Modeling and Adaptive Control of Double-Pendulum Offshore Cranes with Distributed-Mass Payloads and External Disturbances

Offshore cranes are widely used in important fields such as wind power construction and ship replenishment. However, large payloads such as wind turbine blades are hoisted by multiple steel wire ropes, which makes it difficult to directly control their movements; that is, the number of input degrees of freedom is less than that of the output degrees of freedom. In addition, compared with land cranes, offshore cranes are inevitably affected by waves, wind, etc. The transition from a fixed base to a dynamic base brings severe challenges to their oscillation suppression and precise positioning. At the same time, to improve operational efficiency, the hoisting operation of offshore cranes usually adopts velocity input control patterns that fit the habits of manual operation, and most of them are in the form of dual-axis linkage for pitch and hoisting. Therefore, this paper proposes a fast terminal sliding mode control method for double-pendulum offshore cranes with distributed-mass payloads (DMPs). First, a nonlinear dynamic model of offshore cranes considering DMPs is established, and a dynamic model based on acceleration input control patterns is acquired. Based on this, considering the variation in hoisting rope lengths, a novel adaptive control method is proposed. Finally, simulation results verify the effectiveness of the proposed method, and the robustness of the proposed method to DMP mass parameter uncertainty and disturbances is demonstrated.

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Publication Details

Journal
Actuators
Published
2025-04-23
DOI
https://doi.org/10.3390/act14050204
Citations
2
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
2.43

Funders

Controls
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article

Modeling and Adaptive Control of Double-Pendulum Offshore Cranes with Distributed-Mass Payloads and External Disturbances

Yuxuan Jiao, Weijie Hou, Tong Yang, Yaxuan Wu et al.
2 citations
Actuators
Adaptive Control of Nonlinear Systems
2.43
article

Modeling and Adaptive Control of Double-Pendulum Offshore Cranes with Distributed-Mass Payloads and External Disturbances

Yuxuan Jiao, Weijie Hou, Tong Yang, Yaxuan Wu, Qingxiang Wu, Shudong Guo, Ning Sun, Nan Li, Yuehua Li
article en
2 citations

Abstract

Offshore cranes are widely used in important fields such as wind power construction and ship replenishment. However, large payloads such as wind turbine blades are hoisted by multiple steel wire ropes, which makes it difficult to directly control their movements; that is, the number of input degrees of freedom is less than that of the output degrees of freedom. In addition, compared with land cranes, offshore cranes are inevitably affected by waves, wind, etc. The transition from a fixed base to a dynamic base brings severe challenges to their oscillation suppression and precise positioning. At the same time, to improve operational efficiency, the hoisting operation of offshore cranes usually adopts velocity input control patterns that fit the habits of manual operation, and most of them are in the form of dual-axis linkage for pitch and hoisting. Therefore, this paper proposes a fast terminal sliding mode control method for double-pendulum offshore cranes with distributed-mass payloads (DMPs). First, a nonlinear dynamic model of offshore cranes considering DMPs is established, and a dynamic model based on acceleration input control patterns is acquired. Based on this, considering the variation in hoisting rope lengths, a novel adaptive control method is proposed. Finally, simulation results verify the effectiveness of the proposed method, and the robustness of the proposed method to DMP mass parameter uncertainty and disturbances is demonstrated.

ActuatorsVol. 14(5)
Nankai University (CN), State Key Laboratory of Robotics and Systems (CN)
National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 12%
Adaptive Control of Nonlinear Systems
2.43
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