MPC-Based Exponential Weight Laguerre Function With Non-Singular Terminal SMC for Four-Wheel Independent Drive Electric Vehicles

Abstract

This article describes a complete control method that uses Laguerre exponentially weighted model predictive control (LEMPC) to help four-wheel independent drive electric vehicles stay stable and follow their paths. The proposed method incorporates an enhanced direct yaw moment control using a robust non-singular terminal sliding mode control framework. We evaluated traditional, Laguerre, and exponentially weighted model predictive control methodologies (TMPC, LMPC, and LEMPC), respectively, with comparisons of reduced computational load and complexity while maintaining path tracking. The weighted Laguerre model predictive control exhibits improved robustness and reduced computational time and load. The suggested strong non-singular terminal sliding mode control (NTSMC) combined with LEMPC improved control and stability in a wide range of maneuvering situations and levels of uncertainty. The synergistic impact of NTMSC with LEMPC was examined to improve path tracking efficacy and dynamic stability under diverse road conditions and disturbances. The effectiveness of the control strategy in handling and stability of vehicle at high speed while maintaining efficient path tracking was validated by simulation conducted in MATLAB/Simulink along with high-fidelity co-Simulink Carsim environment.

Keywords

• Classical sliding mode control (CSMC)
• direct yaw moment (DYC)
• electric vehicle
• exponential weighted Laguerre model predictive control (LEMPC)
• fuzzy sliding mode control (FSMC)
• nonsingular terminal sliding mode control (NTSMC)