采用自适应后退滑模控制方法抑制双摆塔式起重机的载荷摇摆

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS
Zijie Fang;Huimin Ouyang;Hui Yi;Xiaodong Miao
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引用次数: 0

摘要

塔式起重机被广泛应用于各个行业,由于吊钩质量引起的复杂动力学,它引入了双摆运动,因此面临着挑战。这使得小车和吊臂的精确定位和摇摆控制变得困难。此外,现实世界的操作经常涉及不可预测的外部干扰。为了解决这些问题,本文提出了一种自适应反步分层滑模控制策略,通过简化塔机的动态模型来开发。利用李亚普诺夫定理和拉萨尔不变性原理证实了系统的鲁棒稳定性。通过大量的实验,所提出的控制器表现出优异的性能和鲁棒性,能够有效地处理塔机运行的复杂性,并在环境不确定的情况下保持精确控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load Sway Suppression for Double-Pendulum Tower Cranes Using Adaptive Backstepping Sliding Mode Control Approach
Tower cranes, commonly used across various industries, face challenges due to the complex dynamics caused by the hook mass, which introduces double-pendulum motion. This makes precise positioning and sway control of the trolley and jib difficult. Additionally, real-world operations often involve unpredictable external disturbances. To address these challenges, this article proposes an adaptive backstepping hierarchical sliding mode control strategy, developed by simplifying the tower crane’s dynamic model. The system’s robust stability is confirmed using Lyapunov’s theorem and LaSalle’s invariance principle. Through extensive experiments, the proposed controller demonstrates excellent performance and robustness, effectively handling the complexities of tower crane operations and maintaining precise control despite environmental uncertainties.
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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