Vehicle Stability Upper-Level-Controller Based on Parameterized Model Predictive Control

This paper presents an upper-level vehicular stability controller based on parameterized Model Predictive Control (MPC). The proposed system computes the additional moment applied vehicle’s yaw axis to improve lateral stability. In MPC formulation, optimization problem is defined as a quadratic programming derived from linear time-invariant model of vehicle dynamics. control implemented that considers rolling movement and simpler does not consider it, in order evaluate effects using more representative for accurate prediction or simplified faster calculation. Constraints are imposed deal with limits corrective moment. A approach designed reduce number variables, hence, reducing computation time required real-time implementation. Model-in-the-loop simulations effectiveness strategy avoid steering instability. Simulations performed profiling calculation time, tuning parameters, testing algorithm running ARM-Cortex A8 control. Simulation results show effective preventing destabilization demonstrates even longer resulting scheme meets requirements successfully, under presence disturbances.