Abstract
To improve the performance of the magnetorheological (MR) semi-active suspension system, a fractional-order sliding mode control (FOSMC) strategy is proposed to address the nonlinear problems caused by the external disturbances and changes in parameters of system. Firstly, The MR damper designed by the research team is applied to the vehicle’s MR semi-active suspension, and a one-fourth semi-active suspension dynamic model is established. Mechanical performance tests of the MR damper are conducted through tensile experiments, confirming its satisfactory mechanical characteristics and suitability for meeting the output damping force requirements of the vehicle’s semi-active suspension. To accurately convert the computed control force into the MR damper’s control current, an adaptive neuro-fuzzy inference system (ANFIS) inverse model of the MR damper is constructed. Comparative data analysis demonstrates the inverse model’s high accuracy and its ability to effectively meet the controller’s requirements. The proposed FOSMC strategy effectively reduces the chattering phenomenon associated with sliding mode control, leading to improved vibration-damping performance of the suspension. Subsequently, a simulation model and experimental platform are utilized to evaluate the performance of the proposed controller. Experimental results indicate that the FOSMC-controlled suspension outperforms the passive suspension, achieving significant reductions in body acceleration, suspension dynamic travel, and tire dynamic displacement by 27.4%, 7.3%, and 17.39%, respectively. Similarly, the semi-active suspension controlled by sliding mode control (SMC) also shows improvements compared to the passive suspension, with reductions in body acceleration, suspension dynamic travel, and tire dynamic displacement by 20.9%, 4.3%, and 5.2%, respectively. In summary, the FOSMC-controlled MR semi-active suspension exhibits superior damping performance compared to both the passive suspension and the SMC-controlled semi-active suspension, demonstrating the effectiveness of the proposed FOSMC controller.
Keywords
Get full access to this article
View all access options for this article.
