ABSTRACT
Model Predictive Control (MPC) is an increasingly popular research area for active torque distribution. Previous predictive methods have utilised non-linear models with online partial differentiation to obtain state space matrices. This is computationally expensive and can limit how quickly the controller operates. A two-degree-of-freedom (DOF) state space controller is developed to control the vehicle’s yaw rate and lateral acceleration. The controller was evaluated using a 7DOF vehicle model and a sinusoidal steering input. The control algorithm improved the vehicle performance and does not show obvious limitations due to its lower model complexity.
