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<p>Precise dynamic positioning of autonomous underwater vehicles (AUVs) faces significant challenges because of actuator nonlinearities such as input saturation and backlash, which degrade system performance and stability in subsea operations. This work proposes a disturbance observer-based event-triggered prescribed-time dynamic positioning (DOB-ETPTDP) control framework to address these issues. The scheme reformulates the AUV kinematics as a dynamic position error system, modeling actuator nonlinearities as a bounded lumped disturbance. A key innovation is the prescribed-time disturbance observer that ensures rapid and accurate disturbance estimation, enhancing robustness against unknown actuator dynamics. A prescribed-time backstepping-based control law uses these estimates, to guarantee the asymptotic convergence of the dynamic position error to zero, independent of initial conditions. An adaptive prescribed-time event-triggered mechanism further optimizes control efficiency by reducing update rates and preventing Zeno behavior. Numerical simulations verified the effectiveness of the proposed DOB-ETPTDP scheme. In terms of convergence speed, the proposed method achieved improvements of approximately 55% and 67% compared with the sliding mode and backstepping approaches, respectively. Regarding computational complexity, the proposed method reduced the average computational load by about 20%. Moreover, the average data transmission ratio was significantly reduced, conserving more than 65% of the communication resources relative to the backstepping strategy. Rigorous stability analysis validated the theoretical guarantees, and extensive simulations confirmed that the proposed DOB-ETPTDP approach ensures high-accuracy dynamic positioning with enhanced robustness under complex actuator constraints.</p>

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Event-triggered prescribed-time position control for AUVs with input constraints: a nonlinear disturbance observer approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月6日

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  • Minfei Dai,
  • Wei Cai,
  • Chang He,
  • Houjun Shi,
  • Xingyu Zhou

摘要

Precise dynamic positioning of autonomous underwater vehicles (AUVs) faces significant challenges because of actuator nonlinearities such as input saturation and backlash, which degrade system performance and stability in subsea operations. This work proposes a disturbance observer-based event-triggered prescribed-time dynamic positioning (DOB-ETPTDP) control framework to address these issues. The scheme reformulates the AUV kinematics as a dynamic position error system, modeling actuator nonlinearities as a bounded lumped disturbance. A key innovation is the prescribed-time disturbance observer that ensures rapid and accurate disturbance estimation, enhancing robustness against unknown actuator dynamics. A prescribed-time backstepping-based control law uses these estimates, to guarantee the asymptotic convergence of the dynamic position error to zero, independent of initial conditions. An adaptive prescribed-time event-triggered mechanism further optimizes control efficiency by reducing update rates and preventing Zeno behavior. Numerical simulations verified the effectiveness of the proposed DOB-ETPTDP scheme. In terms of convergence speed, the proposed method achieved improvements of approximately 55% and 67% compared with the sliding mode and backstepping approaches, respectively. Regarding computational complexity, the proposed method reduced the average computational load by about 20%. Moreover, the average data transmission ratio was significantly reduced, conserving more than 65% of the communication resources relative to the backstepping strategy. Rigorous stability analysis validated the theoretical guarantees, and extensive simulations confirmed that the proposed DOB-ETPTDP approach ensures high-accuracy dynamic positioning with enhanced robustness under complex actuator constraints.