The invention relates to an anti-swing control method and device for a portal crane based on deep reinforcement learning, and the method comprises the steps: constructing an anti-swing control virtual platform for the portal crane, and determining an initial strategy of the anti-swing control virtual platform for the portal crane based on an input shaping algorithm; based on the initial strategy and a depth deterministic strategy gradient algorithm, determining a final strategy of the anti-swing control virtual platform of the gantry crane; and based on a double-Q network, transferring the final strategy to an anti-swing control real platform of the overhead and gantry crane, and determining an anti-swing control strategy of the anti-swing control real platform of the overhead and gantry crane. According to the invention, the application of the deep reinforcement learning algorithm in the anti-swing control of the overhead and gantry crane is realized, and the anti-swing control performance of the overhead and gantry crane is improved.
本发明涉及一种基于深度强化学习的桥门式起重机防摇控制方法及装置,包括:构建桥门式起重机防摇控制虚拟平台,基于输入整形算法确定所述桥门式起重机防摇控制虚拟平台的初始策略;基于所述初始策略和深度确定性策略梯度算法,确定所述桥门式起重机防摇控制虚拟平台的最终策略;基于双Q网络,将所述最终策略迁移至桥门式起重机防摇控制真实平台,确定所述桥门式起重机防摇控制真实平台的防摇控制策略。本发明实现了深度强化学习算法在桥门式起重机防摇控制上的应用,提高了桥门式起重机防摇控制的性能。
Anti-swing control method and device for gantry crane based on deep reinforcement learning
基于深度强化学习的桥门式起重机防摇控制方法及装置
2024-01-30
Patent
Elektronische Ressource
Chinesisch
IPC: | B66C Krane , CRANES |
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