivers this information to the microcon-troller using I2C interface. Reference temperature and the temperaturemeasured from the process control trainer are then incorporated intothe control algorithms, i.e. on–off with hysteresis and PID, running onthe microcontroller in order to generate an output controlling signalthat puts the system into desired state. The contributions of this studycan be summarized as follows:
• A new testbed, i.e. WNCSbed, has been designed and implementedusing WSANs in order to monitor and control industrial systemsthrough wireless medium.
• WNCSbed can be employed in any application related to themonitor-ing and controlling of industrial systems, provided that the user inter-face and control algorithm are modified according to the applicationrequirements.
• Experiments on monitoring and controlling of industrial systemscan easily be realized by means of the testbed developed, whichimplies that lots of time can be saved from creating an experimen-tal environment.
• In order to manage system control functions, MD320 DAQ has beenintegrated with a microcontroller through I2C interface.
The remainder of the paper is organized as follows. In the next sec-tion, a brief literature search is given related to the study. Section 3 pre-sents general information about theWSANs. Overall properties and thecomponents of the testbed developed are presented in Section 4. Designstages of the testbed together with related algorithms are describedcomprehensively in Section 5. Section 5 also includes example WSANexperiments each using individual control algorithms. The paper is con-cluded with the last section providing summary about the study withfinal remarks.
2. Related works
Although the WSAN concept is relatively new, plenty of relatedstudies can be found in the literature. Some of them are summarizedin this section. In [1], authors present WSN concept and the factorsthat affect WSN design. It is a survey study on WSN. Authors of [6]design a smart sensing system in order to monitor scientific datafrom the active volcano, Mt. St. Helens. In the study, MDA320 DAQis employed for only monitoring purpose, however, we used it forboth monitoring and controlling of industrial systems in our study.A testbed that allows for realizing experiments in heterogeneousWSN is designed in [7]. By the testbed developed, users are able tocustomize their applications for specific SNs and experiments locallywith remote hardware resource. Article [8] presents a model basedpredictive control over WSAN. The validation of the approach isalso realized using a testbed in the study. In article [9], an autono-mous light control system based on the feedback from light sensorscarried by users is proposed. The control system developed concen-trates on providing users' preferences and energy efficiency. Wholeand local lighting devices are considered in the study. The design istested by using simulations and experiments. The proposed systemin [10] monitors water quality in restricted marine environments.Contrast to our study, MDA320 DAQ is employed for only monitoring
purposes. The authors in [11] design and implement a WSAN systemfor robotics in indoor environments. They investigate the localiza-tion accuracy and the navigation accuracy metrics experimentallyin the study. In article [12], an interface system is developed forWSN monitoring and controlling purposes. The authors of article[13] develop and deploy WSN for Precision Agriculture and examinethe impacts of WSN technology in agricultural environment. In con-trast to our study, MDA320 DAQ is deployed here just to providemonitoring functions. A new simulation model of WirelessHARTwritten in OMNET++ is developed and comparative performanceevaluation is presented in [14]. In [15], behavior of the fire in a spe-cific area and the reaction time of WSAN to the fire are simulatedusing Ptolemy environment. Article [16] introduces a testbed for de-signing and experimenting with WSAN based Ambient Intelligenceapplications, whose goal is energy saving. In [17], authors investigatethe design of WSAN systems for control applications with desiredQoS guarantee. They present a generic application level designmeth-odology that is independent of computation and communicationplatforms.
Article [18] introduces the current status of a WSAN testbedSANDbed which is still in development state (to the best knowledgeof us, there is no publication related to the completed version of thisstudy). When the study is completed, following goals are intendedto be achieved: i) Side effect free monitoring, which impliesobtaining sensed data as precise as possible. ii) Easy deploymentand management of WSAN experiments through a web based userinterface. iii) In order to optimize energy efficiency and accordinglyprolong the network lifetime, providing distributed energy mea-surement. Our study differs from [18] in terms of following aspects:i) WNCSbed, is a completed testbed with all hardware and softwarecomponents. ii) Other contributions of our study are summarized inthe paragraph just before the last paragraph of the Introductionsection.
3. Wireless Sensor and Actuator Network architecture
Although theWSNs have beenwidely used for especiallymonitoringand tracking purposes, together with the last technological develop-ments, they are recently deployed in industrial control applications aswell. This new trend, as stated before, is named asWSAN. AWSAN sys-tem has the capabilities of monitoring, data processing, and decisionmaking. These network infrastructures are deployed in such applica-tions as battlefieldmonitoring, determination of chemical and biologicalattacks, home and industrial automation, environmental monitoringand tracking, and etc.
For example; in case of a fire, when it is in initial stages, sensorsmay determine the fire place and a controller may get the valvesopened to extinguish it. Similarly, as in our case studies, temperatureof the process control trainer is sensed and compared to the desiredvalue so that a controlling signal can be generated. In WSAN, sensingand actuating actions are handled by SNs and actuator nodes (ANs),respectively.
As can be seen from the Fig. 1a, commonly, a wireless SN is com-posed of four major components, i.e.; a sensing unit, a processingunit, a power unit and a wireless transceiver unit [19]. The sensingunit is in charge of converting measured physical quantities like hu-midity, pressure, temperature, and etc. into a voltage signal and oftransforming this signal to the digital form for further operations.The processing unit manages all of the functions of SN includingcommunication protocols in order to carry out specific tasks. SN is at-tached to the network by transceiver unit. Finally, required energy issupplied to all of the units by the power unit. Additional componentssuch as power generator, location finding system and mobilizer canalso be incorporated into an SN according to requirements of appli-cation implemented.
Fig. 1. General architecture of a) a wireless sensor node b) a wireless actuator node.
Fig. 2. General architecture of a networked control system.
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Fig. 1b outlines a general wireless AN. As it can be seen from the fig-ure a wireless AN, together with the units in SN, commonly has a deci-sion unit for control value computation and an actuation unit thatprovides an interface to the system controlled [19].
SNs commonly have lower cost, lower power, limited sensing andprocessing capacity, and wireless communications ability. On theother hand, ANs have greater processing capacity, battery lifetime andpower ratio. The number of SNs in a WSAN infrastructure may vary inhundreds to thousands according to applications, whereas, it is smallerfor ANs [19].
SN in aWSAN infrastructure is in charge of collecting physical quan-tities from the vicinity. Senseddata then converted to thedigital formbythe ADC in order to be processed. It consequently is delivered to the re-lated node, i.e. another SN, control center, or AN. On the other side, de-cision unit of any AN get the measured data and the reference value,evaluates this inputs by means of the control algorithms included andfinally generates a control output. The obtained value then transformedto the analog signal using aDAC unit so that the controlling signal can beapplied to the system. In some applications, especially related to robot-ics, SN and AN seem to be integrated in order to form a self-containedstructure.
As it is depicted in Fig. 2, all of the nodes and other componentsmaycommunicate with each other over a network structure in order to per-form related operations properly in terms of both cost efficiency andcomplexity [20].
4. Architecture of WNCSbed
The testbed developed consists of several components. Here, in thissection, both hardware infrastructure and software framework ofWNCSbed that is outlined in Fig. 4 will be given. For more detailsabout WNCSbed, please refer to [21].
4.1. Hardware infrastructure
WNCSbed consists of a PC with several software for controlling andmonitoring purposes and a WSAN infrastructure including an accesspoint, an actuator subsystem and a sensing unit. In order to evaluatethe performance of the testbed, a process control trainer system andan interface program are employed as well. Hardware infrastructure
of WNCSbed consists of an MIB520 access point, an MDA320 DAQ anda PIC16F877 microcontroller.
MIB520 access point is a gateway between PC and WSAN. It isconnected to PC over a USB interface and is in charge of providingcommunication between MICA/IRIS sensor/actuator node familiesand Xserve program running on PC. It can be employed in order toprogram sensor/actuator nodes as well.
MDA320 DAQ, another crucial hardware component, has 8 analoginput channels eachwith 8bit resolution, 8 digital input/output channels,3 different stage probes for external sensors and I2C pins. Fig. 3 depictstop view of MDA320 DAQ [22]. In the study, reference value is transmit-ted from PC to the MDA320 DAQ by means of MIB520 over wirelessmedium. The measured value from the system controlled is deliveredto the MIB 520 and accordingly to the PC using MD320 DAQ as well in
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reverse direction. It is also connected to the PICmicrocontroller using I2Cinterface so that decision making function could be carried out. In thetestbed, DATA andCLKpins ofMDA320 are employed to provide connec-tion with microcontroller through I2C interface, and A0 pin is for mea-sured data input.
4.2. Software framework
In the PC part, there are three software running in order to completesensing and controlling processes. XServe can be considered as a gate-way between WSAN and applications running on PC. In WNCSbed,XServe provides services to route data to and from the MIB520 accesspoint, accordingly WSAN. It is able to parse, transform and processdata so that it can be conveyed between WSAN and other applicationsor platforms properly. XServe is capable of offering multiple communi-cation inputs and providing high level services, which are customizableusing XML based configuration files and loadable plug-in modules, forthe users and applications wishing to interact with XServe or themesh network. As users are allowed to interact with XServe through aterminal interface, applications can access the network directly orthrough a powerful XML RPC (Extensible Markup Language-RemoteProcedure Call) command interface. XML RPC is a web service that al-lows application programs to executemethods running on any softwareand hardware platform, remotely.
Perl module running on the PC gets xml packet, which includes thesensed data, from XServe and relay it to the Matlab for monitoringsystem status. Perl module also executes the XServe method related toreference value transmission from PC to the MDA320 DAQ by meansof XML RPC technique. An example XML RPC request that is deliveredto XServe gateway, consecutively, to the MDA320 DAQ is given inFig. 4. This request is responsible for transmitting reference temperaturevalue, input by the user interface running on PC and developed byMatlab, to the MDA 320 DAQ and then to the microcontroller via I2Cinterface.
MIB520 andMDA320 nodes have open source and component basedTinyOS operating system which is developed for especially embeddedsystems. It abstracts the hardware and provides a software develop-ment environment for the application programs which command tothe hardware components for desired operations. Any applicationrunning on TinyOS is built using nesC (network embedded systemsC) language that is a component based and event driven programminglanguage. In the testbed, MIB520 and MDA320 WSAN nodes areprogrammed using nesC.
Fig. 3.MDA 320 data acquisition board
In WNCSbed, all of the WSAN nodes, i.e. MDA320 DAQ andMIB520, deploy ZigBee wirelessmesh network standard so that com-munications over wireless medium can be achieved. It is a low-costand low-power standard, and widely deployed in WSAN applica-tions. While it can operate different aforementioned ISM bands, inour applications, 2.4GHz radio band is preferred. Data rate of ZigBeemay vary from 20 to 900Kbps [2].
5. Experimental study
5.1. General architecture
The bottom line in this study is remote controlling of industrial sys-tems over wireless medium by using WNCSbed, as stated earlier. Inorder to evaluate the performance of WNCSbed, this section includes anexperimental study that is illustrated in Fig. 5. As can be shown fromthe depiction, a first order plus dead time system, i.e. process controltrainer, is attached to the testbed developed. The process control trainerhere is a self-contained process and control device. In this equipment,air temperature through a tube is measured, and this value is comparedto the set point (reference value) in order to generate a controlling sig-nal using various control algorithms. The controlling signal then appliedto the heater grid so that the desired temperature can be reached. Anycontrolling signal can also be applied to the system as an independentinput, externally, which is the case in our study. The detailed informa-tion about the process control trainer can be found in [23].
A Matlab based GUI is also developed in the study, which allowsusers to deliver any reference temperature value towards the processcontrol trainer. Options of this graphical interface may need to bechanged according to the control algorithm incorporated. In the exper-iments realized, on–off control with hysteresis and PID controlmethodsare employed.
In on–off control, control equipment puts the system into “on” or“off” state considering the measured value. The system is in on state ifthe measured value is less than the reference value, otherwise it is inthe off state. The problem with this approach is that, when the systemcomes to the desired value, on and off state transitions occur continu-ously and this may result a harmful impact on the physical components.In order to avoid this event, a hysteresis is imposed to the algorithm.
Since the same control signal is applied to the system all the time re-gardless of the offset value, a continues fluctuation is appeared at thecontroller output and consecutively in the systemoperation state. A bet-ter approach, i.e. PID control, is also employed in order to evaluate the
and PIN configuration (top view).
Fig. 4. An example XML RPC request.
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performance of testbed through the study. In PID control, an error isagain calculated using the set point and measured value. This error isattempted to be minimized using three separate constant parameters,i.e. proportional, integral, and derivative values. The weighted sum ofthese parameters is then used to generate the control signal which ad-justs the system behavior to desired state. The control signal calculatedis given in Eq. (1);
u tð Þ ¼ ke tð Þ þ KiZ
e tð Þdtþ Kdde tð Þdt
ð1Þ
where e(t) is error and K, Ki, and Kd are proportional, integral, andderivative terms, respectively.
A simple state transition diagram of the experimental study and se-quence diagram related with the timing of the processes in the study isgiven in Figs. 6 and 7, respectively.
As can be shown in Figs. 6 and 7, by the user interface implementedin Matlab, the reference temperature is embedded to the XML RPC re-quest and forwarded to the MDA320 DAQ using XServe and subse-quently the access point (MIB520) over wireless medium. The setpoint then delivered fromMDA320 DAQ to themicrocontroller throughI2C bus. The measured temperature value of the system controlled isalso get by the microcontroller after the analog to digital conversionprocess so that the control signal can be generated using the aforemen-tioned control algorithms. In themeanwhile, themeasured temperaturevalue is transmitted to the PC using MDA320 over wireless medium formonitoring purpose. Considering the obtained temperature values, mi-crocontroller calculates a controlling signal using the control algorithmdeployed and sent it to PWM output which is connected to the process
Fig. 5. The block diagram of
control trainer's external control input. The system then adapts itsbehavior according to this input.
5.2. Experimental results and discussion
In order to evaluate the performance of WNCSbed, two differentcontrol applications each has individual control algorithmhave been re-alized through the study, as stated before. In both of the experiments,the user interfaces providing reference temperature input and the pro-cess control trainer controlled, have been the same. The only differencebetween two applications has been the control techniques employed;i.e. on–off with hysteresis and PID control.
In the first application which incorporates on–off control withhysteresis, reference temperature and hysteresis value are chosenas 25 °C and 3 °C, respectively. Graphical results regarding the mea-sured system temperature and the controlling signal produced bythe microcontroller are given in Fig. 8. In the beginning, the referencetemperature 25 °C is sent to the microcontroller using XServe, MIB520and MDA320 DAQ, respectively, as a XML RPC request. Because it is inoff state and the measured temperature value is sufficiently lowerthan the reference temperature, i.e.; reference-hysteresis/2 = 23.5 °C,the process control trainer starts to operate. When the measuredtemperature value starts to be greater than reference + hysteresis/2= 26.5, the controller generates an output signal that informs theprocess control trainer switching to off state again. These events/actionsare repeated until the end of the experiment, as can be shown in Fig. 8.
In the second application in which PID algorithm is incorporated,28 °C is chosen as the reference temperature. This value is transmittedfrom PC to the microcontroller over wireless medium, similarly. Inorder to operate the process control trainer consistently, values of
the experimental study.
Fig. 6. State transition diagram of the experimental study.
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termsKp, Ki, andKd,whichwere determined experimentally,were cho-sen as 1, 0.001, and 0.1, respectively. Fig. 9 shows themeasured temper-ature value of the system controlled.
As can be seen from Fig. 8 the temperature of the system arrived tothe desired level rapidly (settling time is 200 ms, and rise time is100ms), and the range offluctuations is less than those of on–off controlwith hysteresis algorithm, as a consequence of PID control techniqueemployed.
The results show that the WSNs can also be utilized efficiently forcontrolling purpose in addition to its common applications, i.e. moni-toring and tracking. In the light of the discussions given above, onecan easily deduce that the testbed can be employed in controlling andmonitoring applications of any industrial system, provided that theuser interface and control algorithm are modified according to the ap-plication requirements. It is also clear that, by the testbed developed,one can easily realize experiments on monitoring and controlling of
Fig. 7. Sequence diagram of
industrial systems remotely and can save lots of time from creating anexperimental environment.
6. Conclusions
In this study, a newWSAN based testbed, also called WNCSbed, isproposed in order for industrial systems to be monitored and to becontrolled. Process control trainer which is a first order plus deadtime system is monitored and controlled using both of on–off controlwith hysteresis and PID control algorithms experimentally, so thatthe performance of WNCSbed can be evaluated. The results revealthat WNCSbed can be employed in the applications related to con-trolling and monitoring of any industrial system, provided that theuser interface and control algorithm are modified according to theapplication requirements. It can also be concluded that experimentson controlling of industrial systems can be easily realized over the
the experimental study.
Fig. 8. On–off control of the system with hysteresis.
Fig. 9. PID control.
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testbed developed and lots of time can be saved from creating an ex-perimental environment.
Acknowledgment
The authors would like to thank the members of NCS group inKocaeli University for their valuable contributions.
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Faruk Aktaş received his B.S. and M.S. degrees in Electronicand Computer Education from Kocaeli University, Turkey,in 2008 and 2012, respectively. He is currently pursuing hisPh.D. degree in biomedical engineering at the Kocaeli Uni-versity. His active researches are wireless sensor networks,wireless sensor/actuator networks, control systems, wirelessnetworked control systems, microcontrollers and wirelesscommunication.
Celal Çeken received his Ph.D. degree in 2004 from KocaeliUniversity, Kocaeli, Turkey. Since 1999 he has been withthe Electronics and Computer Education Department of theKocaeli University. He is interested in many fields such aswireless communications, computer networks, web basedprogramming and database systems. His current research in-terests include wireless MAC protocols, high speed wirelesscommunication protocols, next generation wireless systems,cognitive radio, wireless sensor and actuator networks andwireless networked control systems.
Kadir Erkan received the M.Sc. and Ph.D. degrees from Uni-versity of Marmara, Turkey in 1989 and 1994, respectively.His active research interests include networked control sys-tems, artificial intelligence, intelligent control, and expertsystems.