Tunnel central control system enhanced with modern control approaches

• Autorzy: Hrbcek J. , Simak V. , Janota A. , Pirnik R.
• Języki publikacji: EN

Abstrakty

EN

The tunnel central control system is designed for maintaining the necessary safety and resistance against failures as a system fully redundant at all levels. All hardware components of the control system and their connections are doubled. Control system is based on the programmable logic controllers (PLC’s) and used the industrial buses on an optical and metallic physical layer. This system controls the traffic and all tunnel equipment systems (variable traffic signs, various lighting elements, ventilation system, etc.). Nowadays the control strategy is based on measured data inside the tunnel, metrological information and operator’s commands. The control strategy or algorithm must be enhanced to obtain better or optimal results. Using of model predictive control (MPC) may lead to optimize the control way for chosen criteria. MPC can be implemented to PLC by several methods.

Słowa kluczowe

EN

tunnel central control system; modern control

PL

centralny system sterowania tunelem; nowoczesne sterowanie

• Wydawca: Polskie Stowarzyszenie Telematyki Transportu
• Czasopismo: Archives of Transport System Telematics
• Rocznik: 2014
• Tom: Vol. 7, iss. 3
• Strony: 3--7
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Hrbcek J.

• University of Žilina, Faculty of Electrical Engineering, Univerzitná 1, 01026 Žilina, Slovakia

autor

Simak V.

• University of Žilina, Faculty of Electrical Engineering, Univerzitná 1, 01026 Žilina, Slovakia

autor

Janota A.

• University of Žilina, Faculty of Electrical Engineering, Univerzitná 1, 01026 Žilina, Slovakia

autor

Pirnik R.

• University of Žilina, Faculty of Electrical Engineering, Univerzitná 1, 01026 Žilina, Slovakia

Bibliografia

• [1] Camacho , E. F., Bordons , C.: Model Predictive Control. 2nd ed., Springer-Verlag LondonLimited (2004)
• [2] Johanson , R.: System modeling and identification, Prentice- Hall (1993)
• [3] Huang , Z.Y., Wu, K., Xu, L.T. : Simulation analysis of longitudinal ventilation system with jet fan speed control for MPC strategy in a road tunnel, In. Proc. of the 15th International IEEE Conference on Intelligent Transportation Systems, Anchorage, Alaska, USA (2012)
• [4] Hole čko , P., Buben ikov a, E., Pirnik, R.: Communication systems in transport – hybrid ITS interface. In: Proc. of 9th international conference ELEKTRO 2012, Žilina - Rajecke Teplice, Slovakia (2012)
• [5] Hrbček, J., Spalek , V., Šimak, V.: Mathematical description of tunnel systems for the purpose of design the predictive algorithm, Acta Electrotechnica et Informatica, Vol. 10, No. 2, (2010)
• [6] Maciejovski , J. M.: Predictive Control with constrains. 1st publ., Harlow, England: Prentice Hall (2002)
• [7] Hruboš , M., Janota , A.: Algorithm for Surface Creation from a Cloud of Points. In: Mikulski J. (Ed.), CCIS 395, Springer Heidelberg (2013)
• [8] Yinghua H., Hong W., Bo Z.: Color-Based Road Detection in Urban Traffic Scenes, IEEE Transactions on intelligent transportation systems, vol. 5, no. 4 (2004)
• [9] Ilavsk y, J., Rasto čny, K.: Considerations of the recovery in 2-out-of-3 safety-related control system. In proc. of the 11th IFAC/IEEE Conference on Programmable Devices and Embedded Systems – PDES 2012(2012)
• [10] Ždansky , J., Nagy , P.: Influence of the control system structure with safety PLC on its reliability and safety. Proceedings of the 9th international conference ELEKTRO 2012, IEEE Catalog Number: CFP1248S-ART, Rajecke Teplice (2012)
• [11] Ab-Rahman, S. M., Guna , H.: Integration of Green Technology POF based Splitter for Low-Cost WDM Network Solutions. Journal of Applied Sciences Research. Vol. 7(4) (2011)
• [12] Ab-Rahman, M.S., Hadiguna ,Supian , L.S.: Selection of spectral filters for optical demultiplexer-same filter different source. J. Comput (2013)
• [13] Yingjie X., Zhen T.G.Z.: Adaptive Fine Pollutant Discharge Control for Motor Vehicles Tunnels under Traffic State Transition. In: IET Intelligent Transport Systems (2014)
• [14] Lipika S., Shailja S.: Application of Model Predictive Control for Improving Stability of Rotor and Controlling Active Rotor Vibration, In: International Journal of Computer Applications , Volume 72– No.13 (2013)
• [15] Bubnicki , Z.: Modern Control Theory. Springer, (2005)
• [16] Cerovsk a, A., Spalek , J.: Implementation of Network Redundancy in Environment of Road Tunnel Control, Transport Systems Telematics, In: Mikulski J. (ed.) CCIS 104, Springer Heidelberg (2010)
• [17] Hrbček, J., Šimak, V.: Implementation of Multidimensional Model Predictive Control for Critical Process with Stochastic Behavior, chapter in: Advanced Model Predictive Control, InTech, Zheng T. (Ed.) (2011)
• [18] Hausler W.: Modern Air Velocity Sensors in Tunnels, In: International Conference „Tunnel Safety and Ventilation“ 2004, Graz (2004)
• [19] Hrbček, J.: Active Control of Rotor Vibration by Model Predictive Control – a simulation study. Report 153, Picaset Oy, Helsinki (2007)
• [20] B&R Automation Studio Target for Simulink, http://www. br-automation.com/en-gb/products/software/automationstudio- target-for-simulink/ (accesed: 06.2014)
• [21] Karo ń, G., Mikulski , J.: Transportation Systems Modelling as Planning, Organisation and Management for Solutions Created with ITS, In: Mikulski J. (Ed.), CCIS 329, Springer Heidelberg (2011)