Preset trajectory based prescribed performance control for active anti-roll of automotives

In this paper, our main focus is on the research of Active Stabilizer Bar System (ASBS) for roll control. Prescribed Performance Control (PPC) has garnered significant attention from scholars and researchers in recent years. In mainstream PPC methods, barrier functions are widely adopted, leading to potential singularity issues in control laws during most unexpected scenarios such as sensor failures. In this study, we employ a robust PPC approach that does not rely on barrier functions, thereby completely circumventing singularity problems in control laws. Firstly, we establish a vehicle roll dynamics model incorporating parameter uncertainties and disturbances with ASBS. Subsequently, controller design is performed in three steps: firstly, constructing performance functions based on system performance requirements to form performance envelopes; secondly, designing reference trajectories within the preset performance envelopes; thirdly, designing robust sliding mode control laws to ensure that the actual tracking error of the system evolves within a tubular region containing the reference trajectories and strictly varies within the performance envelopes. Finally, through simulation experiments, we demonstrate the effectiveness and superiority of this control method.