A combined use of adaptive sliding mode control and unscented Kalman filter estimator to improve vehicle yaw stability

Abstract

In this paper, an adaptive sliding mode controller is proposed to improve the vehicle yaw stability and enhance the lateral motion by direct yaw moment control method using active braking systems. As the longitudinal and lateral velocities of the vehicles as well as many other vehicle dynamics variables cannot be measured in a cost-efficient way, a robust control method combined with a state estimator is required to guarantee the system stability. Furthermore, some parameters such as the tyre–road friction coefficient undergo frequent changes, and the aerodynamics resistance forces are often exerted as a disturbance during the wide driving condition. So, an adaptive sliding mode controller is applied to make vehicle yaw rate to track its reference with robustness against model uncertainties and disturbances and a non-linear estimator based on unscented Kalman filter is used to estimate wheel slip, yaw rate, road friction coefficient, longitudinal and lateral velocities. The estimation algorithm directly uses non-linear equations of the system and does not need the linearization and differentiation. The designed controller, which is insensitive to system uncertainties, offers the adaptive sliding gains to eliminate the precise determination of the bounds of uncertainties. The sliding gain values are determined using a simple adaptation algorithm that does not require extensive computational load. Numerical simulations of various manoeuvres using a non-linear full vehicle model with seven degrees of freedom demonstrate the high effectiveness of the presented controller for improving the vehicle yaw stability and handling performance.