Suppr超能文献

基于可拓理论与 Neutrosophic 逻辑决策的混合位姿/力步行机器人控制

The Hybrid Position/Force Walking Robot Control Using Extenics Theory and Neutrosophic Logic Decision.

机构信息

Institute of Solid Mechanics of the Romanian Academy, 15 C. Mille, 010141 Bucharest, Romania.

出版信息

Sensors (Basel). 2022 May 11;22(10):3663. doi: 10.3390/s22103663.

Abstract

This paper presents a hybrid force/position control. We developed it for a hexapod walking robot that combines multiple bipedal robots to increase its load. The control method integrated Extenics theory with neutrosophic logic to obtain a two-stage decision-making algorithm. The first stage was an offline qualitative decision-applying Extenics theory, and the second was a real-time decision process using neutrosophic logic and DSmT theory. The two-stage algorithm separated the control phases into a kinematic control method that used a PID regulator and a dynamic control method developed with the help of sliding mode control (SMC). By integrating both control methods separated by a dynamic switching algorithm, we obtained a hybrid force/position control that took advantage of both kinematic and dynamic control properties to drive a mobile walking robot. The experimental and predicted results were in good agreement. They indicated that the proposed hybrid control is efficient in using the two-stage decision algorithm to drive the hexapod robot motors using kinematic and dynamic control methods. The experiment presents the robot's foot positioning error while walking. The results show how the switching method alters the system precision during the pendulum phase compared to the weight support phase, which can better compensate for the robot's dynamic parameters. The proposed switching algorithm directly influences the overall control precision, while we aimed to obtain a fast switch with a lower impact on the control parameters. The results show the error on all axes and break it down into walking stages to better understand the control behavior and precision.

摘要

本文提出了一种力/位置混合控制方法。我们为一个六足步行机器人开发了这种控制方法,该机器人将多个双足机器人结合在一起,以增加其负载。该控制方法将可拓学理论与中性逻辑集成在一起,获得了两阶段决策算法。第一阶段是离线定性决策——应用可拓学理论,第二阶段是使用中性逻辑和 DSmT 理论进行实时决策过程。两阶段算法将控制阶段分为使用 PID 调节器的运动学控制方法和借助滑模控制(SMC)开发的动力学控制方法。通过将由动态切换算法分隔的两种控制方法集成在一起,我们获得了一种力/位置混合控制方法,该方法利用运动学和动力学控制特性来驱动移动步行机器人。实验和预测结果非常吻合。结果表明,所提出的混合控制方法在使用两阶段决策算法驱动六足机器人电机方面非常有效,它使用运动学和动力学控制方法。实验展示了机器人在行走过程中的足部定位误差。结果表明,与重量支撑阶段相比,切换方法如何在摆锤阶段改变系统精度,可以更好地补偿机器人的动态参数。所提出的切换算法直接影响整体控制精度,而我们的目标是获得快速切换,同时对控制参数的影响较小。结果显示了所有轴上的误差,并将其分解为行走阶段,以便更好地理解控制行为和精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21da/9143458/fac92b05dbef/sensors-22-03663-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验