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Experimental evaluation of a fuzzy logic controller on a quarter car test rig

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Abstract

This paper considers the experimental investigation of a multiple-input single-output fuzzy logic controller on an active suspension system based on a quarter car test rig. Prior to implementation of the controller, the quarter car test rig is described in detail. Afterward, the structure and design of the implemented fuzzy logic controller is presented. In this study, fuzzy logic control is preferred, since it does not require the exact mathematical model of the system and allows using expert knowledge about vehicle suspensions. Experimental results are presented and discussed via extensive time and frequency responses. Classical fuzzy logic controller is also utilized for comparison. Time responses of sprung mass displacements and accelerations, suspension deflections and actuator forces are compared for passive system and active controllers. Finally, the frequency responses of sprung mass displacements and accelerations are also compared. From the results it is deduced that the multiple-input single-output fuzzy logic controller performed well when compared with passive and classical fuzzy logic controlled systems.

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Abbreviations

e :

Error

FLC:

Fuzzy logic controller

k 1 :

Tire stiffness

k 2 :

Suspension stiffness

m 1 :

Unsprung mass

m 2 :

Sprung mass

NB:

Negative big

N:

Negative

P:

Positive

PB:

Positive big

RMS:

Root mean square

SF:

Scaling factor

u :

Active control force (signal)

y 0 :

Road input

y 1 :

Vertical displacement of the unsprung mass

y 2, \(\dot{y}_{2}\), \(\ddot{y}_{2}\) :

Vertical displacement, velocity and acceleration of the sprung mass

y 2 − y 1 :

Suspension deflection (travel)

Z:

Zero

α :

Weighing factor

1/τ :

Filter cutoff frequency

References

  1. Smith MC, Wang FC (2002) Controller parameterization for disturbance response decoupling: application to vehicle active suspension control. IEEE Trans Contr Syst Technol 10:393–407

    Article  Google Scholar 

  2. Swevers J, Lauwerys C, Vandersmissen B, Maes M, Reybrouck K, Sas P (2007) A model-free control structure for the on-line tuning of the semi-active suspension of a passenger car. Mech Syst Signal Process 21:1422–1436

    Article  Google Scholar 

  3. Rauh J, Ammon D (2011) System dynamics of electrified vehicles: some facts, thoughts, and challenges. Veh Syst Dyn 49:1005–1020

    Article  Google Scholar 

  4. Moradi M, Fekih A (2014) Adaptive PID-sliding-mode fault-tolerant control approach for vehicle suspension systems subject to actuator faults. IEEE Trans Veh Technol 63:1041–1054

    Article  Google Scholar 

  5. Silveira M, Pontes BR, Balthazar JM (2014) Use of nonlinear asymmetrical shock absorber to improve comfort on passenger vehicles. J Sound Vib 333:2114–2129

    Article  Google Scholar 

  6. Yagiz N, Hacioglu Y, Taskin Y (2008) Fuzzy sliding-mode control of active suspensions. IEEE Trans Ind Electron 55:3883–3890

    Article  Google Scholar 

  7. Garcia-Rodriguez C, Cortes-Romero JA, Sira-Ramirez H (2009) Algebraic identification and discontinuous control for trajectory tracking in a perturbed 1-DOF suspension system. IEEE Trans Ind Electron 56:3665–3674

    Article  Google Scholar 

  8. Lin J, Lian R-J (2011) Intelligent control of active suspension systems. IEEE Trans Ind Electron 58:618–628

    Article  Google Scholar 

  9. Lajqi S, Pehan S (2012) Designs and optimizations of active and semi-active non-linear suspension systems for a terrain vehicle. Stroj Vestnik-J Mech Eng 58:732–743

    Article  Google Scholar 

  10. Sun W, Zhao Y, Li J, Zhang L, Gao H (2012) Active suspension control with frequency band constraints and actuator input delay. IEEE Trans Ind Electron 59:530–537

    Article  Google Scholar 

  11. Ahmadian M, Pare CA (2000) A quarter-car experimental analysis of alternative semiactive control methods. J Intell Mater Syst Struct 11:604–612

    Article  Google Scholar 

  12. Lauwerys C, Swevers J, Sas P (2005) Robust linear control of an active suspension on a quarter car test-rig. Control Eng Pract 13:577–586

    Article  Google Scholar 

  13. Lee S, W-j Kim (2010) Active suspension control with direct-drive tubular linear brushless permanent-magnet motor. IEEE Trans Contr Syst Technol 18:859–870

    Article  Google Scholar 

  14. Lian R-J (2013) Enhanced adaptive self-organizing fuzzy sliding-mode controller for active suspension systems. IEEE Trans Ind Electron 60:958–968

    Article  Google Scholar 

  15. J-l Yao, W-k Shi, J-q Zheng, H-p Zhou (2013) Development of a sliding mode controller for semi-active vehicle suspensions. J Vib Control 19:1152–1160

    Article  Google Scholar 

  16. van der Sande TPJ, Gysen BLJ, Besselink IJM, Paulides JJH, Lomonova EA, Nijmeijer H (2013) Robust control of an electromagnetic active suspension system: simulations and measurements. Mechatronics 23:204–212

    Article  Google Scholar 

  17. Lin J, Cheng KWE, Zhang Z, Cheung NC, Xue X, Ng TW (2013) Active suspension system based on linear switched reluctance actuator and control schemes. IEEE Trans Veh Technol 62:562–572

    Article  Google Scholar 

  18. Snamina J, Kowal J, Orkisz P (2013) Active suspension based on low dynamic stiffness. Acta Phys Pol A 123:1118–1122

    Article  Google Scholar 

  19. Chen H, Long C, Yuan C-C, Jiang H-B (2013) Non-linear modelling and control of semi-active suspensions with variable damping. Veh Syst Dyn 51:1568–1587

    Article  Google Scholar 

  20. Sunwoo M, Cheok KC, Huang NJ (1991) Model reference adaptive control for vehicle active suspension systems. IEEE Trans Ind Electron 38:217–222

    Article  Google Scholar 

  21. Chen H, Guo K-H (2005) Constrained H∞ control of active suspensions: an LMI approach. IEEE Trans Contr Syst Technol 13:412–421

    Article  Google Scholar 

  22. Onat C, Kucukdemiral IB, Sivrioglu S, Yuksek I, Cansever G (2009) LPV gain-scheduling controller design for a non-linear quarter-vehicle active suspension system. Trans Inst Meas Control 31:71–95

    Article  MATH  Google Scholar 

  23. Fei J, Xin M (2012) Robust adaptive sliding mode controller for semi-active vehicle suspension system. Int J Innov Comput Inf Control 8:691–700

    Google Scholar 

  24. Félix-Herrán LC, Mehdi D, de Rodríguez-Ortiz JJ, Soto R, Ramírez-Mendoza R (2012) H∞ control of a suspension with a magnetorheological damper. Int J Control 85:1026–1038

    Article  MathSciNet  MATH  Google Scholar 

  25. Yeh F-K, Chen Y-Y (2013) Semi-active bicycle suspension fork using adaptive sliding mode control. J Vib Control 19:834–846

    Article  MathSciNet  MATH  Google Scholar 

  26. Soliman HM, Bajabaa NS (2013) Robust guaranteed-cost control with regional pole placement of active suspensions. J Vib Control 19:1170–1186

    Article  MathSciNet  MATH  Google Scholar 

  27. Canale M, Milanese M, Novara C (2006) Semi-active suspension control using “Fast” model-predictive techniques. IEEE Trans Contr Syst Technol 14:1034–1046

    Article  Google Scholar 

  28. Demir O, Keskin I, Cetin S (2012) Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach. Nonlinear Dyn 67:2139–2151

    Article  Google Scholar 

  29. Li H, Yu J, Hilton C, Liu H (2013) Adaptive sliding-mode control for nonlinear active suspension vehicle systems using T-S fuzzy approach. IEEE Trans Ind Electron 60:3328–3338

    Article  Google Scholar 

  30. Yagiz N, Hacioglu Y (2008) Backstepping control of a vehicle with active suspensions. Control Eng Pract 16:1457–1467

    Article  Google Scholar 

  31. Zhang G, Zhang Y, Yu F (2013) Active suspension robust control based on main/torque-tracking loop structure. J Vib Control 19:1123–1138

    Article  Google Scholar 

  32. Zhang G, Zhang Y, Yu F (2013) μ -Synthesis controller design for a DC-motor-based active suspension with parametric uncertainties. J Vib Control 19:585–604

    Article  Google Scholar 

  33. Jayachandran R, Krishnapillai S (2013) Modeling and optimization of passive and semi-active suspension systems for passenger cars to improve ride comfort and isolate engine vibration. J Vib Control 19:1471–1479

    Article  Google Scholar 

  34. Zhang Y, Alleyne A (2005) A practical and effective approach to active suspension control. Veh Syst Dyn 43:305–330

    Article  Google Scholar 

  35. Guclu R (2003) Active control of seat vibrations of a vehicle model using various suspension alternatives. Turk J Eng Environ Sci 27:361–373

    Google Scholar 

  36. Hacioglu Y, Arslan YZ, Yagiz N (2008) PI + PD type fuzzy logic controlled dual-arm robot in load transfer. Stroj Vestnik-J Mech Eng 54:347–355

    Google Scholar 

  37. Li S, Chen S, Liu B, Li Y, Liang Y (2012) Decentralized kinematic control of a class of collaborative redundant manipulators via recurrent neural networks. Neurocomputing 91:1–10

    Article  Google Scholar 

  38. Li S, Li Y, Liu B, Murray T (2012) Model-free control of Lorenz chaos using an approximate optimal control strategy. Commun Nonlinear Sci Numer Simul 17:4891–4900

    Article  MathSciNet  MATH  Google Scholar 

  39. Foda SG (2000) Fuzzy control of a quarter-car suspension system. In: Proceedings of the 12th International Conference on Microelectronics, p 231–234

  40. Sharkawy AB (2005) Fuzzy and adaptive fuzzy control for the automobiles’ active suspension system. Veh Syst Dyn 43(11):795–806

    Article  Google Scholar 

  41. Sakman LE, Guclu R, Yagiz N (2005) Fuzzy logic control of vehicle suspensions with dry friction nonlinearity. Sadhana 30(5):649–659

    Article  Google Scholar 

  42. Salem MMM, Aly AA (2009) Fuzzy control of a quarter-car suspension system. Int J Comput Electr Autom Control Inf Eng 3(5):1276–1281

    Google Scholar 

  43. Golob M (2001) Decomposed fuzzy proportional-integral-derivative controllers. Appl Soft Comput 1(3):201–214

    Article  Google Scholar 

  44. Taskin Y, Hacioglu Y, Yagiz N (2007) The use of fuzzy-logic control to improve the ride comfort of vehicles. Stroj Vestnik-J Mech Eng 53(4):233–240

    Google Scholar 

  45. Quanser, Active Suspension-User’s Manual. Revision 2.1. Quanser Consulting Inc., Ontario, Canada

  46. Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    Article  MATH  Google Scholar 

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Correspondence to Yuksel Hacioglu.

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Technical Editor: Kátia Lucchesi Cavalca Dedini.

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Taskin, Y., Hacioglu, Y. & Yagiz, N. Experimental evaluation of a fuzzy logic controller on a quarter car test rig. J Braz. Soc. Mech. Sci. Eng. 39, 2433–2445 (2017). https://doi.org/10.1007/s40430-016-0637-0

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  • DOI: https://doi.org/10.1007/s40430-016-0637-0

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