A novel robust fuzzy sampled adaptive event-triggered control for enhancing vehicle stability and maneuverability

This work concerns the event-triggered vehicle direct yaw moment control to improve its stability and its handling during critical maneuver. An adaptive sampled event-triggered scheme, based on the logistic function, is proposed for reducing over-consumption of network, computing and energy resources. A novel approach to deal with the premises asynchronicity is introduced to reduce the number of design conditions. The reference trajectory tracking problem is solved with the presented sufficient Linear Matrix Inequality (LMI) based conditions. The effectiveness of the proposed approach is demonstrated via a co-simulation with the high-fidelity simulation software Carsim.