Skip to main content
SpringerLink
Log in

Adaptive Critic Design Based Control of Tunnel Ventilation System with Variable Jet Speed

  • Published:
Journal of Signal Processing Systems Aims and scope Submit manuscript

Abstract

In this paper, an adaptive critic design (ACD) based control algorithm is proposed for road tunnel ventilation systems with jet fans. Firstly, a comprehensive dynamic model is established for control purpose, which considers both the static and dynamic nonlinearities between the pollutant concentration and the jet speed or the air flow inside the tunnel. Vehicle speed and density are also integrated into the model as system external disturbances. To cope with the time-varying model parameters and unknown system uncertainties, one artificial neural network (NN) unit is employed in controlling the jet fans to regulate the pollutant concentration to a desired level, even in the presence of varying working conditions. An additional NN is utilized to approximate the cost-to-go function required for the performance optimization. The proposed scheme is also verified and compared with traditional control design in simulation environment. The simulation results substantiate the conclusion that the adaptive controller can achieve a better regulation performance along with less energy consumption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  1. Chow, W. K., & Chan, M. Y. (2003). Field measurement on transient carbon monoxide levels in vehicular tunnels. Building and Environment, 38, 227–236.

    Article  Google Scholar 

  2. Tan, Z., Huang, Z. Y., Wu, K. (2012). Simulation analysis of longitudinal ventilation system with jet fan speed control for MPC strategy in a road tunnel. In 15th IEEE ITSC., Anchorage, Alaska, pp. 1471–1476.

  3. Zheng, X. (2008). Tunnel ventilator variable-frequency control in Fuzzy PID Algorithm. In IEEE KAM., Wuhan, Hubei, pp. 128–131.

  4. Bogdan, S., & Birgmajer, B. (2006). Model predictive fuzzy control of longitudinal ventilation system in a road tunnel. ATKAAF, 47, 39–48.

    Google Scholar 

  5. Ferkl, L., & Meinsma, G. (2007). Finding optimal ventilation control for highway tunnels. Tunnelling and Underground Space Technology, 22, 222–229.

    Article  Google Scholar 

  6. Ma, C. Q., Jiang, D. S., Yue, X. (2009). Intelligent model of urban road tunnel ventilation system based on multi-level neural network. In Circuits, Communications and Systems. In IEEE PACCS., Sichuan, Chengdu, pp. 636–639

  7. Hrbcek, J., Spalek, J., Simak, V. (2010). Process model and implementation the multivariable model predictive control to ventilation system. In 8th IEEE SAMI., Herlany, Slovakia, pp. 211–214.

  8. Li, Y., Ling, L., & Chen, J. (2015). Combined grey prediction fuzzy control law with application to road tunnel ventilation system. Journal of Applied Research and Technology, 13(2), 313–320.

    Article  Google Scholar 

  9. Karakas, E. (2003). The control of highway tunnel ventilation using fuzzy logic. Engineering Applications of Artificial Intelligence, 16, 717–721.

    Article  Google Scholar 

  10. Du, P. Y. & Luo, X. P. (2010). The Research of urban road tunnel longitudinal ventilation control based on RBF neural network. In 2st IITA-GRS., Qingdao, Shandong, pp. 85–87.

  11. Mu, Q. X. & Zheng, X. (2010). The tunnel ventilation control based on iterative learning scheme. In 2st IITA-GRS., Qingdao, Shandong, pp. 306–309.

  12. Jang, H. M., & Chen, F. (2002). On the determination of the aerodynamic coefficients of highway tunnels. Journal of Wind Engineering and Industrial Aerodynamics, 90, 869–896.

    Article  Google Scholar 

  13. Tan, Z., Xia, Y., Yang, Q., & Zhou, G. (2015). Adaptive fine pollutant discharge control for motor vehicles tunnels under traffic state transition. IET Intelligent Transport Systems, 9(8), 783–791.

    Article  Google Scholar 

  14. Kuesel, T. R., King, E. H., Bickel, J. O. (2012). Tunnel engineering handbook. Springer Science & Business Media.

  15. Tan, Z., Huang, Z. Y., Wu, K., Xu, L. T. (2012). Simulation analysis of longitudinal ventilation system with jet fan speed control for MPC strategy in a road tunnel. In 15th IEEE International Conference on Intelligent Transportation Systems (ITSC), pp. 1471–1476.

  16. Igelnik, B., & Pao, Y. H. (1995). Stochastic choice of basis functions in adaptive function approximation and the functional-link net. IEEE Neural Networks, 6, 1320–1329.

    Article  Google Scholar 

  17. Si, J., Member, S., & Wang, Y. (2001). On-line learning control by association and reinforcement. IEEE Neural Networks, 12, 264–276.

    Article  Google Scholar 

  18. Yang, Q., & Jagannathan, S. (2012). Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators. IEEE Transactions on Systems, Man, and Cybernetics. Part B, 42(2), 377–90.

    Article  Google Scholar 

  19. Yang, Q., Vance, J. B., & Jagannathan, S. (2008). Control of nonaffine nonlinear discrete-time systems using reinforcement-learning-based linearly parameterized neural networks. IEEE Transactions on Systems, Man, and Cybernetics. Part B, 38, 994–1001.

    Article  Google Scholar 

Download references

Acknowledgments

This work was financially supported by the Project “Research on key technology of large-span municipal tunnel construction and operation under complicated environment”.

Author information

Authors and Affiliations

  1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, People’s Republic of China

    Ke Wu, Cheng Kang, Xin Zhang & Zhiyi Huang

  2. College of Control Science and Engineering, Zhejiang University, Hangzhou, People’s Republic of China

    Qinmin Yang

Authors
  1. Ke Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qinmin Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cheng Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhiyi Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qinmin Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, K., Yang, Q., Kang, C. et al. Adaptive Critic Design Based Control of Tunnel Ventilation System with Variable Jet Speed. J Sign Process Syst 86, 269–278 (2017). https://doi.org/10.1007/s11265-016-1123-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11265-016-1123-8

Keywords

Search

Navigation