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Fractional-Order PID Control of Hydraulic Thrust System for Tunneling Boring Machine

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Intelligent Robotics and Applications (ICIRA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8103))

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Abstract

The hydraulic thrust system is a major system of tunneling boring machine (TBM). It is known that the flow rate is dramatically fluctuant under conventional PID pressure control. At the same time the pressure is fluctuant when applying conventional PID flow rate control. Considering the dynamic performance of the hydraulic thrust system, we make use of fractional calculus which results in more satisfactory results. The fractional-order PID controller is adopted to control the hydraulic thrust system in this paper. The simulation is carried out with the AMESim software and the MATLAB/Simulink tool. The result shows that flow and pressure control using fractional-order PID controllers can reduce the flow rate and pressure fluctuation and make the flow rate and pressure track the set value faster.

This work was supported by National 973 Program of China (No. 2013CB035406), National Natural Science Foundation of China (No. 61174059, 60934007, 61233004),Research Project of Shanghai Municipal Economic and Informatization Commission.

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References

  1. Okubo, S., Fukui, K., Chen, W.: Expert system for applicability of tunnel boring machines in Japan. Rock Mechanics and Rock Engineering 36(4), 305–322 (2003)

    Article  Google Scholar 

  2. Kunzhou, H., Liping, X., Dezhi, R.: Hydraulic thrust system researchbased on single neuron adaptive PID controlfor double shield TBM. Fluid Power Transmission and Control (1), 39–41 (2010)

    Google Scholar 

  3. Maidl, B., Schmid, L., Ritz, W., et al.: Hardrock tunnel boring machines. Wiley-VCH (2008)

    Google Scholar 

  4. Huayong, Y., Hu, S., Guofang, G., et al.: Electro-hydraulic proportional control of thrust system for shield tunneling machine. Automation in Construction 18(7), 950–956 (2009)

    Article  Google Scholar 

  5. Monje, C.A., Vinagre, B.M., Feliu, V., et al.: Tuning and auto-tuning of fractional order controllers for industry applications. Control Engineering Practice 16(7), 798–812 (2008)

    Article  Google Scholar 

  6. Manabe, S.: Early development of fractional order control, pp. 2–6

    Google Scholar 

  7. Samko, S.G., Kilbas, A.A., Marichev, O.I.: Fractional Integrals and Derivatives: Theory and Applications, Gordon and Breach, Yverdon (1993)

    Google Scholar 

  8. Zhou, C., Gao, H.-B., Gao, L., et al.: Particle Swarm Optimization (PSO) Algorithm. Application Research of Computers 12, 7–11 (2003)

    Google Scholar 

  9. Hongqing, F., Zuyi, S.: Optimal hydraulic turbo generators PID governor tuning with an improved particle swarm optimization algorithm. Proceedings of the CSEE 25(22), 120–124 (2005)

    Google Scholar 

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Fei, L., Wang, J., Zhang, L., Ge, Y., Li, K. (2013). Fractional-Order PID Control of Hydraulic Thrust System for Tunneling Boring Machine. In: Lee, J., Lee, M.C., Liu, H., Ryu, JH. (eds) Intelligent Robotics and Applications. ICIRA 2013. Lecture Notes in Computer Science(), vol 8103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40849-6_48

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  • DOI: https://doi.org/10.1007/978-3-642-40849-6_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40848-9

  • Online ISBN: 978-3-642-40849-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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