Neural network based decoupling control of lifting of 7500t floating crane vessel

Weifeng Shi, Zuohan Zhou, Zhenhua Shi, Liufeng Shen
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引用次数: 0

Abstract

According to characteristics of nonlinear and strong coupling between rolling and luffing of 7500 Ton crane arm with vessel stability in lifting process, we built a mathematical model of movement stance of crane vessel lifting process and brought forward a neural network decoupling control strategy. The control method was applied to solve the coupling problem between rolling and luffing for the crane lifting of the vessel. The executive motors of crane vessel work stably under the control. The space position of heavy load can be controlled stably in lifting process because of good control stability of motor. The control is also well effect for vessel stability. The control aim is used for safety and reliability of crane vessel operation. Simulation results indicate that there is good stability of dynamic decoupling between rolling and luffing of crane vessel.
基于神经网络的7500t浮式起重船起升解耦控制
针对7500吨起重臂在起重过程中横摇变幅与船舶稳定性非线性强耦合的特点,建立了起重臂起重过程运动姿态的数学模型,提出了神经网络解耦控制策略。将该控制方法应用于船舶起重过程中横摇与变幅的耦合问题。起重机船的执行电机在控制下工作稳定。由于电机的控制稳定性好,在提升过程中可以稳定地控制重物的空间位置。对船舶的稳定性也有很好的控制效果。控制目的是为了保证起重船的安全可靠运行。仿真结果表明,该方法具有良好的横摇与变幅动态解耦稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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