文献类型：期刊文献

英文题名：Adaptive Input Shaping Control Based on RLS for Harvesting Mechanical Arm

作者：Sun, Mingming[1,2]; Liu, Dexin[3,4]

第一作者：Sun, Mingming

机构：[1] Basic Experimental Center for Natural Science, University of Science and Technology Beijing, Beijing, 100083, China; [2] School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China; [3] Beijing Union University, Beijing Key Laboratory of Information Service Engineering, Beijing, 100101, China; [4] College of Robotics, Beijing Union University, Beijing, 100101, China

第一机构：Basic Experimental Center for Natural Science, University of Science and Technology Beijing, Beijing, 100083, China

年份：2023

起止页码：705-710

外文期刊名：Proceedings of 2023 IEEE 12th Data Driven Control and Learning Systems Conference, DDCLS 2023

收录：EI(收录号：20233114457750)

语种：英文

外文关键词：Harvesting - Least squares approximations - Vibrations (mechanical)

摘要：In this paper, a direct method of adaptive input shaping algorithm for a harvesting mechanical arm clamps the tomato bunches is proposed to achieved zero residual vibration. The traditional input shaping would lose its vibration suppressing function when the system parameter changed during mechanical arm's load varied. The adaptive input shaping algorithm based on recursive least square method (RLS) requires no system identification. The residual vibration of output signal is used as the input of the algorithm to calculate the impulse time and amplitude of shaper. An adaptive forgetting factor updating algorithm is proposed to improve the control performance in variable load condition. The experimental results show that the adaptive forgetting factor input shaper greatly reduces the residual vibration. ? 2023 IEEE.