Control System Software Design Methodology forAutomotive Industry

Giovanni Di Orio, Jose BarataCTS – UNINOVA, Dep. de Eng. Electrotecnica, FCT

Universidade Nova de Lisboa2829-516 Caparica, Portugal{gido, jab}@uninova.pt

Carlos Sousa, Luis FloresINTROSYS, SA – Global Control System Designers

2860 Moita, Pourtugal{carlos.sousa, luis.flores}@introsys.eu

Abstract—As automated manufacturing systems become moreand more complex, the need for new methodologies to improvethe design and development of industrial monitoring and controlsolutions is becoming peremptory. Programmable Logic Con-trollers (PLCs) dominates the application domain meaning thatthey are established as the most popular industrial controllersused in factory and shop floor. Although the capabilities of thesecontrollers have strongly improved in the last decades, theirhistorical background as the easy understand by the electricianswho had previously worked on electrical systems has meant thatthe de-facto standard for the implementation of control andmonitoring solution for these devices remains the ladder logic.However, to face the globalization challenges, the manufacturingcompanies needs to improve their productivity by reducing thecosts, delivering high-quality of products with high variety andimproving their responsiveness to changing market condition.Moreover productivity gains can also be achieved by reducingthe life-cycle costs of manufacturing production systems implyingthe using of more flexible and agile approaches. In this scenario,the proposed methodology aims to provide a homogeneous andoptimum process that, starting from a set of mechanical specifica-tions and behavioural models of machines, enable the generationof industrial logic automatically ensuring the same structure andnaming standard in every project and the quality of the code.

Index Terms—Behavioural Modelling, Design Methodology,Programmable Logic Controller, IEC-61131-3, Automotive Indus-try

I. INTRODUCTION

The increasing demand and competition in the automotivemanufacturing market are radically changing the productionsystem design and manufacturing in terms of flexibility, life-cycle cost, customization of products and time to market [1].

Due to the competition for key markets share, the OriginalEquipment Manufacturers (OEMs) are engaged in an inno-vation race [2] to implement more and more exclusive andefficient production systems able to produce as many differ-ent product variations as quickly as possible [3]. Therefore,manufacturing companies are striving to introduce flexiblemanufacturing techniques in order to better meet market needswhilst maintaining the low cost base of heavily automatedmass production techniques [4]. In this context, the key tocompetitiveness is the ability to have systems able to quicklyrespond to markets variations and demands for new and inno-vative products which means frequently changes in productsthat in turn cause changes in the plant’s hardware structure

and functionality. As existing plants cannot be rebuild dueto high investment volumes, the changes in hardware compo-nents affect particularly the software: it has to be modifiedcontinuously and its amount and complexity increases [5].Furthermore, the manufacturing systems of today are complexand heterogeneous in terms of hardware and software sincethey are characterized by a lot of different devices, such as sen-sors, actuators, etc., interconnected across multiple controllersand communicating with each other by means communica-tions networks in order to accomplish the given automationtasks. At the same time, the presence of industrial proprietarystandards, encompassing electrical systems and diagnostic aswell as PLC types and software structure, means that eachmanufacturer have its own exclusive production and controlsolution, developed considering a set of mechanical, electricaland electronics proprietary rules and software philosophies.These aspects together highlight that every change in the shopfloor environment has heavy consequences on the productionsince brings the production system from the normal productionstate to a new one that is the system reengineering statecharacterized by zero-production, where the system is shut-down for reprogramming task to face of the process of change.The time needed for this task depends strictly by the dimensionof changes, presence of a well-suited documentation, particularstandard familiarity and last software version [6]. Moreover,the programming task represents an error-prone activity sincecould introduce new possible errors in the system that mightaffect the way the system will operate. The design and de-velopment of methods and tools to eliminate or reduce time,costs and errors related to shop floor reengineering as much aspossible would offer a competitive advantage to contemporarymanufacturing companies.

The paper proposes a new methodology for modelling andprogramming manufacturing control systems. The method-ology is intended to improve shop floor agility and globalcompetitiveness of companies, providing a homogeneous andoptimum process that, starting from a set of mechanicalspecifications and behavioural models of machines, enables thegeneration of reliable industrial Ladder Logic Diagram (LLD)automatically ensuring the same structure and naming standardin every project and the quality of the code.

The reminder of this paper is organized as follows: sec-

tion II presents a review on common practices for PLCsoftware development in industry. Section III focuses on theproposed methodology. Section IV provides a brief descriptionof the demostrator used for applying the proposed method-ology. Finally, section V presents the conclusions and futurework.

II. A REVIEW ON PRACTICES FOR PLC SOFTWAREDEVELOPMENT IN INDUSTRY

In its root the effectiveness and efficiency of monitoring andcontrol programs relates with the methodology used to imple-ment them. Actually tools and methodologies used to developsuch systems, do not possess enough level of representationmaking the design and development process a very painfulactivity in terms of time and costs. Moreover, the challengesimposed by globalization ask for more evolvable and high levelcontrol systems underlining the need for new methodologiesthat are able to move high level software engineering tech-niques to the automation world in order to have solutions notso much bit-oriented and based on scan paradigm. Anotherimportant limitation is the lack of a neutral representationfor programs, i.e. current program representations depend onthe type of used PLC as well as on the end-user implyingthat the same process can be designed and implemented incompletely different ways. Worse than that, the same processin the same PLC is designed and developed in differentway according to the particular manufacturing company, inautomotive industry this problem is amplified by the presenceof hardware and software standard. To really understand theinnovative role played by the proposed methodology in designand development of monitoring and control programs, existingapproaches are discussed.

A. Current Design Methodologies

The design methodologies are a fundamental issue andunfortunately little work has been done in this direction. Themost significant works describing logic design principles formonitoring and control systems was done in 2003 [7], [8], 2007[9] and 2008 [4], [10], [11]. As stated in [11] there is no defini-tive report on main challenges faced by the users of industrialcontrol and supervision systems, nor is there any publishedmaterial on the tools and techniques and methodologies used inorder to overcame these problems. The Hajarnavis and Young’sworks tries to alert industrial users to different practice and/orapproaches used outside their company, in order to open adiscussion inside the industrial community and the researchcommunity for potential ways for improving usability and flex-ibility of PLC systems. In Lucas’s work the current methodsof creating control logic are observed. Those observations are,then, used to measure the effectiveness of the logic controldesign methodologies enabling the comparison with existingacademic methods. The final result not demonstrates whichdesign method is better but, on the contrary, demonstratesthat a room for improvement exists. Ljungkrantz, in his work,provides a study of logic control programming practices anddescribes a component based approach to develop industrial

logic control programs. Component based approach promisesto shorten development and modification times, and lessenprogramming errors improving at the same time readability,code auto-description and code reusability. Finally, Hajarnavisdescribes the results of an investigation into the techniquesused to design factory control system in the body-in-whitesection of car manufacturing plants located in Europe.

Since PLCs are established as the device of choice forthe implementation of control algorithms in many manufac-turing companies [11] a good starting point is to presentthe industrial specification IEC 61131-3 [12] which containsfive programming languages for developing PLC programsthat are supposed to be supported by any compliant vendor.The main goals of the IEC 61131-3 standard is to unify allthe programming concepts for developing industrial controlapplications [13].

The supported programming language are:1) Instruction List (IL) - A textual low level programming

language similar to assembly and consisting of simpleoperation codes.

2) Structured Text (ST) - A high-level programming lan-guage with syntax similar to Pascal, Basic or Fortransuited for programming more complex algorithms.

3) Function Blocks Diagram (FBD) - A graphical languageproviding a mechanism for encapsulating functionalityinto a module with a common external interface, anddesigned to promote reuse of code.

4) Sequential Function Chart (SFC) - A graphic languagederived from the GRAFCET (a simplified version ofPetri Nets). It is made up of graphical elements calledsteps and transitions; a step represents a specific statein process and/or machine sequence while a transitionrepresents the set of conditions that allows the evolutionfrom one step to another.

5) Ladder Diagram (LLD) - A graphical language deriveddirectly from the electrical relay diagram and created tobe easy to understand for booth engineers and technicianwithout any software skills.

Most of the industrial applications are designed using oneof these languages. However as exposed in [8] and recentlyconfirmed a poll realized by the Control Engineering U.S. andControl Engineering Poland magazine [14], 96% of industrialdevelopers uses LLD diagrams. FBDs are the next mostpopular at 67%, followed by IL (37%) as depicted in fgiure 1.

Therefore, the LLDs represent the most common methodfor creating control solutions, especially as regards the car

Fig. 1. Industrial programming languages dissemination [14]

manufacturing industry, that represents the background for theProFlex methodology. The LD diagrams are, probably, thesimplest mechanism for constructing industrial control appli-cations, since are rooted directly to the electrical drawings forhardwired control panel. Several reasons exist for ladder dia-grams prevalence in the industry. First of all a historical reason,since the ladder diagram was created to enable a soft paradigmswitch from electromechanical systems to new microprocessor-based system allowing creation of control applications thatlook like the electrical diagrams. According to Walter [15],LD diagrams are an excellent graphical representation basedon well-understood circuit design concepts allowing to quicklydevelop basic programming skills. Furthermore, since LLDsare designed to mirror electrical circuits then it naturally isa good way to represent discrete logic. However Walter alsopoints out some drawbacks when using LLDs such as the poordata structure, the limited execution control and arithmeticcapabilities. The lack of a good semantic level in LLDs is stilla discussion element in the scientific community. As exposedin [16], semantics describe the meaning of diagrams, i.e., thebehaviour of the computer when such diagram is “executed”. Ina LLD the semantic is defined by spatial relationship betweencomponents implying that LLDs could be hard to visualize andbecome unreadable even for small to medium size programsresulting in a monitoring and control application hard to debugand modify [17].

B. Alternative Design Methodologies

As pointed in II-A, LLDs weaknesses lead the researchcommunity to find new techniques, methodologies and/orapproaches to improve ladder code even if without abandoningit. A lot of work has been carried out by several authorson the application of structured programming techniques,software engineering methods including modularity and top-down design as well as object oriented paradigm to the designof LLDs for advanced automation engineering [18]–[20]. Javabased solutions have also been used to design industrial controlapplications that satisfy requirements imposed by agility suchas reconfiguration allowing at the same time to generate a IEC61131-3 standard compliant code [21], however more exper-imental tests and validations on real manufacturing systemshave still to be conducted. Other authors have focused on theapplication of Petri Nets as a formal method to reduce theerror during the process of implementing industrial controlapplications while improving the semantic level and thusto facilitate the programming process [22], [23] and/or toautomatically generate ladder diagrams [24], [25] increasing,in this way, the industrial acceptance of the new methodology.Despite the existence of extensive published material outliningthe availability of Petri Nets paradigm for design, modellingand developing industrial control applications, there are nocommercial Petri Net based development environment , fur-thermore, there is little reported application of Petri Nets inpractice. Nevertheless, further work in addition to Petri Netshas also been proposed. Finite state machines (FSM) has beenused to create a modular structure for designing and modelling

controllers as well as generating LLDs [26], [27]. A set ofsoftware tools that have been developed to create, manipulate,verify, and execute logic control systems written using modularfinite state machines (MFSMs) is described in [28], [29].

Despite the ladder diagram disadvantages and the prolif-eration of more powerful and richer semantic representationprogramming languages, it is believed that ladder diagramswill continue to be wide used for constructing industrialapplications. The reason why the industry is still betting onthe ladder diagrams is basically due to its simplicity withrespect of more advanced programming languages allowingto be handled by operators, as well as the lack of betteralternatives that justify costs and risks associated with theshift to another design methodology. Moreover the existence ofseveral rigid software and hardware standards, especially in theautomotive industry, quite complicates the introduction of anynew tool and methodology and discourages their acceptanceby the industrial community.

Nevertheless, the using of LLDs not prevent the devel-oping of new methodologies that based on good program-ming practices do not need ladder for creating industrialapplications. The challenges for agility demand new methodsand approaches for creating industrial application even if thefinal result has to be a ladder diagram. In this scenario, theproposed methodology defines a set of rule based on highlevel programming language paradigm for creating industrialapplications assuming that the original representation willalways be transformed into ladder.

III. METHODOLOGY

The methodology proposed in this paper addresses aneffective way for high level PLCs monitoring and controlsolution implementation and automatic generation of IEC61131-3 compliant code starting from a behavioral model ofthe constituent resources of a manufacturing assembly line (seeFig. 2).

Fig. 2. Methodology Concept

To do this, a new and innovative methodology has been de-signed and implemented as shown in Fig. 3. The methodologycan be divided into two main cycles the Model DevelopmentCycle and the Control Development Cycle respectively. Theformer includes the sequence of activities necessary to developa behavioural model of the manufacturing assembly line. Thelatter includes all the activities to develop an IEC61131-3standard compliant control software. Furthermore, inside theModel Development Cycle the Agentification Cycle is executed

Fig. 3. Main activities of the proposed methodology

and intended to transform real manufacturing componentsinto agents which behaviour is modelled using a formal andunique representation. In this scenario, each manufacturingcomponent will be then represented by a self-contained pieceof software (agent) inside the PLC that is responsible to controland monitor the status and activities of its own associatedmanufacturing equipment in order to meet a specific objective.Even if each agent is capable to sense changes in the stateof its own resource and act in response of these, only theinteractions between them enable the correct execution of theactivities of the manufacturing production line and/or cells interms of functionalities and sequence of operations.

Therefore the main activities of the methodology are five,namely:

• A0: Monitoring and Control system requirements analy-sis.

• A1: Identification of the constituent resources of themanufacturing assembly line.

• A2: Construct an universal behavioural model of eachresource.

• A3: Software Generation.• A4: Deployment and Tests.The activities A0, A1 and A2 are executed during the Model

Development Cycle.The Monitoring and Control system Requirements Analysis

activity is intended to identify the monitoring and controlsystem requirements starting from the entire set of mechanicaland electrical specifications of the manufacturing assemblyline. In this context the following documents are analyzed:the mechanical and electrical drawings, the description of the

Fig. 4. Formal representation of real machines/stations

hardware, the sequences of works of the machines/stations andthe description of the proprietary software standard. The outputof the activity A0 is used to start the Agentification Cyclethat, in turn, includes the activities A1 and A2. The activityA1 performs the identification of the constituent resources ofthe manufacturing assembly line. During this activity all themachines/stations of the manufacturing line are identified andtheir sensors and actuators are grouped together. Moreoverall the interactions of machines/stations are explained. In thiscontext, two kinds of interactions can occur, namely internalinteractions (between machine/station internal components)and external interactions (with other machines/stations). Theresults of this activity are a set of Manufacturing ResourcesEntities and/or agents which behaviour is modelled usinga formal and unique representation (see Fig. 4) during theactivity A2. Once the behavioral model of the manufacturingcomponents is obtained, the Control Development Cycle startsand the activity A3 is performed. The control software isdeveloped starting from the behavioral model and consider-ing necessary information such as the specific software andhardware standards. Furthermore, several templates are usedduring the Software Generation activity in order to keep thesoftware structure as much as possible similar to the differentproprietary standards. This way the generated code satisfiesboth the functional requirements and the specific formalismand syntax.

The output of the activity A3 will be an eXtensible MarkupLanguage (XML) file that can be easily deployed into severalPLCs.

Finally, the Deployment and Tests activity represents a setof tasks for mapping the XML file to IEC-61131-3 standardcompliant language. This activity is performed using the PLCvendor development environment.

The proposed methodology offers an effective and simpleway for developing monitoring and control solutions using aformal representation of the manufacturing resources whilekeeping the specific proprietary standards. The methodologyfocuses on a kind of “lingua franca”, represented by thebehavioral model, as a way to enable fast coding, improveindustrial acceptance of developed code and, most important,reduce the error during the programming activity. As a result,the following section IV shows some experimental resultobtained by applying such methodology.

IV. A MANUFACTURING CELL FOR APPLYING THEMETHODOLOGY

In order to validate and test the proposed methodology, tworobotized manufacturing cells located at IntRoSys have beenused (see Fig. 5).

Fig. 5. Manufacturing cell used to test the methodology

The cells are identical in terms of functionalities, howeverthey rely on two distinct hardware and software standardsfrom two automotive industry manufacturer. The cells includea loading station used to load car components and a weldingrobot. The main differences between the manufacturing cellsare resumed in table I. These jigs presented in both cellsare symmetric and their purpose is to hold and guarantee afirm position to allow operations over the parts with the tworobots (KUKA and Fanuc). These two robots, despite beingprogrammed according to distinguished Standards, (composedby 6 axes, controller, and the possibility to plug a tool on thesixth axis) can perform the same detailed actions in parts.

The LLDs for monitoring and control these two cells hasbeen implemented applying two distinct approaches. First ofall, a traditional programming approach has been consideredand the time needed to create LLDs has been monitored.Secondly, the manufacturing cell has been programmed, i.e. theLLDs have been implemented using the proposed approach.During the design and development of the offline monitoringand control solution two fundamental differences between theapplied approaches arose, namely:

1) The time needed to model the problem;2) and the time needed to create the LLDs;As a matter of fact, applying a traditional programming

approach the modelling time is extremely short (the codingstarts as soon as possible without any modelling activity),while on the contrary the coding time varies between fiveand seven days. On the other hand, applying the proposedmethodology the modelling time is greater than before andvaries between one or two days (depending on how complex

the manufacturing cell is), however the coding time is almostzero since the LLDs are automatically generated and theprogrammer needs only to check the generated files. The testsperformed, clearly shown that the application of the proposedmethodology could improve the coding activity performed es-pecially by system integrators while keeping the code standardcompliant. As a matter of fact, the results of the application ofthe proposed methodology can be resumed in a reduction ofalmost 70% of the time needed to generate the LLDs and as aconsequece a significant reduction of the programming effortwhenever modificaions should be realized inside the PLC code(see Fig. 6).

Fig. 6. Experimental Results obtained applying the two approaches

V. CONCLUSION

The following paper presents an innovative methodologyfor automatically generate the LLDs. The key element andinnovative aspect of these methodology is that it relies ona unique model that is generated from the entire set ofmanufacturing process specifications. The choice of the formalrepresentation for manufacturing machines/stations has beenrealized considering the main documents and principal tech-niques used by system integrators to design and implementprocess specific LLDs. All the steps of the methodology havedescribed and an application scenario has been consideredto show the feasibility and repeatability of the proposedapproach. Furthermore, relevant results has been presentedshowing the reduction of the time necessary to create LLDsalso called coding time. Finally, it is imperative to state thatthe reduction of the coding time is not the only achievementsince typically the development of LLDs is an error-proneactivity especially when 100% performed by human. In thisscenario, the proposed methodology allows the reduction of theerrors during the coding activity while guaranting a standardcompliant code since it is template-based. The LLDs created

Ford Motor Company Volkswagen AG

Type of Controller Main characteristics Type of Controller Main characteristics

Rockwell

Safety softwired

Siemens

Safety softwiredEthernet IP ProfiNetImplicit Sequencer (DCP) Explicit Sequencer (S7 Graph)Dynamic Address space Static Address SpaceRISC CISCLLDs LLDs, STL, FBDIntegrated Development Environment Modularized Development Environment

TABLE ICOMPARISON BETWEEN FORD MOTOR COMPANY AND VOLKSWAGEN AG STANDARDS

using the proposed methodology can be directly downloadedinside PLCs and is ready to be tested.

ACKNOWLEDGMENT

This work was funded by the Regional Operational Pro-gramme of Lisbon (POR Lisboa), in the scope of the NationalStrategic Reference Framework of Portugal (QREN), part ofthe European Regional Development Fund (FEDER). Thiswork is also supported by FCT Fundacao para a Ciencia eTecnologia under project grant Pest-OE/EEI/UI0066/2011.

REFERENCES

[1] F. Rosin and S. Temperini, “Advanced maintenance strategies for asustainable manufacturing,” in 10th IFAC Workshop on Intelligent Man-ufacturing Systems (IMS’10), Lisbon, 2010.

[2] M. Bergert and J. Kiefer, “Mechatronic data models in productionengineering,” Lisbon, 2010.

[3] H. Van Dyke Parunak, “What can agents do in industry, and why? anoverview on industrially-oriented R&D at CEC,” 1998.

[4] V. Hajarnavis and K. Young, “An assessment of PLC software structuresuitability for the support of flexible manufacturing processes,” Automa-tion Science and Engineering, IEEE Transactions on, vol. 5, no. 4, pp.641 –650, Oct. 2008.

[5] T. Wagner, “Applying agents for engineering of industrial automationsystems,” pp. 1097— 1097, 2003.

[6] J. Barata, Coalition Based Approach For ShopFloor Agility. Amadora- Lisboa: Orion, 2005.

[7] M. Lucas and D. Tilbury, “A study of current logicdesign practices in the automotive manufacturing industry,”International Journal of Human-Computer Studies, vol. 59,no. 5, pp. 725–753, Nov. 2003. [Online]. Available:http://www.sciencedirect.com/science/article/pii/S1071581903001150

[8] M. R. Lucas, “Understanding and assessing logic control design method-ologies,” Ph.D. dissertation, University of Michigan, 2003.

[9] O. Ljungkrantz and K. Akesson, “A study of industrial logic controlprogramming using library components,” in Automation Science andEngineering, 2007. CASE 2007. IEEE International Conference on.IEEE, 2007, pp. 117–122.

[10] O. Ljungkrantz, K. Akesson, and M. Fabian, “Formal specification andverification of components for industrial logic control programming,” inAutomation Science and Engineering, 2008. CASE 2008. IEEE Interna-tional Conference on, Aug. 2008, pp. 935 –940.

[11] V. Hajarnavis and K. Young, “An investigation into programmablelogic controller software design techniques in the automotive industry,”Assembly Automation, vol. 28, no. 1, pp. 43–54, 2008.

[12] R. W. Lewis, Programming Industrial Control Systems Using Iec 1131-3.IET, 1998.

[13] A. Zoitl and V. Vyatkin, “IEC 61499 architecture for distributed automa-tion: the ”Glass half full” view,” Industrial Electronics Magazine, pp. 7— 23, 2009.

[14] K. Pietrusewicz and L. Urbanski, “Control programming software strate-gies for industrial systems,” Control Engineering, 2011.

[15] T. Walter, “Ladder logic: Strengths, weaknesses.” Control Engineering,Mar. 2007. [Online]. Available: http://www.highbeam.com/doc/1G1-160719386.html

[16] M. Minas, “Creating semantic representations of diagrams,”in Applications of Graph Transformations with IndustrialRelevance, ser. Lecture Notes in Computer Science, M. Nagl,A. Schrr, and M. Mnch, Eds. Springer Berlin /Heidelberg, 2000, vol. 1779, pp. 286–289. [Online]. Available:http://www.springerlink.com/content/x71ykr6wmpp5e6mf/abstract/

[17] D. Bender, B. Combemale, X. Cregut, J. Farines, B. Berthomieu,and F. Vernadat, “Ladder metamodeling and plc program validationthrough time petri nets,” in Model Driven Architecture–Foundations andApplications. Springer, 2008, pp. 121–136.

[18] M. Bonfe, C. Donati, and C. Fantuzzi, “An application of software designmethods to manufacturing systems supervision and control,” in ControlApplications, 2002. Proceedings of the 2002 International Conferenceon, vol. 2, 2002, pp. 850 – 855 vol.2.

[19] D. Ponizil, “Back to basics: the essentials of structured plc,” ControlEngineering, vol. 48, no. 9, p. 76, 2001.

[20] C. Maffezzoni, L. Ferrarini, and E. Carpanzano, “Object-orientedmodels for advanced automation engineering,” Control EngineeringPractice, vol. 7, no. 8, pp. 957–968, Aug. 1999. [Online]. Available:http://www.sciencedirect.com/science/article/pii/S096706619900074X

[21] G. Aiello, M. Alessi, M. Bruccoleri, C. D’Onofrio, and G. Vella, “Anagile methodology for manufacturing control systems development,”in Industrial Informatics, 2007 5th IEEE International Conference on,vol. 2, Jun. 2007, pp. 817 –822.

[22] J.-S. Lee and P.-L. Hsu, “An improved evaluation of ladder logicdiagrams and petri nets for the sequence controller design in manufac-turing systems,” The International Journal of Advanced ManufacturingTechnology, vol. 24, no. 3, pp. 279–287, 2004. [Online]. Available:http://www.springerlink.com/content/q7nnqrcq2atkr9jt/abstract/

[23] K. Venkatesh, M. Zhou, and R. Caudill, “Comparing ladder logicdiagrams and petri nets for sequence controller design through a discretemanufacturing system,” Industrial Electronics, IEEE Transactions on,vol. 41, no. 6, pp. 611 –619, Dec. 1994.

[24] S. Korotkin, G. Zaidner, B. Cohen, A. Ellenbogen, M. Arad, andY. Cohen, “A petri net formal design methodology for discrete-eventcontrol of industrial automated systems,” in Electrical and ElectronicsEngineers in Israel (IEEEI), 2010 IEEE 26th Convention of. IEEE,2010, pp. 000 431–000 435.

[25] S. S. Peng and M. C. Zhou, “Ladder diagram and petri-net-baseddiscrete-event control design methods,” Systems, Man, and Cybernetics,Part C: Applications and Reviews, IEEE Transactions on, vol. 34, no. 4,pp. 523 –531, Nov. 2004.

[26] S. Manesis and K. Akantziotis, “Automated synthesis of ladder au-tomation circuits based on state-diagrams,” Advances in EngineeringSoftware, vol. 36, no. 4, pp. 225–233, 2005.

[27] G. Ekberg and B. H. Krogh, “Programming discrete control systemsusing state machine templates,” in Discrete Event Systems, 2006 8thInternational Workshop on. IEEE, 2006, pp. 194–200.

[28] E. Almeida, J. Luntz, and D. Tilbury, “Event-condition-action systemsfor reconfigurable logic control,” Automation Science and Engineering,IEEE Transactions on, vol. 4, no. 2, pp. 167 –181, Apr. 2007.

[29] E. Endsley, Modular finite state machines for logic control: Theory,verification and applications to reconfigurable manufacturing systems.University of Michigan, 2004.