Piecewise Compensation Model Predictive Governor Combined With Conditional Disturbance Negation for Underactuated AUV Tracking Control

Kong, Shihan; Sun, Jinlin; Wang, Jian; Zhou, Ziye; Shao, Jinyan; Yu, Junzhi

doi:10.1109/tie.2022.3194637

Cited by 7 publications

(1 citation statement)

References 36 publications

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“…Remark 1. Contrasting our proposed FTESO (7) with the FTESO in [37], our approach factors in the dynamics of disturbances and uncertainties to achieve a higher degree of estimation accuracy. Our usage of fractional powers within the FTESO allows for a quick finite-time convergence.…”

Section: Fteso Design and Convergence Analysismentioning

confidence: 99%

Distributed Dual Closed-Loop Model Predictive Formation Control for Collision-Free Multi-AUV System Subject to Compound Disturbances

Zhang,

Yan,

Zhou

et al. 2023

JMSE

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This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to accurately estimate both model uncertainties and external disturbances for each subsystem. Subsequently, the outer-loop and inner-loop formation controllers are developed by integrating disturbance compensation with distributed model predictive control (DMPC) theory. With full consideration of the input and state constraints, we resolve the local information-based DMPC optimization problem to obtain the control inputs for each AUV, thereby preventing actuator saturation and collisions among AUVs. Moreover, to mitigate the increased computation caused by the control structure, the Laguerre orthogonal function is applied to alleviate the computational burden in time intervals. We also demonstrate the stability of the closed-loop system by applying the terminal state constraint. Finally, based on a connected directed topology, comparative simulations are performed under various control schemes to verify the robustness and superior performance of the proposed scheme.

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Section: Fteso Design and Convergence Analysismentioning

confidence: 99%