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An effective projection-based nonlinear adaptive control strategy for heavy vehicle suspension with hysteretic leaf spring

Journal Article


Abstract


  • © 2020, Springer Nature B.V. A new nonlinear adaptive control strategy for electrohydraulic active suspensions with the hysteretic leaf spring is proposed to improve suspension performances of heavy vehicle. The nonlinear hysteresis property of leaf spring, described and experimentally validated with the Bouc–Wen model, is transformed into linear system by Takagi–Sugeno (T–S) fuzzy approach. Based on the derived T–S fuzzy model, a robust H∞ dynamic feedback control with adaptive gain is employed to generate the desired target forces for hydraulic actuators. A new projection-based adaptive control (PAC) law is further proposed for actuators to track the target forces under parametric uncertainties. The PAC law is derived based on the global asymptotic stability conditions of Lyapunov function for the obtained T–S fuzzy model with parametric uncertainties under inputs from both outputs of robust H∞ controller and errors of force tracking. The benefits of vehicle systems with PAC active suspension are compared to both sliding mode control (SMC) active suspension and passive suspension. The obtained results indicate that the PAC method can be able to cope with uncertainties and has better robustness than SMC method. Furthermore, the obtained results also indicate that the proposed nonlinear adaptive control strategy effectively improves the suspension performances of heavy vehicle with the hysteretic leaf spring.

UOW Authors


  •   Zhang, Jie (external author)
  •   Ding, Fei (external author)
  •   Zhang, Bangji (external author)
  •   Jiang, Chao (external author)
  •   Du, Haiping
  •   Li, Boyuan (external author)

Publication Date


  • 2020

Citation


  • J. Zhang, F. Ding, B. Zhang, C. Jiang, H. Du & B. Li, "An effective projection-based nonlinear adaptive control strategy for heavy vehicle suspension with hysteretic leaf spring," Nonlinear Dynamics, 2020.

Scopus Eid


  • 2-s2.0-85080879908

Place Of Publication


  • Netherlands

Abstract


  • © 2020, Springer Nature B.V. A new nonlinear adaptive control strategy for electrohydraulic active suspensions with the hysteretic leaf spring is proposed to improve suspension performances of heavy vehicle. The nonlinear hysteresis property of leaf spring, described and experimentally validated with the Bouc–Wen model, is transformed into linear system by Takagi–Sugeno (T–S) fuzzy approach. Based on the derived T–S fuzzy model, a robust H∞ dynamic feedback control with adaptive gain is employed to generate the desired target forces for hydraulic actuators. A new projection-based adaptive control (PAC) law is further proposed for actuators to track the target forces under parametric uncertainties. The PAC law is derived based on the global asymptotic stability conditions of Lyapunov function for the obtained T–S fuzzy model with parametric uncertainties under inputs from both outputs of robust H∞ controller and errors of force tracking. The benefits of vehicle systems with PAC active suspension are compared to both sliding mode control (SMC) active suspension and passive suspension. The obtained results indicate that the PAC method can be able to cope with uncertainties and has better robustness than SMC method. Furthermore, the obtained results also indicate that the proposed nonlinear adaptive control strategy effectively improves the suspension performances of heavy vehicle with the hysteretic leaf spring.

UOW Authors


  •   Zhang, Jie (external author)
  •   Ding, Fei (external author)
  •   Zhang, Bangji (external author)
  •   Jiang, Chao (external author)
  •   Du, Haiping
  •   Li, Boyuan (external author)

Publication Date


  • 2020

Citation


  • J. Zhang, F. Ding, B. Zhang, C. Jiang, H. Du & B. Li, "An effective projection-based nonlinear adaptive control strategy for heavy vehicle suspension with hysteretic leaf spring," Nonlinear Dynamics, 2020.

Scopus Eid


  • 2-s2.0-85080879908

Place Of Publication


  • Netherlands