access icon free Robust fault-tolerant H output feedback control of active suspension and dynamic vibration absorber with finite-frequency constraint

Currently, majorities of the robust H control methods are designed for active suspensions, and seldom take the active control of the in-wheel-motor (IWM) into consideration for IWM driven electric vehicles (EVs). In this study, a robust fault-tolerant H output feedback control strategy with finite-frequency constraint is proposed to synchronously control the active suspension and dynamic vibration absorber (DVA) for IWM driven EVs. Firstly, a DVA-based electric wheel model is developed, in which the IWM is designed as DVA. Furthermore, the spring-damper parameters of the DVA are matched by using particle swarm optimisation (PSO). Then, the robust fault-tolerant H output feedback control strategy is developed based on linear matrix inequality, in which the finite-frequency constraint is designed in the resonance frequency range of sprung mass. Finally, simulation results validate that the PSO can effectively optimise the spring-damper parameters of the DVA. The robust fault-tolerant H output feedback control with finite-frequency constraint can effectively improve the ride comfort and suppress the vertical vibration caused by IWM compared with entire frequency constraint. Meanwhile, the fault-tolerant effectiveness of the proposed method is demonstrated under the actuator faults concerning the actuator force noises and losses.

Inspec keywords: electric vehicles; vibration control; particle swarm optimisation; linear matrix inequalities; actuators; suspensions (mechanical components); springs (mechanical); control system synthesis; wheels; vehicle dynamics; robust control; vibrations; feedback; fault tolerant control; shock absorbers

Other keywords: IWM driven electric vehicles; finite-frequency constraint; linear matrix inequality; active suspension control; frequency constraint; sprung mass; robust fault-tolerant H∞ output feedback control strategy; actuator force noises; PSO; dynamic vibration absorber; IWM driven EVs; resonance frequency range; DVA-based electric wheel model; fault-tolerant effectiveness; spring-damper parameters; in-wheel-motor; vertical vibration suppression; particle swarm optimisation

Subjects: Control system analysis and synthesis methods; Transportation; Algebra; Algebra; Vibrations and shock waves (mechanical engineering); Mechanical components; Mechanical variables control; Transportation system control; Optimal control; Optimisation; Optimisation techniques; Control technology and theory (production); Optimisation techniques; Stability in control theory; Algebra; Actuating and final control devices; Vehicle mechanics

References

    1. 1)
      • 25. Wang, R., Jing, H., Karimi, H.R., et al: ‘Robust fault-tolerant H control of active suspension systems with finite-frequency constraint’, Mech. Syst. Signal Process., 2015, 62–63, pp. 341355.
    2. 2)
      • 26. Liu, M., Zhang, Y., Huang, J., et al: ‘Optimization control for dynamic vibration absorbers and active suspensions of in-wheel-motor-driven electric vehicles’, Proc. Inst. Mech. Eng. D, J. Automob. Eng., 2020, 234, (9), pp. 23772392.
    3. 3)
      • 14. Karnopp, D.: ‘How significant are transfer function relations and invariant points for a quarter car suspension model?’, Veh. Syst. Dyn., 2009, 47, (4), pp. 457464.
    4. 4)
      • 3. Chen, J., Shuai, Z., Zhang, H., et al: ‘Path following control of autonomous four-wheel-independent-drive electric vehicles via second-order sliding mode and nonlinear disturbance observer techniques’, IEEE Trans. Ind. Electron., 2020, pp. 11.
    5. 5)
      • 10. Wang, R., Jing, H., Yan, F., et al: ‘Optimization and finite-frequency H control of active suspensions in in-wheel motor driven electric ground vehicles’, J. Franklin Inst., 2015, 352, (2), pp. 468484.
    6. 6)
      • 8. Qin, Y., He, C., Shao, X., et al: ‘Vibration mitigation for in-wheel switched reluctance motor driven electric vehicle with dynamic vibration absorbing structures’, J. Sound Vib., 2018, 419, pp. 249267.
    7. 7)
      • 17. Choi, H.D., Ahn, C.K., Lim, M.T., et al: ‘Dynamic output-feedback H control for active half-vehicle suspension systems with time-varying input delay’, Int. J. Control Autom. Syst., 2016, 14, (1), pp. 5968.
    8. 8)
      • 15. Lee, H.-S., Choi, S.-B.: ‘Control and response characteristics of a magneto-rheological fluid damper for passenger vehicles’, J. Intell. Mater. Syst. Struct., 2000, 11, (1), pp. 8087.
    9. 9)
      • 11. Shao, X., Naghdy, F., Du, H., et al: ‘Output feedback H control for active suspension of in-wheel motor driven electric vehicle with control faults and input delay’, ISA Trans.., 2019, 92, pp. 94108.
    10. 10)
      • 31. Zhang, H., Mehr, A.S., Shi, Y.: ‘Improved robust energy-to-peak filtering for uncertain linear systems’, Signal Process., 2010, 90, (9), pp. 26672675.
    11. 11)
      • 20. Fallah, S., Khajepour, A., Fidan, B., et al: ‘Vehicle optimal torque vectoring using state-derivative feedback and linear matrix inequality’, IEEE Trans. Veh. Technol., 2013, 62, (4), pp. 15401552.
    12. 12)
      • 5. Shao, X., Naghdy, F., Du, H., et al: ‘Coupling effect between road excitation and an in-wheel switched reluctance motor on vehicle ride comfort and active suspension control’, J. Sound Vib., 2019, 443, pp. 683702.
    13. 13)
      • 6. Li, Z., Zheng, L., Gao, W., et al: ‘Electromechanical coupling mechanism and control strategy for in-wheel-motor-driven electric vehicles’, IEEE Trans. Ind. Electron., 2019, 66, (6), pp. 45244533.
    14. 14)
      • 32. Rubió-Massegú, J., Rossell, J.M., Karimi, H.R., et al: ‘Static output-feedback control under information structure constraints’, Automatica, 2013, 49, (1), pp. 313316.
    15. 15)
      • 18. Wang, G., Chen, C., Yu, S.: ‘Robust non-Fragile finite-frequency H static output-feedback control for active suspension systems’, Mech. Syst. Signal Process., 2017, 91, pp. 4156.
    16. 16)
      • 16. Sun, W., Gao, H., Kaynak, O.: ‘Finite frequency H control for vehicle active suspension systems’, IEEE Trans. Control Syst. Technol., 2011, 19, (2), pp. 416422.
    17. 17)
      • 9. Shao, X., Naghdy, F., Du, H.: ‘Reliable fuzzy H control for active suspension of in-wheel motor driven electric vehicles with dynamic damping’, Mech. Syst. Signal Process., 2017, 87, pp. 365383.
    18. 18)
      • 7. Li, Z., Zheng, L., Ren, Y., et al: ‘Multi-objective optimization of active suspension system in electric vehicle with in-wheel-motor against the negative electromechanical coupling effects’, Mech. Syst. Signal Process., 2019, 116, pp. 545565.
    19. 19)
      • 30. Zhang, H., Wang, R., Wang, J., et al: ‘Robust finite frequency H static-output-feedback control with application to vibration active control of structural systems’, Mechatronics. (Oxf), 2014, 24, (4), pp. 354366.
    20. 20)
      • 1. Cheng, S., Li, L., Chen, X., et al: ‘Model-predictive-control-based path tracking controller of autonomous vehicle considering parametric uncertainties and velocity-varying’, IEEE Trans. Ind. Electron., 2020, pp. 11.
    21. 21)
      • 27. Iwasaki, T., Hara, S.: ‘Generalized Kyp lemma: unified frequency domain inequalities with design applications’, IEEE Trans. Autom. Control, 2005, 50, (1), pp. 4159.
    22. 22)
      • 28. Apkarian, P., Tuan, H.D., Bernussou, J.: ‘Continuous-time analysis, eigenstructure assignment, and H/sub 2/synthesis with enhanced linear matrix inequalities (lmi) characterizations’, IEEE Trans. Autom. Control, 2001, 46, (12), pp. 19411946.
    23. 23)
      • 29. Ouellette, D.V.: ‘Schur complements and statistics’, Linear Algebra Appl., 1981, 36, pp. 187295.
    24. 24)
      • 23. Kong, Y., Zhao, D., Yang, B., et al: ‘Robust non-Fragile H ∞/L2-L∞ control of uncertain linear system with time-delay and application to vehicle active suspension’, Int. J. Robust Nonlinear Control, 2015, 25, (13), pp. 21222141.
    25. 25)
      • 19. Cheng, S., Li, L., Liu, C.-Z., et al: ‘Robust lmi-based H-infinite controller integrating afs and dyc of autonomous vehicles with parametric uncertainties’, IEEE Trans. Syst. Man Cybern. Syst., 2020, pp. 110.
    26. 26)
      • 21. Liu, M., Gu, F., Huang, J., et al: ‘Integration design and optimization control of a dynamic vibration absorber for electric wheels with in-wheel motor’, Energies, 2017, 10, (12), p. 2069.
    27. 27)
      • 22. Pan, H., Li, H., Sun, W., et al: ‘Adaptive fault-tolerant compensation control and its application to nonlinear suspension systems’, IEEE Trans. Syst. Man Cybern. Syst., 2020, 50, (5), pp. 17661776.
    28. 28)
      • 13. Zhang, H., Huang, X., Wang, J., et al: ‘Robust energy-to-peak sideslip angle estimation with applications to ground vehicles’, Mechatronics. (Oxf), 2015, 30, pp. 338347.
    29. 29)
      • 24. Jing, H., Wang, R., Li, C., et al: ‘Fault-tolerant control of active suspensions in in-wheel motor driven electric vehicles’, Int. J. Veh. Des., 2015, 68, (1-3) pp. 2236.
    30. 30)
      • 12. Karim Afshar, K., Javadi, A., Jahed-Motlagh, M.R.: ‘Robust H control of an active suspension system with actuator time delay by predictor feedback’, IET Control Theory Appl., 2018, 12, (7), pp. 10121023.
    31. 31)
      • 34. Badri, P., Amini, A., Sojoodi, M.: ‘Robust fixed-order dynamic output feedback controller design for nonlinear uncertain suspension system’, Mech. Syst. Signal Process., 2016, 80, pp. 137151.
    32. 32)
      • 2. Wang, Y., Wang, Z., Zhang, L., et al: ‘Lateral stability enhancement based on a novel sliding mode prediction control for a four-wheel-independently actuated electric vehicle’, IET Intell. Transp. Syst., 2019, 13, (1), pp. 124133.
    33. 33)
      • 4. Liu, M., Gu, F., Zhang, Y.: ‘Ride comfort optimization of in-wheel-motor electric vehicles with in-wheel vibration absorbers’, Energies, 2017, 10, (10), p. 1647.
    34. 34)
      • 33. Gahinet, P., Nemirovskii, A., Laub, A.J., et al: ‘The lmi control toolbox’. Proc. of 1994 33rd IEEE Conf. on Decision and Control, Lake Buena Vista, FL, USA, 1994.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2020.0364
Loading

Related content

content/journals/10.1049/iet-its.2020.0364
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading