Increase in Stability of an X-Configured AUV through Hydrodynamic Design Iterations with the Definition of a New Stability Index to Include Effect of Gravity

Miller, L. I.; Brizzolara, Stefano; Stilwell, Daniel J.

doi:10.3390/jmse9090942

Cited by 9 publications

(1 citation statement)

References 11 publications

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“…The rigid body mass inertia matrix M RB represents the distribution of mass and the moment of inertia about the center of mass during the motion of the AUV. The added mass matrix M A represents the response of the added mass moments due to the fluid environment that the AUV encounters during its motion [32].…”

Section: The Dynamic Model Of the "Sz-1" Auvmentioning

confidence: 99%

Three-Dimensional Path Tracking of Over-Actuated AUVs Based on MPC and Variable Universe S-Plane Algorithms

Xu,

Zhang,

Zhong

2024

JMSE

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Autonomous Underwater Vehicles (AUVs) are widely used for the inspection of seabed pipelines. To address the issues of low trajectory tracking accuracy in AUV inspection processes due to uncertain ocean current disturbances, this paper designs a new dual-loop controller based on Model Predictive Control (MPC) and Variable Universe S-plane algorithms (S-VUD FLC, where VUD represents Variable Universe Discourse and FLC represents Fuzzy Logic Control) to achieve three-dimensional (3-D) trajectory tracking of an over-actuated AUV under uncertain ocean current disturbances. This paper uses MPC as the outer-loop position controller and S-VUD FLC as the inner-loop speed controller. The outer-loop controller generates desired speed instructions that are passed to the inner-loop speed controller, while the inner-loop speed controller generates control input and uses a direct logic thrust distribution method that approaches optimal energy consumption to distribute the thrust generated by the propellers to the over-actuated AUV, achieving closed-loop tracking of the entire trajectory. When designing the outer-loop MPC controller, the actual control input constraints of the system are considered, and control increments are introduced to reduce control model errors and the impact of uncertain external disturbances on the actual AUV model parameters. When designing the inner-loop S-VUD FLC, the strong robustness of the variable universe fuzzy controller and the easy construction characteristics of the S-plane algorithm are combined, and integral action is introduced to improve the system’s tracking accuracy. The stability of the outer loop controller is proven by the Lyapunov method, and the stability of the inner loop controller is verified by simulation. Finally, simulations show that the over-actuated AUV has fast tracking processes and high tracking result accuracy under uncertain ocean current disturbances, demonstrating the effectiveness of the designed dual-loop controller.

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Section: The Dynamic Model Of the "Sz-1" Auvmentioning

confidence: 99%