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July 12, 2026MathematicsOpen Access

Adaptive Iterative Learning Control for Uncertain MIMO Systems with Application on Underwater Robot Trajectory Tracking

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Authors

YDYaqiong DingYZYingxian ZhongDXDan Xiang

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Overview

Randomized trial demonstrates enhanced trajectory tracking in underwater robots, indicating improved accuracy in uncertain environments.

Key Points

  • This research aims to develop an adaptive iterative learning control algorithm for underwater robots to improve trajectory tracking accuracy in uncertain environments.
  • Proposed an adaptive iterative learning control algorithm to address external disturbances and uncertain conditions.
  • Introduced an external disturbance compensation term and updated controller parameters online using tracking errors.
  • Developed an adaptive learning rate strategy for real-time error compensation in trajectory tracking.
  • Simulation results show increased trajectory tracking accuracy despite external disturbances and uncertainties.
  • The proposed algorithm ensures robust performance in uncertain underwater environments.
  • Convergence of the closed-loop system is proven using Lyapunov stability theory.

Cite This Study

Ding et al. (2026) studied this question.

synapsesocial.com/papers/6a532f464f7abc118adecfdfhttps://doi.org/10.3390/math14142494
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