Skip to main content
SpringerLink
Log in

Fuzzy Preview Control for Half-vehicle Electro-hydraulic Suspension System

  • Regular Papers
  • Intelligent Control and Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

This paper proposes a new fuzzy preview control method for an electro-hydraulic suspension system to further improve the suspension performance and extend the results to practical situations that use the actual actuator in a preview suspension system. A new augmented system that includes hydraulic actuators and preview information of road disturbances is proposed and described by the T-S fuzzy system. Based on the parallel distributed compensation (PDC) and multi-objective H∞/GH2 control design scheme, the fuzzy preview controller is designed for a newly obtained model in which the closed-loop suspension system is asymptotically stable with guaranteed robust performance in the H∞ sense. The simulation results clearly validate the effectiveness of the proposed controllers in terms of its suspension performance.

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

Similar content being viewed by others

References

  1. D. Hrovat, “Survey of advanced suspension developments and related optimal control applications,” Automatica, vol. 33, no. 10, pp. 1781–1817, 1997.

    Article  MathSciNet  MATH  Google Scholar 

  2. R. A. Williams, “Automotive active suspensions,” Proc. Inst. Mech. Eng. Part D: Journ. Automobile Eng., vol. 211, pp. 415–444, 1997.

    Article  Google Scholar 

  3. M. Yamashita, K. Fujimori, K. Hayakawa, and H. Kimura, “Application of H ∞ control to active suspension systems,” Autometica, vol. 30, no.11, pp. 1717–1729, 1994.

    Article  Google Scholar 

  4. W. Sun, Y. Zhao, J. Li, L. Zhang, and H. Gao, “Active suspension control with frequency band constraints and actuator input delay,” IEEE Trans. Ind. Electron., vol. 59, no. 1, pp. 530–537, 2012.

    Article  Google Scholar 

  5. J. Cao, H. Liu, P. Li, and D. Brown, “State of the art in vehicle active suspension adaptive control systems based on intelligent methodologies,” IEEE Trans. Intell. Transp. Syst., vol. 9, no. 3, pp. 392–405, 2008.

    Article  Google Scholar 

  6. J. Wang and D. A. Wilson, “Mixed GL 2/H 2/GH 2 control with pole placement and its application to vehicle suspension systems,” Int Journ. Contr., vol. 74, no. 13, pp. 1353–1369, 2001.

    Article  Google Scholar 

  7. H. Gao, W. Sun, and P. Shi, “Robust sampled-data H ∞ control for vehicle active suspension systems,” IEEE Trans. Contr. Syst. Technol., vol. 18, no. 1, pp. 238–245, 2010.

    Article  Google Scholar 

  8. H. Lim, S. H. Lee, B. R. So, and B. J. Yi, “Design of a New 6-DOF Parallel Mechanism with a Suspended Platform,” Int Journ. Contr. Autom. and Syst., vol. 13, no. 4, pp. 942–950, 2015.

    Article  Google Scholar 

  9. H. Du and N. Zang, “H ∞ control of active vehicle suspension with actuator time delay,” Journ. Sound Vib., vol. 301, no. 1–2, pp. 236–252, 2007.

    Article  MathSciNet  Google Scholar 

  10. H. Chen and K. Guo, “Constrained H ∞ control of active suspensions: an LMI approach,” IEEE Trans. Contr. Syst. Technol., vol. 13, no. 3, pp. 412–421, 2005.

    Article  Google Scholar 

  11. H. D. Choi, C. K. Ahn, M. T. Lim, and M. K. Song, “Dynamic output-feedback H ∞ control for active half-vehicle suspension systems with time-varying input delay,” Int Journ. Contr. Autom. and Syst., vol. 14, no. 1, pp. 59–68, 2016.

    Article  Google Scholar 

  12. S. Boyd, L. E. Ghaoui, E. Feron, and V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory, Philadelphia, PA, USA: SIAM, 1994.

    Book  MATH  Google Scholar 

  13. C. Kaddissi, J. P. Kenne, and M. Saad, “Identification and real-time control of an electrohydraulic servo system based on nonlinear backstepping,” IEEE/ASME Trans. Mechatronics, vol. 12, no. 1, pp. 12–22, 2007.

    Article  Google Scholar 

  14. A. Alleyne and J. K. Hedrick, “Nonlinear adaptive control of active suspensions,” IEEE Trans. Contr. Syst. Technol., vol. 3, no. 1, pp. 94–101, 1995.

    Article  Google Scholar 

  15. A. Alleyne, P. D. Neuhaus, and J. K. Hedrick, “Application of nonlinear control theory to electronically controlled suspensions,” Vehicle Syst. Dyn., vol. 22, no. 5, pp. 309–320, 1993.

    Article  Google Scholar 

  16. A. G. Thompson and B. R. Davis, “Force control in electrohydraulic active suspensions revisited,” Vehicle Syst. Dyn., vol. 35, no. 3, pp. 217–222, 2001.

    Article  Google Scholar 

  17. P. C. Chen and A. C. Huang, “Adaptive sliding control of active suspension systems with uncertain hydraulic actuator dynamics,” Vehicle Syst. Dyn., vol. 44, no. 5, pp. 357–368, 2006.

    Article  Google Scholar 

  18. H. Du and N. Zhang, “Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint,” IEEE Trans. Fuzzy Syst., vol. 17, no. 2, pp. 343–356, 2009.

    Article  Google Scholar 

  19. H. Du and N. Zhang, “Takagi-Sugeno fuzzy control scheme for electrohydraulic active suspensions,” Control and Cybernetics, vol. 39, no. 4, pp. 1095–1115, 2010.

    MATH  Google Scholar 

  20. H. Pan, W. Sun, X. Jing, H. Gao, and J. Yao, “Adaptive tracking control for active suspension systems with nonideal actuators,” Journal of Sound and Vibration, vol. 399, no. 7, pp. 2–20, 2017.

    Article  Google Scholar 

  21. T. Takagi and M. Sugeno, “Fuzzy identification of systems and its application to modeling and control,” IEEE Trans. Syst., Man, Cybern., vol. 15, pp. 116–132, 1985.

    Article  MATH  Google Scholar 

  22. G. Feng, “A survey on analysis and design of model-based fuzzy control systems,” IEEE Trans. Fuzzy. Syst., vol. 14, no. 5, pp. 676–697, 2006.

    Article  Google Scholar 

  23. H. Karimi, B. Moshiri, and C. Lucas, “Robust fuzzy linear control of a class of stochastic nonlinear time-delay systems,” Nonlinear Dyn. Syst. Theory, vol. 4, no. 3, pp. 317–332, 2004.

    MathSciNet  MATH  Google Scholar 

  24. S. Nguang and P. Shi, “H ∞ fuzzy output feedback control design for nonlinear systems: An LMI approach,” IEEE Trans. Fuzzy. Syst., vol. 11, no. 3, pp. 331–340, 2003.

    Article  Google Scholar 

  25. H. Li, J. Yu, C. Hilton, and H. Liu, “Adaptive sliding-mode control for nonlinear active suspension vehicle systems using T-S fuzzy approach,” IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3328–3338, 2013.

    Article  Google Scholar 

  26. H. D. Choi, C. K. Ahn, P. Shi, L. Wu, and M. T. Lim, “Dynamic output-feedback dissipative control for T-S fuzzy systems with time-varying input delay and output constraints,” IEEE Trans. Fuzzy Syst., vol. 25, no. 3, pp. 511–526, 2017.

    Article  Google Scholar 

  27. H. Du and N. Zhang, “Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint,” IEEE Trans. Fuzzy Syst., vol. 17, no. 2, pp. 343–356, 2009.

    Article  Google Scholar 

  28. H. Li, H. Liu, H. Gao, and P. Shi, “Reliable fuzzy control for active suspension systems with actuator delay and fault,” IEEE Trans. Fuzzy Syst., vol. 20, no. 2, pp. 342–357, 2012.

    Article  Google Scholar 

  29. S. Bououden, M. Chadli, and H. R. Karimi, “A robust predictive control design for nonlinear active suspension systems,” Asian Jour. of Contr., vol. 18, no. 1, pp.122–132, 2016.

    Article  MathSciNet  MATH  Google Scholar 

  30. E. Bender, “Optimum linear preview control with application to vehicle suspension,” Jour. Basic Engineering, vol. 90, no. 2, pp. 213–221, 1968.

    Article  Google Scholar 

  31. M. Tomizuka, “Optimal continuous finite preview problem,” IEEE Trans. Autom. Contr., vol.21, no. 3, pp. 362–365, 1975.

    Article  MathSciNet  MATH  Google Scholar 

  32. A. Hac, “Optimal linear preview control of active vehicle suspension,” Vehicle Syst. Dyn., vol. 21, no. 1, pp. 167–195, 1992.

    Article  Google Scholar 

  33. J. Marzbanrad, G. Ahmadi, H. Zohoor, and Y. Hojjat, “Stochastic optimal preview control of a vehicle suspension,” Jour. Sound Vib., vol. 275, no. 3–5, pp. 973–990, 2004.

    Article  MathSciNet  MATH  Google Scholar 

  34. H. Roh and Y. Park, “Stochastic optimal preview control of an active vehicle suspension,” Jour. Sound Vib., vol. 220, no. 2, pp. 313–330, 1999.

    Article  MATH  Google Scholar 

  35. M. Elmadany, Z. Abduljabbar, and M. Foda, “Optimal preview control of active suspensions with integral constraint,” Jour. Sound Vib., vol. 9, no. 12, pp. 1377–1400, 2003.

    Google Scholar 

  36. Z. Xie, P. Wong, X. Huang, and H. Wong, “Design of an active vehicle suspension based on an enhanced PID control with wheelbase preview and tuning using genetic algorithm,” Jour. the Chinese Society of Mechanical Engineers, vol. 33, pp. 103–112, 2012.

    Google Scholar 

  37. K. Zhou, P. P. Khargonekar, J. Stoustrup, and H. H. Niemann, “Robust performance of systems with structured uncertainties in state space,” Automatica, vol. 31, no.2, pp. 249–255, 1995.

    Article  MathSciNet  MATH  Google Scholar 

  38. A. Akbari, G. Koch, E. Pellegrini, and B. Lohmann, “Multi-objective preview control of active vehicle suspensions: experimental results,” Advanced Computer Contr., vol. 3, pp. 497–502, 2010.

    Google Scholar 

  39. A. Akbari and B. Lohmann, “Output feedback H ∞=GH2 preview control of active vehicle suspensions: a comparison study of LQG preview,” Vehicle Syst. Dyn., vol. 48, no. 12, pp. 1475–1494, 2010.

    Article  Google Scholar 

  40. C. Gohrle, A. Schindler, A. Wagner, and O. Sawodny, “Design and vehicle implementation of preview active suspension controllers,” IEEE Trans. Contr. Syst. Techn., vol. 22, no. 3, pp. 1135–1142, 2014.

    Article  Google Scholar 

  41. Y. J. Xu and F. C. Liao, “Preview control for a class of time varying discrete systems with input time-delay,” Control and Decision, vol. 28, no. 3, pp. 466–470, 2013.

    Google Scholar 

  42. I. Youn, M. A. Khan, N. Uddin, E. Youn, and M. Tomizuka, “Road disturbance estimation for the optimal preview control of an active suspension systems based on tracked vehicle model,” Intern. Journ. Automotive Techn., vol. 18, no. 2, pp. 307–316, 2017.

    Article  Google Scholar 

  43. R. Alur, C. Belta, F. Ivancic, V. Kumar, M. Mintz, G.J. Pappas, H. Rubin, and J. Schug, “Hybrid modeling and simulation of biomolecular networks, in: Hybrid Systems: Computation and Control,” Lecture Notes in Computer Science, vol. 2034, pp. 19–32, 2001.

    Article  MATH  Google Scholar 

  44. P. Gahinet, A. Nemirovski, A. J. Laub, and M. Chilali, LMI Control Toolbox, The Mathwork INC., 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Hyundai Mobis, 17-2, Mabuk-ro 240beon-gil, Giheung-gu, Yongin-si, Gyeonggi-do, 16891, Korea

    Hyun Duck Choi

  2. School of Electrical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Korea

    Chang Joo Lee & Myo Taeg Lim

Authors
  1. Hyun Duck Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chang Joo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Myo Taeg Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Myo Taeg Lim.

Additional information

Recommended by Associate Editor Ho Jae Lee under the direction of Editor Euntai Kim. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant No. NRF-2016R1D1A1B01016071).

Hyun Duck Choi received the B.S. and integrated M.S/Ph.D. degrees in electrical engineering from Korea University, Seoul, South Korea, in 2011 and 2017, respectively. Since 2017, he has been a Senior Research Engineer with the Hyundai Mobis. His current research interests include fuzzy systems, neural networks, robust control, finite impulse response filters, finite memory controls, nonlinear systems, and their application to vehicle suspension systems.

Chang Joo Lee received his B.S. degree in the School of Electronic Engineering from Soongsil University, Seoul, Korea in 2012. Since 2012, he has been a Ph.D. candidate in the School of Electrical Engineering, Korea University. His current research interests include fuzzy systems, neural networks, robust control, FIR filters, finite memory controls, nonlinear systems, and advanced driver assistance systems.

Myo Taeg Lim received his B.S. and M.S. degrees in Electrical Engineering from Korea University, Korea, in 1985 and 1987, respectively. He also received M.S. and Ph.D. degrees in Electrical Engineering from Rutgers University, NJ, USA, in 1990 and 1994, respectively. He was a Senior Research Engineer, Samsung Advanced Institute of Technology and an Assistant Professor in the Department of Control and Instrumentation, National Changwon University, Korea. Since 1996, he has been a Professor in the School of Electrical Engineering at Korea University. His research interests include optimal and robust control, vision based motion control, and autonomous mobile robots. He is the author or coauthor of more than 80 journal papers and two books (Optimal Control of Singularly Perturbed Linear Systems and Application: High-Accuracy Techniques, Control Engineering Series, Marcel Dekker, New York, 2001; Optimal Control: Weakly Coupled Systems and Applications, Automation and Control Engineering Series, CRC Press, New York, 2009). Dr. Lim currently serves as an Editor for International Journal of Control, Automation, and Systems. He is a Fellow of the Institute of Control, Robotics and Systems, and a member of the IEEE and Korea Institute of Electrical Engineers.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Choi, H.D., Lee, C.J. & Lim, M.T. Fuzzy Preview Control for Half-vehicle Electro-hydraulic Suspension System. Int. J. Control Autom. Syst. 16, 2489–2500 (2018). https://doi.org/10.1007/s12555-017-0663-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-017-0663-4

Keywords

Search

Navigation