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This paper deals with the simultaneous vehicle-handling and path-tracking improvement through a steer-by-wire system, using non-linear adaptive dynamic surface sliding control. The designed adaptive dynamic surface controller, which is insensitive to system uncertainties, offers an adaptive sliding gain to eliminate the precise determination of the bound of uncertainties. The sliding-gain value is obtained using a simple adaptation law that does not require an extensive computational load. Achieving the improved vehicle-handling and path-tracking characteristics requires both accurate state estimation and well-controlled steering inputs from the steer-by-wire system. A second-order sliding-mode observer provides accurate estimation of the lateral and longitudinal velocities while the yaw rate is available from the angular rate sensor. A driver control model is also presented according to the preview or look-ahead strategy to generate appropriate steering angles using the vehicle state feedback and future information about the path to be followed. Moreover, because of the inertia and viscous damping of the steering mechanism, and the effects of the Coulomb friction and self-aligning moment of the front tyres, the steering-system controller is designed based on the proposed adaptive dynamic surface scheme, to control the front steering angle. A complete stability analysis based on the Lyapunov theory is presented to guarantee closed-loop stability. The simulation results confirmed that the proposed adaptive robust controller not only improves the vehicle-handling and path-tracking performance but also reduces the chattering problem in the presence of uncertainties in the tyres’ cornering stiffnesses.

A nonlinear adaptive sliding mode control for simultaneous vehicle handling and path tracking improvement through the Steer-By-Wire system is presented in this paper. The proposed adaptive sliding mode controller, which is insensitive to system uncertainties, offers an adaptive sliding gain to eliminate the precise determination of the bound of uncertainties. The sliding gain value is calculated using a simple adaptation algorithm which does not require extensive computational load. A driver control model is also presented according to the preview or look-ahead strategy to generate the appropriate steering angles using the vehicle states feedback and the future information about the path to be followed. Moreover, because of the inertia and viscous damping in the steering mechanism and the effects of coulomb friction and self-aligning moment of the front tires, the steering system controller based on the proposed adaptive sliding mode scheme, is designed to control the front steering angle. A complete stability analysis based on the Lyapunov theory is presented in order to guarantee the closed loop stability. Eventually, the simulation results confirm that the proposed adaptive robust controller not only improves the vehicle handling and path tracking performance but also reduces the chattering problem in presence of uncertainties in the tire cornering stiffness and the external disturbance.

The use of control systems, especially vehicle dynamic control systems, is increasing at a remarkable rate. A key parameter that affects the performance of a vehicle dynamic control system is the interaction forces between the tyre and the road since these forces determine the acceleration, braking and steering properties of a car. Consequently, the accurate estimate of these forces is highly desired. Technical limitations and cost considerations mean that it is standard practice to estimate this data instead of performing measurements. Since available tyre models are generally an algebraic representation of the actual tyre and neglect variations in road conditions and uncertainties, an improved model for vehicle dynamic control applications is required. This paper proposes a tyre model which is formulated based on the least squares method and variable exponential forgetting estimation. The proposed estimator calculates tyre forces using information obtained from the sensors in a vehicle dynamic control system. The performance and robustness of the proposed tyre model is evaluated via virtual handling simulations in ADAMS software.