© The Institution of Engineering and Technology
Traffic flow dynamics is an important issue for implementing effective pollutant discharge control of tunnels. Longitudinal ventilation using jet fans is the most popular system for pollutant discharge control of tunnels. Nowadays, jet fans equipped with the frequency conversion technology in the tunnel can shorten the control cycle and even conduct manipulation of step-less jet speeds. The longitudinal ventilation system has considerable inertia and non-linear characteristics, which are partly resulted from traffic flow dynamics such as traffic state transition. Therefore, in this paper an adaptive control method based on the artificial neural-network theory is proposed to be tailored to the traffic state transition. The model is based on aerodynamic equations and takes vehicle speed and density as main system disturbances, whose value can be determined by fundamental diagram when having incomplete field traffic data. The proposed controller can also cope with the parameters and uncertainties of the time-varying model. The author's simulation results show that the adaptive control method can track the desirable system output effectively whenever the traffic condition changes gently or dramatically. The results also show that our method performs better than the common-used proportional integral derivative (PID) controller in terms of system adaptability following the traffic state transition.
References
-
-
1)
-
15. Du, P.Y., Luo, X.P.: ‘The research of urban road tunnel longitudinal ventilation control based on RBF neural network’. Proc. 2010 Second IITA Int. Conf. on Geoscience and Remote Sensing, Qingdao, China, August 2010, pp. 85–87.
-
2)
-
12. Chu, B., Kim, D., Hong, D., et al: ‘GA-based fuzzy controller design for tunnel ventilation systems’, Autom. Constr., 2008, 17, (2), pp. 130–136 (doi: 10.1016/j.autcon.2007.05.011).
-
3)
-
14. Ma, C.Q., Jiang, D.S., Yue, X.: ‘Intelligent model of urban road tunnel ventilation system based on multi-level neural network’. Proc. 2009 Pacific-Asia Conf. on Circuits, Communications and Systems, Chengdu, China, May 2009, pp. 636–639.
-
4)
-
2. Bogdan, S., Birgmajer, B.: ‘Model predictive fuzzy control of longitudinal ventilation system in a road tunnel’. ATKAAF, 2006, 47, (1–2), pp. 39–48.
-
5)
-
1. Ma, Z.L., Shao, C.F., Zhang, S.R.: ‘Characteristics of traffic accidents in Chinese freeway tunnels’, Tunneling and Underground Space Technol., 2009, 24, (3), pp. 350–355 (doi: 10.1016/j.tust.2008.08.004).
-
6)
-
4. Zheng, X.: ‘Tunnel ventilator variable-frequency control in fuzzy PID algorithm’. IEEE Int. Symp. on Knowledge Acquisition and Modeling Workshop, Wuhan, China, December 2008, pp. 128–131.
-
7)
-
10. Li, H.C., Chen, K.S., Lai, C.H., Wang, H.K.: ‘Measurements of gaseous pollutant concentrations in the Hsuehshan Traffic Tunnel of Northern Taiwan’, Aerosol Air Quality Res., 2011, 11, (6S), pp. 776–782.
-
8)
-
23. EL-Fadel, M., Hashisho, Z.: ‘Vehicular emissions in roadway tunnels: a critical review’, Crit. Rev. Environ. Sci. Technol., 2001, 31, (2), pp. 125–174 (doi: 10.1080/20016491089190).
-
9)
-
13. Hrbcek, J., Spalek, J., Simak, V.: ‘Process model and implementation the multivariable model predictive control to ventilation system’. Proc. 2010 IEEE Eighth Int. Symp. on Applied Machine Intelligence and Informatics, Slovakia, January 2010, pp. 211–214.
-
10)
-
6. Liao, T.Y., Hu, T.Y., Ho, W.M.: ‘Simulation studies of traffic management strategies for a long tunnel’, Tunnelling and Underground Space Technol., 2012, 27, (1), pp. 123–132 (doi: 10.1016/j.tust.2011.08.004).
-
11)
-
24. Tan, Z., Huang, Z.Y., Wu, K., Xu, L.T.: ‘Theoretical analysis of longitudinal ventilation system in a road tunnel for predictive control based on inertia effect’, Adv. Mater. Res., 2013, 639–640, (1), pp. 665–669 (doi: 10.4028/www.scientific.net/AMR.639-640.665).
-
12)
-
9. Staehelin, J., Schläpfer, K., Bürgin, T., et al: ‘Emission factors from road traffic from a tunnel study (Gubrist tunnel, Switzerland). Part I: concept and first results’, Sci. Total Environ., 1995, 169, (1–3), pp. 141–147 (doi: 10.1016/0048-9697(95)04642-E).
-
13)
-
3. Tan, Z., Huang, Z., Wu, K., et al: ‘Simulation analysis of longitudinal ventilation system with jet fan speed control for MPC strategy in a road tunnel’. Proc. 15th IEEE Intelligent Transportation Systems Conf., Anchorage, Alaska, September 2012, pp. 1271–1276.
-
14)
-
7. Lin, C.J., Chuah, Y.K.: ‘A study on long tunnel smoke extraction strategies by numerical simulation’, Tunnelling and Underground Space Technol., 2008, 23, (5), pp. 522–530 (doi: 10.1016/j.tust.2007.09.003).
-
15)
-
11. Karakas, E.: ‘The control of highway tunnel ventilation using fuzzy logic’, Eng. Appl. Artif. Intell., 2003, 16, (7), pp. 717–721 (doi: 10.1016/S0952-1976(03)00068-X).
-
16)
-
5. He, H.D., Lu, W.Z., Dong, L.Y.: ‘Jam formation of traffic flow in harbor tunnel’, Commun. Theory Phys., 2011, 56, (6), pp. 1140–1144 (doi: 10.1088/0253-6102/56/6/29).
-
17)
-
19. Lubashevsky, I., Garnisov, C., Lifshits, B.: ‘Complex fundamental diagram of traffic flow in the Deep Lefortovo Tunnel (Moscow)’. Traffic and Granular Flow 07, Paris, France, June 2007, pp. 365–371.
-
18)
-
8. Ma, C.M., Hong, G.B., Chang, C.T.: ‘Influence of traffic flow patterns on air quality inside the longest tunnel in Asia’, Aerosol and Air Quality Res., 2011, 11, (1), pp. 44–50.
-
19)
-
17. Chu, B., Hong, D., Park, J.: ‘Tunnel ventilation control via an actor-critic algorithm employing nonparametric policy gradients’, J. Mech. Sci. Technol., 2009, 23, (2), pp. 311–323 (doi: 10.1007/s12206-008-0924-5).
-
20)
-
22. Jang, H.M., Chen, F.: ‘A novel approach to the transient ventilation of road tunnels’, J. Wind Eng. Ind. Aerodyn., 2000, 86, pp. 15–36 (doi: 10.1016/S0167-6105(99)00135-X).
-
21)
-
Q.M. Yang ,
B.J. Vance ,
S. Jagannathan
.
Control of nonaffine nonlinear discrete-time systems using reinforcement-learning-based linearly parameterized neural networks.
IEEE Trans. Syst. Man, Cybern. B, Cybern.
,
4 ,
994 -
1001
-
22)
-
16. Mu, Q.X., Zheng, X.: ‘The tunnel ventilation control based on iterative learning scheme’. Proc. 2010 Second IITA Int. Conf. on Geoscience and Remote Sensing, Qingdao, China, August 2010, pp. 306–309.
-
23)
-
20. Ye, H.H., Chen, X.R., Li, G.X.: ‘Research on traffic status in highway tunnel’, Res. Environ. Sci., 2001, 14, (4), pp. 41–43.
-
24)
-
21. Kurka, L., Ferkl, L., Sladek, O., Porizek, J.: ‘Simulation of traffic, ventilation and exhaust in a complex road tunnel’. Proc. 16th IFAC, Prague, Czech Republic, July 2005, pp. 1–6..
-
25)
-
18. EL-Fadel, M., Hashisho, Z.: ‘Vehicular emissions and air quality assessment in roadway tunnels: the Salim Slam tunnel’, Transp. Res. D, 2000, 5, (5), pp. 355–372 (doi: 10.1016/S1361-9209(00)00004-3).
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