Adaptive fuzzy super-twisting sliding mode control with nonlinear active disturbance rejection for electromechanical stabilizer bars to improve vehicle roll stability

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.