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Previous and Current Cycle Learning approach to a 3D crane system laboratory equipment

机译:3D起重机系统实验室设备的先前和当前循环学习方法

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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.
机译:本文在新的迭代学习控制(ILC)结构的框架下,为3D起重机系统实验室设备的位置控制提供了先前和当前循环学习(PCCL)方法。 PCCL结构是围绕具有频域设计的超前-滞后控制器的控制回路构建的,并且涉及到实际的PD学习规则。应用频域收敛条件设计学习规则。与位置控制有关的实时实验结果说明了ILC结构的设计。

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