Robust control for electric stabilizer bars via super-twisting sliding mode and active disturbance rejection with fuzzy-modulated adaptive gain scheduling

Electric Stabilizer Bars (ESBs) are widely adopted in high-end vehicles to enhance roll stability during steering. However, most existing studies either neglect actuator dynamics or oversimplify vehicle dynamics, while the combined effects of parameter uncertainties, nonlinearities, and external disturbances are insufficiently addressed. To overcome these limitations, this paper proposes a novel integrated control framework that combines an improved Smooth Super-Twisting Sliding Mode Controller (iSTSMC) with Nonlinear Active Disturbance Rejection Control (NADRC) for ESB systems. The main novelty of the proposed framework lies in three aspects. First, the dynamic behaviors of both the actuator and the vehicle are comprehensively modeled, explicitly considering nonlinear dynamics, parameter uncertainties, and external disturbances. Second, a Nonlinear Extended State Observer (NESO) is developed to estimate and compensate for lumped disturbances in real time, thereby improving disturbance-rejection capability. Third, a fuzzy-modulated adaptive gain-scheduling mechanism is incorporated into the iSTSMC to automatically adjust the controller gain, thereby reducing overshoot and suppressing chattering under varying operating conditions. Simulation results demonstrate that chattering is eliminated, while the overshoot and settling time are reduced to 0.49% and 1.98 s, respectively, during a J-turn maneuver at 70 km/h. Furthermore, during a fish-hook maneuver at 90 km/h, the proposed controller achieves maximum and root-mean-square tracking errors of only 0.17 and 0.05 A, respectively. These results demonstrate that the proposed control strategy provides superior disturbance rejection, tracking accuracy, and rollover stability compared with existing benchmark controllers.