多算法融合的并联食品分拣机器人末端控制方法研究
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1西南交通大学希望学院,四川 成都 610400;2昌吉学院,新疆 昌吉 831100;3四川大学锦江学院,四川 眉山 620860

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何青(1984—),女,西南交通大学希望学院副教授,硕士。E-mail:heqsmart@sohu.com

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国家统计局统计信息技术与数据挖掘重点开放实验室开放课题(编号:SDL202520)


Terminal control method of parallel food sorting robot with multi-algorithm fusion
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1Hope College, Southwest Jiaotong University, Chengdu, Sichuan 610400, China;2Changji University, Changji, Xinjiang 831100, China;3Jinjiang College, Sichuan University, Meishan, Sichuan 620860, China

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    摘要:

    目的 解决现有并联食品分拣机器人末端控制中存在的轨迹跟踪精度低、动态响应滞后、外部扰动适应性差,难以满足食品分拣高速、高精度作业需求等问题。方法 基于DELTA并联机器人的食品分拣系统,设计融合改进鲸鱼优化算法、自适应模糊控制和非奇异快速终端滑模控制的末端控制策略。通过自适应模糊控制实时调整输出增益,提高控制器跟踪精度。通过改进鲸鱼优化算法优化算法搜索策略,对整个控制器的滑模面关键参数进行全局寻优,解决传统参数手动调节导致的响应速度慢、动态特性差的问题。结合非奇异快速终端滑模控制的有限时间收敛特性,进一步增强系统抗扰动能力。通过搭建试验平台进行对比试验,验证所提控制方法的优越性。结果 与现有控制方法相比,所提多算法融合控制方法的轨迹跟踪误差降低40%以上,运行时间缩短30%以上。在实际分拣中,100,200 mm/s传送速度下,分拣成功率分别达到99.70%,98.70%,较现有方法提升4.30%~12.50%,抗扰动鲁棒性显著优于对比方法。结论 所提多算法融合控制方法能够有效解决并联食品分拣机器人末端控制精度低、响应慢、抗扰动能力弱的问题,显著提升机器人的动态响应特性和分拣作业性能,可满足食品分拣行业高速、高精度、高稳定性的作业需求。

    Abstract:

    Objective To address the problems of low trajectory tracking accuracy, delayed dynamic response, poor adaptability to external disturbances, and difficulty in meeting the requirements of high-speed and high-precision food sorting in existing end control of parallel food sorting robots.Methods A food sorting system based on a DELTA parallel robot was developed, and an end-effector control strategy integrating an improved whale optimization algorithm, adaptive fuzzy control, and nonsingular fast terminal sliding mode control was designed. Adaptive fuzzy control was used to adjust the output gain in real time to enhance controller tracking accuracy. The improved whale optimization algorithm was employed to optimize the search strategy and globally optimize key sliding mode surface parameters of the controller, addressing the problems of slow response and poor dynamic performance caused by traditional manual parameter tuning. By combining the finite-time convergence characteristics of nonsingular fast terminal sliding mode control, the system's disturbance rejection capability was further enhanced. Comparative experiments were conducted on an experimental platform to verify the superiority of the proposed control method.Results Compared with existing control methods, the proposed multi-algorithm fusion control method reduced trajectory tracking error by more than 40% and shortened running time by more than 30%. In practical sorting tests, at conveying speeds of 100 and 200 mm/s, the sorting success rates reached 99.70% and 98.70%, respectively, representing an improvement of 4.30%~12.50% over existing methods. The anti-disturbance robustness was significantly better than that of the comparison methods.Conclusion The proposed multi-algorithm fusion control method can effectively solve the problems of low end-effector control accuracy, slow response, and weak disturbance rejection in parallel food sorting robots, significantly improving dynamic response performance and sorting efficiency, and meeting the requirements of high-speed, high-precision, and high-stability operations in the food sorting industry.

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引用本文

何青,吴田峰,赵旖旎.多算法融合的并联食品分拣机器人末端控制方法研究[J].食品与机械,2026,42(6):75-82.
HE Qing, WU Tianfeng, ZHAO Yini. Terminal control method of parallel food sorting robot with multi-algorithm fusion[J]. Food & Machinery,2026,42(6):75-82.

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  • 收稿日期:2026-02-20
  • 最后修改日期:2026-05-18
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  • 在线发布日期: 2026-07-13
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