A sliding mode predictive anti-pitching control for a high-speed multihull

Xu, Weidong; Zhang, Jun; Zhong, Mingjie

doi:10.1016/j.oceaneng.2023.115466

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…In addition, the authors have some research results in the field of model predictive control algorithms as well as high-speed multihull robust control. Specifically, a sliding mode predictive anti-pitching control considering appendage constraints is proposed in [13] (Jun Zhang), in which a prediction model and an objective function are established with the sliding mode states as variables, and the sliding mode terminal stability constraint set is adopted to improve the stability of the closed-loop system. Considering the excessive vertical motion amplitude of high-speed multihulls, and the difficulty of measuring heave velocity and pitch angular velocity directly, a robust anti-pitching control method without velocity measurements is proposed in [14].…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control Based on State Space and Risk Augmentation for Unmanned Surface Vessel Trajectory Tracking

Li,

Zhang,

Wang

et al. 2023

JMSE

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The underactuated unmanned surface vessel (USV) has been identified as a promising solution for future maritime transport. However, the challenges of precise trajectory tracking and obstacle avoidance remain unresolved for USVs. To this end, this paper models the problem of path tracking through the first-order Nomoto model in the Serret–Frenet coordinate system. A novel risk model has been developed to depict the association between USVs and obstacles based on SFC. Combined with an artificial potential field that accounts for environmental obstacles, model predictive control (MPC) based on state space is employed to achieve the optimal control sequence. The stability of the designed controller is demonstrated by means of the Lyapunov method and zero-pole analysis. Through simulation, it has been demonstrated that the controller is asymptotically stable concerning track error deviation, heading angle deviation, and heading angle speed, and its good stability and robustness in the presence of multiple risks are verified.

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Section: Introductionmentioning

confidence: 99%