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<p>This paper addresses the trajectory tracking control problem for unmanned aerial vehicles (UAVs) by incorporating a non-singular terminal sliding mode auxiliary control (TSMAC) into the Lyapunov-based model predictive control (LMPC) framework. The integration of Lyapunov tightening constraints ensures that the tracking error converges within a finite time, thereby enhancing the stability and robustness in dynamic environments. Additionally, the proposed LMPC framework offers a well-balanced approach between computational complexity and tracking performance. Through rigorous theoretical analysis, the feasible set for the optimization problem is delineated, ensuring that the control inputs remain within acceptable limits. Finally, the effectiveness of the proposed algorithm is validated through simulation results, with advantages in UAV trajectory tracking demonstrated by faster convergence, improved disturbance rejection, and overall enhanced control performance.</p>

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Lyapunov-based model predictive control for unmanned aerial vehicles with integrated non-singular terminal sliding mode surface

  • 期刊论文

  • 发表日期：

    2025年1月29日

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  • Yuan Tian,
  • Run-Zhi Wang,
  • Li-Ying Hao

摘要

This paper addresses the trajectory tracking control problem for unmanned aerial vehicles (UAVs) by incorporating a non-singular terminal sliding mode auxiliary control (TSMAC) into the Lyapunov-based model predictive control (LMPC) framework. The integration of Lyapunov tightening constraints ensures that the tracking error converges within a finite time, thereby enhancing the stability and robustness in dynamic environments. Additionally, the proposed LMPC framework offers a well-balanced approach between computational complexity and tracking performance. Through rigorous theoretical analysis, the feasible set for the optimization problem is delineated, ensuring that the control inputs remain within acceptable limits. Finally, the effectiveness of the proposed algorithm is validated through simulation results, with advantages in UAV trajectory tracking demonstrated by faster convergence, improved disturbance rejection, and overall enhanced control performance.