PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 28, 2025Actuators6 citationsOpen Access

Fuzzy Adaptive PID-Based Tracking Control for Autonomous Underwater Vehicles

View Full Paper
SFShicheng FanHWHaoming WangCZChenyu Zuo

Key Points

  • The proposed fuzzy adaptive PID controller shows significant improvement in tracking performance.
  • Simulation experiments demonstrate superiority over conventional PID and standalone fuzzy controllers.
  • A detailed stability analysis assures the robustness of the control system in varying conditions.
  • The control system effectively handles nonlinear dynamics and time-varying parameters of underwater environments.

Abstract

This paper addresses the trajectory tracking control problem of Autonomous Underwater Vehicles (AUVs). A comprehensive mathematical model is first established based on Newtonian mechanics, incorporating both kinematic and dynamic equations. By reasonably neglecting the minor influence of roll motion, a five-degree-of-freedom (5-DOF) underactuated AUV model is derived. Considering the strong nonlinearities, high coupling, and time-varying hydrodynamic parameters typical of underwater environments, a fuzzy adaptive PID controller is proposed. This controller combines the adaptability of fuzzy logic with the structural simplicity and reliability of PID control, making it well-suited to the demanding requirements of AUV motion control. Extensive simulation experiments are conducted to evaluate the controller’s performance under various operating conditions. The results show that the fuzzy adaptive PID controller significantly outperforms conventional PID and standalone fuzzy logic controllers in terms of convergence speed and oscillation suppression. Furthermore, a theoretical stability analysis is provided to ensure that the proposed control system remains stable under time-varying fuzzy gain scheduling, confirming its effectiveness and potential for practical application in underwater vehicle control.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Fan et al. (2025) studied this question.

synapsesocial.com/papers/68d9051b41e1c178a14f4f4chttps://doi.org/10.3390/act14100470
Ask AI
Helpful
Bookmark
Share
View Full Paper