Open AccessInvestigation of sliding mode control for nonlinear suspension systems with state estimation
Author(s) -
Xing Chen,
Sen Han,
Tianhong Luo,
Guanhua Du
Publication year - 2020
Publication title -
mechanics and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.256
H-Index - 18
eISSN - 2257-7777
pISSN - 2257-7750
DOI - 10.1051/meca/2020081
Subject(s) - control theory (sociology) , suspension (topology) , shock absorber , active suspension , nonlinear system , controller (irrigation) , sliding mode control , kalman filter , noise (video) , extended kalman filter , engineering , computer science , control (management) , mathematics , structural engineering , actuator , physics , agronomy , electrical engineering , quantum mechanics , artificial intelligence , homotopy , pure mathematics , image (mathematics) , biology
This paper presented a new control strategy for active suspension of nonlinear quarter-vehicle model. An active suspension controller designed for using sliding mode control with noise filtering. The Kalman filter (KF) predicted the state response of the nonlinear one-quarter automobile model, and the estimated values used for the design of the active control force. Finally, the shock absorption performance compared with the LQR controller and the passive suspension. The simulation results showed that the control method significantly improve the ride performance and safety of the vehicle.