以前和当前周期学习方法的三维起重机系统实验室设备

M. Radac, Florin-Cristian Enache, R. Precup, E. Petriu, S. Preitl, C. Dragos
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引用次数: 2

摘要

本文提出了一种新的迭代学习控制(ILC)结构框架下的前周期和当前周期学习(PCCL)方法,用于三维起重机系统实验室设备的位置控制。PCCL结构围绕控制环构建,采用频域设计的超前滞后控制器,并涉及一个真实的PD学习规则。采用频域收敛条件设计学习规则。通过与位置控制相关的实时实验结果说明了ILC结构的设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Previous and Current Cycle Learning approach to a 3D crane system laboratory equipment
The paper offers a Previous and Current Cycle Learning (PCCL) approach to the position control of a 3D crane system laboratory equipment in the framework of a new Iterative Learning Control (ILC) structure. The PCCL structure is constructed around a control loop with a frequency domain designed lead-lag controller, and a real PD learning rule is involved. A frequency domain convergence condition is applied to design the learning rule. The design of the ILC structure is illustrated by real-time experimental results related to the position control.
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