Evaluates vehicle stability enhancements with adaptive control of AFS and DYC systems, suggesting improved handling under uncertain conditions.
This paper presents an Adaptive MIMO Sliding Mode Control (AMSMC) strategy for coordinating Active Front Steering (AFS) and Direct Yaw Control (DYC) systems to enhance vehicle stability and handling under uncertain conditions. Traditional Single Input Single Output (SISO) models fail to capture the complex interactions and nonlinearities inherent in vehicle dynamics, leading to suboptimal performance. The proposed method addresses these limitations by utilizing a Multiple Input Multiple Output (MIMO) framework, which accurately models the nonlinear interactions between AFS and DYC systems. Additionally, the method introduces a dynamic coefficient in the sliding mode control, enabling real‐time adaptation to unknown uncertainties and enhancing robustness. The slip angle is estimated by an observer and a first‐order delay is introduced into the lateral forces modeling to improve the accuracy of vehicle dynamics representation. The stability of the closed‐loop system is further validated using the Lyapunov method. The performance of the proposed controller is evaluated considering the coefficient of road tire friction and parametric uncertainties in vehicle parameters, such as total mass, moment of inertia, and tire stiffness. The efficacy of this method has been rigorously confirmed through MATLAB simulations using a nonlinear 8‐DOF vehicle model, which includes parameter uncertainties to ensure the control strategy's resilience to varying road conditions. The simulation results demonstrate significant improvements in the vehicle's stability and handling performance across a variety of driving maneuvers.
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Muhammad et al. (2025) studied this question.
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