Tracking Control With Adjustable Trajectory Envelope for Cable-Driven Robots

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS
Haining Sun;Rongqiao Zhang;Ruihang Ji;Xiaoqiang Tang;Shuzhi Sam Ge
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引用次数: 0

Abstract

In industrial applications, insufficient motor torque and overload issues can limit the control force in cable-driven robots (CDRs), affecting the stability and robustness of trajectory tracking control. This work presents a specialized tracking controller to achieve stable trajectory tracking under constrained control forces. The controller incorporates a trajectory envelope system that actively adjusts the permissible range of the actual trajectory. When control forces approach their upper limits, the envelope automatically expands and reduces the precision requirement for trajectory tracking. The controller then ensures that the actual trajectory remains within the designated permissible boundaries, thereby maintaining controllable trajectory tracking. The stability of the control system is validated using the Lyapunov method. Experimental validations on CDRs with one, two, and four cables are conducted. Both simulations and experiments confirm the effectiveness of the proposed tracking controller under conditions of constrained motor output torque.
缆索驱动机器人轨迹包络可调跟踪控制
在工业应用中,电机转矩不足和过载问题会限制电缆驱动机器人(cdr)的控制力,影响轨迹跟踪控制的稳定性和鲁棒性。本文提出了一种专门的跟踪控制器,以实现在约束控制力下的稳定轨迹跟踪。控制器包含一个轨迹包络系统,该系统可以主动调整实际轨迹的允许范围。当控制力接近其上限时,包络线自动扩展,降低了轨迹跟踪的精度要求。然后,控制器确保实际轨迹保持在指定的允许边界内,从而保持可控的轨迹跟踪。利用李亚普诺夫方法验证了控制系统的稳定性。对单、双、四根电缆的话单进行了实验验证。仿真和实验验证了该跟踪控制器在电机输出转矩受限条件下的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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