1.东南大学自动化学院,江苏 南京 210096
2.东南大学南通海洋高等研究院,江苏 南通 226010
3.英特尔边缘计算研究所,江苏 南京 211135
甘亚辉(1985年生),男;研究方向:机器人控制;E-mail:ganyahui@seu.edu.cn
收稿:2025-05-20,
录用:2025-06-03,
网络首发:2025-09-23,
纸质出版:2026-01-25
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甘亚辉,徐升,韩早等.基于模糊前馈控制的关节型机器人振动抑制算法[J].中山大学学报(自然科学版)(中英文),2026,65(01):43-51.
GAN Yahui,XU Sheng,HAN Zao,et al.Vibration suppression for articulated robot by fuzzy feedforward control[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2026,65(01):43-51.
甘亚辉,徐升,韩早等.基于模糊前馈控制的关节型机器人振动抑制算法[J].中山大学学报(自然科学版)(中英文),2026,65(01):43-51. DOI: 10.13471/j.cnki.acta.snus.ZR20250087.
GAN Yahui,XU Sheng,HAN Zao,et al.Vibration suppression for articulated robot by fuzzy feedforward control[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2026,65(01):43-51. DOI: 10.13471/j.cnki.acta.snus.ZR20250087.
提出了一种基于前馈补偿与模糊控制的混合控制策略。该方法基于精确动力学模型进行前馈控制,同时引入模糊逻辑以提升控制器的性能。首先,对机器人运行中产生振动的主要因素进行分析,并选定ISO9283标准中的估计准确度作为性能评估指标,用于量化轨迹跟踪误差与振动抑制的效果。文中将提出的模糊前馈控制算法与传统PD控制、结合前馈补偿的PD控制进行了对比。仿真结果表明,该方法在轨迹跟踪精度和振动抑制效果方面均表现出显著提升,验证了方法的有效性与优越性。
This paper presents a hybrid control strategy combining feedforward compensation and fuzzy control. The approach leverages an accurate dynamic model for feedforward control and incorporates fuzzy logic to enhance overall controller performance. Key vibration sources during robot operation are analyzed, and trajectory accuracy, as defined by ISO9283, is adopted as the evaluation metric. The proposed fuzzy feedforward controller is compared with traditional PD control and feedforward-compensated PD control. Simulation results demonstrate that the proposed method significantly improves trajectory tracking accuracy and vibration suppression, validating its effectiveness.
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