In this paper, we focus on addressing the trajectory tracking control problem for autonomous six-wheel-drive/six-wheel-steering (6WD/6WS) vehicles. It is noted that the dynamics of the 6WD/6WS vehicle is considered as an overactuated system corresponding to three control inputs, including the front, mid, and rear wheel steering angles. Furthermore, the lateral tracking error and the steering angle inputs must be constrained, providing safety and good tracking performance. To achieve these objectives, the Lyapunov-based Model Predictive Control (LMPC) is employed for the linearized bicycle model of the 6WS/6WD vehicles to achieve the trajectory tracking control and state constraint. Based on a Lyapunov candidate function, which is constructed based on Sliding Mode Control (SMC) principles and is then integrated into the LMPC formulation as a constraint, the closed-loop stability is theoretically guaranteed. Finally, a simulation result is provided to show the feasibility of the proposed approach and the superior trajectory tracking performance.

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Lyapunov-Based Model Predictive Tracking Control for Autonomous Six-Wheel- Steering /Six-Wheel- Drive Vehicles in Lane Changing Maneuvers

  • Dang Khoa Tran,
  • Dan Truong Do,
  • Van Dien Tran,
  • Gia Khiem Dinh,
  • Tung Lam Nguyen

摘要

In this paper, we focus on addressing the trajectory tracking control problem for autonomous six-wheel-drive/six-wheel-steering (6WD/6WS) vehicles. It is noted that the dynamics of the 6WD/6WS vehicle is considered as an overactuated system corresponding to three control inputs, including the front, mid, and rear wheel steering angles. Furthermore, the lateral tracking error and the steering angle inputs must be constrained, providing safety and good tracking performance. To achieve these objectives, the Lyapunov-based Model Predictive Control (LMPC) is employed for the linearized bicycle model of the 6WS/6WD vehicles to achieve the trajectory tracking control and state constraint. Based on a Lyapunov candidate function, which is constructed based on Sliding Mode Control (SMC) principles and is then integrated into the LMPC formulation as a constraint, the closed-loop stability is theoretically guaranteed. Finally, a simulation result is provided to show the feasibility of the proposed approach and the superior trajectory tracking performance.