International Symposium on INnovations in Intelligent SysTems and Applications, INISTA'09, Karadeniz Technical University, Trabzon, Turkey, 29 June - 01 July, 2009.
Automation Petri Net Based Railway Interlocking and Signalization Design Mustafa Seçkin Durmuş1, Mehmet Turan Söylemez2 Istanbul Technical University
[email protected],
[email protected] Abstract Signalization and interlocking systems play a crucial role to provide safe transportation in railway systems. Since no error can be tolerated in these systems it is important to use formal methods in the design. Several formal methods that can be used in this perspective exist in the literature including automata theory and Petri Nets (PNs). In this study, it is shown that railway track interlocking and signalization operations can be modeled by Automation Petri Nets (APNs) which is an extended type of PNs. Moreover, obtained model can easily be implemented on a programmable logic controller (PLC) to verify the accuracy of the method on a sample railway yard.
1. Introduction Systems like communication, transportation, computer and manufacturing which have features like non-determinism, asynchronism, event-driven and simultaneity in their structures are known as Discrete Event Systems (DES) [2]. As a result of rapidly developing technology, complexity of those systems gradually increase and this brings along adversity in control of those systems. Therefore, requirement of efficient and formal methods come into question. Most common methods are as follows: Petri Nets (PN) [3], [4], Finite State Machines (FSM) [5] and Grafcet [6]. In FSM approach, an increase in system complexity causes an increase in the number of states, consequently illustration of graphics gets more complicated and intelligibility decreases. Because of above reasons this method is not a practical solution. Grafcet which is inspired by PNs is also used in modeling of DES. Simultaneous and interacting simple systems which have states with only one token can be modeled by Grafcet [6]. Therefore this method is not flexible as PNs [7, 8]. PNs are more comprehensible then FSMs and Grafcet, in addition to this, because of its easiness in graphical illustration and easiness in practice on programmable logic controller (PLC), PNs have a wide field of application area [4, 7, 11-13].
However, ordinary PNs do not deal with actuators or sensors, therefore in addition to all these methods for modeling and analyzing DES a new method is proposed as an extension of PNs and is called as Automation Petri Nets (APN) [710] that can embrace both actuators and sensors. Beside industrial applications, PNs are also used in railway applications like scheduling rail operations [14], a supervisory control approach for railway networks [15, 16], modeling train control systems for level crossing [17], constructing PN model automatically for Oslo subway [18], another simulation study of Oslo subway [19] and German railways [20], developing interlocking [21] and signaling systems [22] with safety verifications. In this paper, interlocking and signalization of a railway yard is modeled by APNs and resulting model is implemented on a PLC by using Token Passing Logic (TPL) [23], [24] to verify its accuracy. This paper is structured as follows. Section 2 introduces APNs briefly. A short description about components in railway signalization and interlocking is given in section 3. Design by APNs is discussed and model of a sample railway yard by APNs is introduced in section 4. At last, results are given in section 5.
2. Automation Petri Nets A marked PN is a quintuple and can be seen on figure 1 [2, 4]. PN = (P, T, Pre, Post, M0)
(1)
P : {p1, p2, …, pn}, finite set of places. T : {t1, t2, …, tn}, finite set of transitions. Pre : (PxT) → N, directed ordinary arcs from places to transitions (N is a set of nonnegative integers). Post : (TxP) → N, directed ordinary arcs from transitions to places. M0 : P → N, initial marking.
International Symposium on INnovations in Intelligent SysTems and Applications, INISTA'09, Karadeniz Technical University, Trabzon, Turkey, 29 June - 01 July, 2009. •
Token
• • P1
• P3
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2
Transition
t2
t1 Place
P4
P2
Directed Ordinary Arc
(b)
(a)
Figure 1. Ordinary Petri Net An extension of the above definition can be done easily by adding four terms to ordinary PNs and known as Automation Petri Nets (APN) [7]. An APN is defined as follows and can be seen on figure 2. In : (PxT) → N, inhibitor arcs from places to transitions. En : (PxT) → N, enabling arcs from places to transitions. χ : {χ1, χ2, …, χm}, firing conditions associated with the transitions. Q : {q1, q2, …, qn}, finite set of actions that might be assigned to the places. P1 •
Figure 3. (a) Number of tokens on P1 is less then the number of enabling arcs from P 1 to t1 therefore t1 is not fired. (b) Number of tokens on P3 is less than the number of inhibitor arcs from P 3 to t2 therefore t2 is fired [7] More than one action can be assigned to places and by putting a token on that place, these assigned actions get activated. However, a transition can be fired under two circumstances; firstly, number of tokens on a place must be equal to the number of ordinary directed arcs and secondly transition firing condition χ (information coming from sensors that is associated with transition t) must be satisfied. When these two conditions are satisfied, tokens can be passed from one place to another through transition t and number of tokens on both places decreases and increases, respectively. An example is shown on figure 4.
•
P2
t1
χ1
P4
P3
t2
χ1
P7
χ1
t1
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P3 (a)
P6
Figure 2. Automation Petri Net APN = (P, T, Pre, Post, In, En, χ, Q, M0)
2
2
P5 χ2
P1
• • P1
t1
P2 •
• P3 (b)
Figure 4. Token passings (2)
Unlike PNs in APNs, inhibitor arcs ( ) and enabling arcs ( ) are added in addition to ordinary directed arcs (→). These newly added arcs are ineffective on number of tokens in places but enables or inhibits transitions. It is shown in figure 3 that, if a place is connected to a transition with an enabling arc, that transition can be fired if and only if the token number on that place is equal or greater than the number of enabling arc number. Likewise if a place is connected to a transition with an inhibitor arc, that transition can be fired if and only if the token number on that place is less than the number of inhibitor arc number.
In Figure 4(a) the number of tokens on P 1 is equal to number of ordinary arcs between P 1 and t1; therefore, t1 is enabled. If firing condition χ1 is satisfied than transition t1 is fired and the number of tokens on P1 is decreased (as the number of ordinary arcs from P1 to t1). Afterwards number of tokens on places which are connected by t1 is increased (as the number of ordinary arcs from t1 to P2 and t1 to P3) as seen on Figure 4(b).
3. Interlocking and signalization system In order to achieve safe transportation on railways the following equipments are used:
3.1. Railway switches Because of the absence of any steering mechanism on trains, switches are use for shifting trains from one railway to another (or changing route). An example switch is shown on figure 5.
International Symposium on INnovations in Intelligent SysTems and Applications, INISTA'09, Karadeniz Technical University, Trabzon, Turkey, 29 June - 01 July, 2009. Protection) and ATO (Automatic Train Operation). However, such mechanisms are considered to be out of the scope of this paper.
4. Design interlocking
Figure 5. Two crossover switches
3.2. Track circuits and signal lights
Railway flow direction
Track circuits (TC) are use for detecting trains on railways. These equipments inform Traffic Control Center (TCC) about the absence or presence of the train (see figure 6).
(a)
G
G
R
R
(b)
Figure 6. (a) Unoccupied track circuit, green light is on, (b) Occupied track circuit, red light is on Signal lights are placed in front of switches on railway yards to inform trains if the railway yard is occupied or not.
3.3 Interlocking Railway traffic is controlled from Traffic Control Center (TCC). TCC reserves the desired route for an incoming train by requesting a reservation from the interlocking system, which checks the suitability of the request and if appropriate completes the reservation by changing the signals and positions of switches on that route. The other routes that intersect with this reserved route are prohibited to assure safety. After a train completes the route reserved for it, prohibited railway tracks become enabled for new route reservations. If a train enters to a previously reserved route even it is prohibited, it is possible to stop the train and prevent a possible collision, using mechanisms like ATP (Automatic Train
of
signalization
and
Railway yard shown in Figure 7 is used for application. The entrance of any train on this railway yard can be defined via track circuits which are established on regions A, B, C, D, E, F, S1 and S2. The train is supposed to follow the route reserved by TCC for it.There are two crossover switches on Figure 7 named as S1o-S1c, S2o-S2c. When switch S1 is on S1o position, crossing from upper track to lower track (or vice versa) is enabled otherwise crossing is disabled. For every track circuit M (bit) memories (because of only one train can exist on a railway track) are used on S7-200 PLC. Incoming signals (positive (↑) and negative (↓) transition) from track circuits (inputs of the PLC) and reserved route information which is provided by TCC are compared with each other by PLC, then lights on the reserved route are turn to green and keep all the others on red. While a train is moving on its route, the lights passed by turn back to red immediately for new reservations. We assume that all lights are red and all switches are on S1c and S2c position, respectively, at the beginning, when there is no train on the railway yard. If an unwanted situation occurs like reservation of track B and S1 or reservation of track S2 and track F at the same time, APN disables all the crossings on switches and keeps all the related lights on red to prevent derailing or collision. The related enabling and disabling arcs can be seen from APN model given in Figure 8.An APN model of the railway yard shown in figure 7 is given in figure 8. The model consists 40 transitions with 16 places. While constructing the APN model, we assume that trains can exist only in one region (On region A or on region B or between A and B). Firing conditions associated with the transitions are positive and negative edges of the input signals incoming from track circuits. If all conditions are satisfied then related transition is fired and token (train) passes from that place (track circuit) to another place (track circuit).For example, in order to fire transition t10, four conditions have to be satisfied: 1) There has to be a train on track circuit (TC) A, 2) TC-S1 must be reserved (place PA and PS1m have tokens), 3) there mustn’t be any train between TC-A and TCS1 and 4) TC-B mustn’t be reserved (place PAS1 and PBm must have no tokens). After these four conditions are satisfied and if the negative edge signal of TC-A is received t10 will be fired and train (token) can pass from one place to another.
International Symposium on INnovations in Intelligent SysTems and Applications, INISTA'09, Karadeniz Technical University, Trabzon, Turkey, 29 June - 01 July, 2009. B
A A
C
R G
R G
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S2o
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D D
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Figure 7. Railway yard PTCC
t31, S2↑
t2, C↓
PS2C
t1, C↑
PS2
PS2m
PCm
t32, S2↓
t39, C↑
PBC
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t7, B↓
t5, B↑
PEm t29, S2↑
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PAB
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t9, A↓
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PA
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t15, E↑
t16, E↓
PBm
t40, C↓
t4, C↓
t8, B↓
PB
PS1m
t12, A↑ t25, S1↑
PS1 t28, S1↓ t19, E↑
t26, S1↓
PS1E t27, S1↑ t35, D↑
t21, E↑
t22, E↓
t14, D↓
t17, E↓
PDE
t18, E↑ t24, F↑
PEF
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t20, E↓
PE
t23, F↓
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M2.4
t37, F↑
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t38, F↓
•
PLAg
Switch1
PLAr
PS1m↓
t26, S1↓ t28, S1↓
PCm↓
PLCg
t2, C↓ t4, C↓
PLCr
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Light F
PFm↓
PLFg
t23, F↓
PLFr
PS1c
Switch2
PS2m↓ t30, S2↓ t32, S2↓
Light B
PLBr PLBg
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•
Light D
t7, B↓ t8, B↓
PS1o
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•
PAm↓ t9, A↓ t10, A↓
t36, D↓
t13, D↑
Light A
• •
PFm
PC
t3, C↑
Figure 8. APN model of the railway yard
PLDr PLDg
•
PLEr PLEg
PDm↓ t14, D↓
Light E
PEm↓
t16, E↓ t17, E↓ t20, E↓ t22, E↓
International Symposium on INnovations in Intelligent SysTems and Applications, INISTA'09, Karadeniz Technical University, Trabzon, Turkey, 29 June - 01 July, 2009. Ladder Logic”, Proc. of the Symposium on Discrete Events and When a track circuit is reserved by TCC then the Manufacturing Systems, CESA’96 IMACS Multiconference, 1996, related light turns green while the others remain red. pp. 513-518. This is provided by enabling arcs, for example in [9] A. H. Jones, M. Uzam, A. H. Khan, D. Karımzadgan and S. order to turn light A into green TC-A must be B. Kenway, “A General Methodology for Converting Petri Nets reserved that is provided by putting a token into place into Ladder Logic: The TPLL Methodology”, Proc. of the 5th Int. PAm. as can be observed from figure 8. Conference on Computer Integrated Manufacturing and Assume that, a train arrived at TC D and its requested route is D→E→F. At first TCC have to reserve this requested route by putting tokens into PDm, PEm and PFm. (this token putting is achieved by setting the related M memories in PLC). By putting tokens the related lights turn green while others kept red. While train is moving on this route, track circuits passed by this train gets free by deleting tokens from the reserved places (PDm, PEm and PFm) for new reservations (this token deleting is achieved by resetting the related M memories in PLC). This APN model given in figure 8 can be convert into PLC ladder diagram code easily via token passing logic-TPL technique given in [9], [23], [24].
5 Results In this study, interlocking and signalization design of a sample railway yard achieved. Besides gathering more visuality and simple improvability to Discrete Event Systems, APN models can easily implement on a programmable logic controller, therefore error tracing and improving of the APN model for different scenarios can be realize effortless. Signalization and interlocking systems on the routes of light rail and metro systems can be modeled with APNs in order to provide more efficient control and safety. For further work, APN model and PLC code for real systems which have more safety specifications considering time-delays like between the commands and actualizing the commands will be develop in order to broaden availability of this method.
6. References [1] B. Barnard, “Railway System Modeling – Not Just for Fun”, IEE Seminar on Railway System Modeling, London - UK - ISBN: 0 86341 457 5, 30 September 2004, pp. 2-6. [2] C. G. Cassandras and S. Lafortune, “Introduction to Discrete Event Systems”, Kluwer Academic Publishers, 1999. [3] C. A. Petri, “Kommunikation mit Automaten Schriften des Rheinisch”, Westfalischen Inst. fur Instrumentelle Mathematik und der Universitat Bonn, English Translation: C.F. Green, Applied Data Research Inc., Suppl. 1 to Tech report RADC-TR-65-337, NY, 1962. [4] T. Murata, “Petri Nets: Properties, Analysis and Applications”, Proc. of IEEE, vol. 77, no. 4, 1989, pp. 541-580. [5] P. J. Ramadge, W. M. Wonham, “The Control of Discrete Event Systems”, Proc. of IEEE, vol. 77, no. 1, pp. 81-89, 1989. [6] R. David, “Grafcet: A Powerful Tool for Specification of Logic Controllers”, IEEE Trans. on Control Systems Technology, vol. 3, no. 3, 1995, pp. 253-269. [7] M. Uzam and A. H. Jones, “Discrete Event Control System Design Using Automation Petri Nets and Their Ladder Diagram Implementation”, The International Journal of Advanced Manufacturing Technology, vol. 14, no. 10, 1998, pp. 716-728. [8] M. Uzam and A. H. Jones, “Design of a Discrete Event Control System for a Manufacturing System Using Token Passing
Automation Technology–CIMAT’96, 1996, pp. 357-362. [10] M. Uzam and A. H. Jones, “Conversion of Petri Net Controllers for Manufacturing Systems into Ladder Logic Diagrams”, Proc. of the IEEE Conf. on Emerging Technologies and Factory Automation, ETFA’96, vol. 2, 1996, pp. 649-655. [11] R. Zurawski and M. C. Zhou, “Petri Nets and Industrial Applications: A Tutorial”, IEEE Trans. on Industrial Electronics, vol. 41, no. 6, 1994, pp. 567-583. [12] S. S. Peng and M. C. Zhou, “Sensor-based Petri Net Modeling for PLC Stage Programming of Discrete-Event Control Design”. International Journal of Production Research, vol. 41, no. 3, 2003, pp. 629-644. [13] A. D. Febbraro, G. Porta and N. Sacco, “A Petri Net modelling approach of intermodal terminals based on Metrocargo© system”, Proc. of the IEEE Intelligent Transportation Systems Conf., 2006, pp. 1442 – 1447. [14] X. Ren and M. C. Zhou, “Tactical Scheduling of Rail Operations: A Petri Net Approach”, IEEE Int. Conf. on Systems, Man and Cybernetics, 1995, pp. 3087-3092. [15] A. Giua and C. Seatzu, “Supervisory Control of Railway Networks with Petri Nets”, Proc. of the 40th IEEE Conf. on Decision and Control, vol. 5, 2001, pp. 5004-5009. [16] A. Giua and C. Seatzu, “Modeling and Supervisory Control of Railway Networks Using Petri Nets”, IEEE Trans. On Automation Science and Engineering, vol. 5, no. 3, July 2008, pp. 431-445. [17] S. Einer, R. Slovak and E. Schneider, “Modeling Train control systems with Petrinets – An Operational Specification”, IEEE Int. Conf. on Systems, Man and Cybernetics, vol. 4, 2000, pp. 3207-3211. [18] A. M. Hagalisletto, J. Bjork, I. C. Yu and P. Enger, “Constructing and Refining Large-Scale Railway Models Represented by Petri Nets,” IEEE Trans. On System, Man and Cybernetics-Part C: Applications and Reviews, vol. 37, no. 4, pp. 444-460, July, 2007. [19] T. Kristoffersen, A. M. Hagalisletto and H. A. Hansen, “Extracting High-Level Information from Petri Nets: A Railroad Case”, Proceedings of the Estonian Academy of Physics and Mathematics, vol. 52, no. 4, 2003, pp. 378-393. [20] M. M. Hörste, “Modeling and Simulation of Train Control Sytems using Petri Nets”, World Congress on Formal Methods in the Development of Computing Systems, FM’99, vol. 1709 of Lecture Notes in Computer Science, September 1999, pp. 1867. [21] X. Hei, S. Takahashi and H. Nakamura, “Distributed Interlocking System and its Safety Verification”, Proc. of the 6th World Congress on Intelligent Control and Automation, vol. 2, June 21-23, Dalian, China, 2006, pp. 8612 - 8615.. [22] X. Hei, S. Takahashi and H. Nakamura, “Toward Develeoping a Decentralized Railway Signalling System Using Petri Nets”, IEEE Conf. on Robotics, Automation and Mechatronics, September 21-24, Chengdu, China, 2008, pp. 851855. [23] M. Uzam and A. H. Jones, “Design of Sequential Control Systems in Statement Lists Using TPL: Part I - Token Passing Statement List Methodology”, Proceedings of 2nd Portuguese Control Conference - Controlo’96, September 11-13, Porto, Portugal, 1996, pp. 341 - 346. [24] M. Uzam and A. H. Jones, “Design of Sequential Control Systems in Statement Lists Using TPL: Part II - An Application”, Proceedings of 2nd Portuguese Control Conference Controlo’96, September 11-13,Porto, Portugal, 1996, 771 - 775.
