2026-10-13T07:52:37Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34016327 2026-09-28T17:33:07Z category_4 category_15 category_16 category_734 category_61 category_64 portal_5 item_type_3 month_year_09_2026

<p>Vehicle specifications.</p> Tuan Anh Nguyen (121944) Biochemistry Neuroscience Physiology Biological Sciences not elsewhere classified Developmental Biology Cancer three main contributions scheduling mechanism adjusts robust current tracking reducing vertical tire often insufficiently addressed novelty therefore lies enhance rollover stability current tracking error aggressive steering maneuvers adaptive fuzzy gain bar control framework adaptive fuzzy super improving vehicle dynamics electromechanical stabilizer bars vehicle operating conditions vehicle dynamics electromechanical stabilizer proposed framework bar actuator vehicle modeling turn maneuver settling time roll system results demonstrate paper proposes model nonlinearities maximum motor luxury vehicles lumped disturbances integrated super high speeds force variations external disturbances explicitly capture disturbance compensation coordinated integration commonly equipped benchmark controllers active anti 100 km <div><p>Electromechanical stabilizer bars are commonly equipped in luxury vehicles to enhance rollover stability during aggressive steering maneuvers at high speeds. However, most existing studies simplify actuator and vehicle dynamics, while parametric uncertainties, model nonlinearities, and external disturbances are often insufficiently addressed. This paper proposes a robust adaptive control framework for an active anti-roll system with three main contributions. First, a comprehensive coupled dynamic model is established to explicitly capture the interaction between the electromechanical stabilizer-bar actuator and vehicle dynamics. Second, an integrated Super-Twisting Sliding Mode Control and Nonlinear Active Disturbance Rejection Control scheme is developed, in which the nonlinear extended state observer estimates and compensates for lumped disturbances and uncertainties, while the super-twisting mechanism provides robust motor current tracking. Third, an adaptive fuzzy gain-scheduling mechanism adjusts the control gain online according to vehicle operating conditions. The novelty therefore lies in the coordinated integration of coupled actuator–vehicle modeling, disturbance compensation, robust current tracking, and operating-condition-dependent gain adaptation within an electromechanical stabilizer-bar control framework. Numerical simulations demonstrate superior performance to the benchmark controllers in reducing vertical tire-force variations and improving vehicle dynamics. Under a J-turn maneuver at 100 km/h, the maximum motor-current tracking error is limited to 0.11 A, with an overshoot of 3.59% and a settling time of 0.17 s. These results demonstrate the effectiveness and potential of the proposed framework for automotive active control systems.</p></div> 2026-09-28T17:32:53Z Dataset Dataset 10.1371/journal.pone.0356645.t001 https://figshare.com/articles/dataset/_p_Vehicle_specifications_p_/34016327 CC BY 4.0