Kinematic analysis and advanced control of a vectored thruster based on 3RRUR parallel manipulator for micro-size AUVs
Abstract Autonomous underwater vehicles (AUVs) have played a pivotal role in advancing ocean exploration and exploitation. However, traditional AUVs face limitations when executing missions at minimal or near-zero forward velocities due to the ineffectiveness of their control surfaces, considerably constraining their potential applications. To address this challenge, this paper introduces an innovative vectored thruster system based on a 3RRUR parallel manipulator tailored for micro-sized AUVs. The incorporation of a vectored thruster enhances the performance of micro-sized AUVs when operating at minimal and low forward speeds. A comprehensive exploration of the kinematics of the thrust-vectoring mechanism has been undertaken through theoretical analysis and experimental validation. The findings from theoretical analysis and experimental confirmation unequivocally affirm the feasibility of the devised thrust-vectoring mechanism. The precise control of the vector device is studied using Physics-informed Neural Network and Model Predictive Control (PINN-MPC). Through the adoption of this pioneering thrust-vectoring mechanism rooted in the 3RRUR parallel manipulator, AUVs can efficiently and effectively generate the requisite motion for thrust-vectoring propulsion, overcoming the limitations of traditional AUVs and expanding their potential applications across various domains.
Authors
- Jintao Zhao (ORCID: https://orcid.org/0000-0002-4482-9721)
- Tao Liu (ORCID: https://orcid.org/0000-0001-7756-2552)
- Junhao Huang (ORCID: https://orcid.org/0009-0004-6635-399X)
Institutions
- Sun Yat-sen University (CN)
- Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN)
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (CN)
Publication Details
- Journal
- Robotica
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1017/s0263574724001280
- Citations
- 1
- Primary Topic
- Control and Dynamics of Mobile Robots
- Type
- article
- Field-Weighted Citation Impact
- 0.33