Work

Q‐Learning for Tracking Control of Autonomous Underwater Vehicle

Year: 2025

Type: article

Abstract: ABSTRACT In this article, the tracking control problem of autonomous underwater vehicle (AUV) is considered. The main contribution is to give the explicitly optimal tracking controller by using a Q‐learning algorithm when the system model is unknown. The key is to discretize and linearize the kinematic equation of AUV, and then the Q‐factors are expressed as functions of input‐output vectors. In particular, a simulation study is carried out to demonstrate the effectiveness of the proposed method.

Source: International Journal of Robust and Nonlinear Control

DOI: 10.1002/rnc.7976

Authors: Mingchen Yu, Wei Wang, Juanjuan Xu

Institution: Shandong University

Language: English

Topic: Adaptive Dynamic Programming Control

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: National Natural Science Foundation of China

Award: G3783553680