基于模糊控制的机械臂故障识别改进  

Improvement of Robot Arm Fault Identification Based on Fuzzy Control

作　　者：王晶晶 WANG Jing-jing(Department of Mechanical and Electrical Engineering,Yantai Gold College,Yantai 265401 China)

机构地区：[1]烟台黄金职业学院机电工程系,山东烟台265401

出　　处：《自动化技术与应用》2024年第8期20-23,共4页Techniques of Automation and Applications

摘　　要：设计一套有效的故障检测与识别程序,是维护机器人机械臂健康、保证操作安全运行的必要条件。为了解决机器人机械臂故障检测和误差识别困难的问题,提出一种基于ARX-Laguerre模糊控制的鲁棒性观测器混合故障识别方法。将Takagi-Sugeno(T-S)模糊算法应用于ARX-Laguerre检测中,以提升故障判断的性能,扰动机械臂操纵。仿真结果表明,ARX-Laguerre算法、PI观测技术、滑动估计方法和T-S模糊方法具有收敛速度快、精度高等优点。通过机器人执行器测试该方法的有效性,表明该算法的先进性及可用性。It designs an effective fault detection and identification program is a necessary condition to maintain the health of the robot arm and ensure the safe operation.In order to solve the difficulty of fault detection and error identification of robot manipulators,a robust observer hybrid fault identification method based on ARX-Laguerre fuzzy control is proposed.Takagi Sugeno(T-S)fuzzy algorithm is applied to ARX-Laguerre detection to improve the performance of fault diagnosis and disturb the manipulator operation.The simulation results show that ARX-Laguerre algorithm,PI observation technique,sliding estimation method and T-S fuzzy method have the advantages of fast convergence and high accuracy.The effectiveness of the method is tested by the robot actuator,which shows the progressiveness and availability of the algorithm.

关 键 词：故障检测与识别 ARX-Laguerre模糊控制 T-S模糊算法 PI观测技术 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]