Robust Yaw Stability Controller Design and Hardware-in-the-Loop Testing for a Road Vehicle

Abstract

Unsymmetrical loading on a car like μ-split braking, side wind forces, or unilateral loss of tire pressure results in unexpected yaw disturbances that require yaw stabilization either by the driver or by an automatic driver-assist system. The use of two-degrees-of-freedom control architecture known as the model regulator is investigated here as a robust steering controller for such yaw stabilization tasks in a driver-assist system. The yaw stability-enhancing steering controller is designed in the parameter space to satisfy a frequency-domain mixed sensitivity constraint. To evaluate the resulting controller design, a real-time hardware-in-the-loop simulator is developed. Steering tests with and without the controller in this hardware-in-the-loop setup allow the driver to see the effect of the proposed controller to improve vehicle-handling quality. The hardware-in-the-loop simulation setup can also be used for real-time driver-in-the-loop simulation of other vehicle control systems.

Optimal Sensor Configuration and Fault-Tolerant Estimation of Vehicle States

“…Sensor sets including individual sensors are the least favorable configurations based on the measures in Equations (27), (28), (29), (30), (31), (32), (33). However, the system is observable with all the introduced sensor sets, assuming the model (1), (2), (3), (4), (5), (6), (7), (8), (9), (10), (11), (12), (13), (14), (15), (16), (17), (18) …”

“…This model represents handling dynamics of the vehicle and includes lateral acceleration (a y ), yaw rate (r) and roll rate ( ) as dominant elements that contribute to the handling performance. The majority of studies that focused on vehicle handling dynamics consider a 2-DOF vehicle model that only includes yaw and lateral motions [13], [14], [15]. However, the roll motion can significantly affect the handling dynamics due to lateral load transfer.…”

Integrated vehicle dynamics control via coordination of active front steering and rear braking

“…This study mainly focusses on the most commonly used AFS approach. This latter may be formulated using disturbance observer control method [21,22], sliding mode control [23], predictive control [16], or other control techniques. Such active handling control usually serves a steering support system by applying an additional steering angle to the driver's steer command.…”

“…Concerning the lateral behavior, different actuators configuration have been considered using front/rear steering and braking torque distribution (front/rear, differential braking) [22,20,11,39,43,44,33] but also more recently with differential tire slip [26] if electrical in-wheel-motors are considered. Advanced control methods have then been developed to solve this complex control problem for a MIMO system, such as optimal control [44], control allocation [43,39], Model Predictive Control [11], and robust control [22,20]. Some of the previous existing studies, such as [23,20], develop separately both DYC and AFS systems, and then propose a switching strategy between both stand-alone systems, according to the driving situations.…”

“…Thus, it is ensured that the steering action is comfortable for the driver. This filter design is inspired from [21,22].…”