Adaptive Fuzzy Fault Tolerant Control for Robot Manipulators With Fixed-Time Convergence

被引:43
作者
Van, Mien [1 ]
Sun, Yuzhu [1 ]
Mcllvanna, Stephen [1 ]
Nguyen, Minh-Nhat [1 ]
Khyam, Mohammad Omar [2 ]
Ceglarek, Dariusz [3 ]
机构
[1] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT71NN, North Ireland
[2] Cent Queensland Univ, Sch Engn & Technol, Melbourne, Vic 3000, Australia
[3] Univ Warwick, WMG, Coventry CV47AL, England
基金
英国工程与自然科学研究理事会; 英国自然环境研究理事会;
关键词
Robots; Convergence; Fuzzy logic; Backstepping; Robustness; Manipulator dynamics; Artificial neural networks; Backsepping control; control of robots; fault tolerant control; fixed-time convergence; fuzzy logic system; SLIDING MODE CONTROL; TRACKING CONTROL; NONLINEAR-SYSTEMS; SCHEME; IDENTIFICATION; REDUNDANT; SUBJECT;
D O I
10.1109/TFUZZ.2023.3247693
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article aims to resolve the three major issues of fault tolerant control (FTC) for robot manipulators: 1) the faster response, lower tracking errors, lower chattering, and higher robustness of the FTC, 2) the requirement of partial or full knowledge of robot dynamics for the design of model-based FTC, and 3) the global fixed-time convergence of the system. First, a fixed-time controller based on a backstepping control is designed and its disadvantages are analyzed. Then, an adaptive fuzzy backstepping control is developed to enhance the tracking performance of the system. The proposed approach does not require the full prior knowledge of robot dynamic model, thus facilitating implementation of the controller in practical applications. In addition, the tracking errors of the system will be practically convergent within a fixed-time, which provides additional system information in advance. The fixed time convergence of the system is mathematically proved and the performance of the system is demonstrated for FTC of a PUMA560 robot.
引用
收藏
页码:3210 / 3219
页数:10
相关论文
共 45 条
[1]  
Armstrong B., 1986, Proceedings 1986 IEEE International Conference on Robotics and Automation (Cat. No.86CH2282-2), P510
[2]   Internal model based fault tolerant control of a robot manipulator [J].
Bonivento, C ;
Gentili, L ;
Paoli, A .
2004 43RD IEEE CONFERENCE ON DECISION AND CONTROL (CDC), VOLS 1-5, 2004, :5260-5265
[3]   Discrete-Time Framework for Fault Diagnosis in Robotic Manipulators [J].
Caccavale, Fabrizio ;
Marino, Alessandro ;
Muscio, Giuseppe ;
Pierri, Francesco .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2013, 21 (05) :1858-1873
[4]   Adaptive PID-like fault-tolerant control for robot manipulators with given performance specifications [J].
Cao, Ye ;
Song, Yong-Duan .
INTERNATIONAL JOURNAL OF CONTROL, 2020, 93 (03) :377-386
[5]   Manipulator Fault Diagnosis via Higher Order Sliding-Mode Observers [J].
Capisani, Luca Massimiliano ;
Ferrara, Antonella ;
de Loza, Alejandra Ferreira ;
Fridman, Leonid M. .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2012, 59 (10) :3979-3986
[6]   Adaptive Fuzzy Practical Fixed-Time Tracking Control of Nonlinear Systems [J].
Chen, Ming ;
Wang, Huanqing ;
Liu, Xiaoping .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (03) :664-673
[7]   Finite-Time Consensus Tracking Neural Network FTC of Multi-Agent Systems [J].
Dong, Guowei ;
Li, Hongyi ;
Ma, Hui ;
Lu, Renquan .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 32 (02) :653-662
[8]   Command-filtered fixed-time trajectory tracking control of surface vehicles based on a disturbance observer [J].
Gao, Zhenyu ;
Guo, Ge .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2019, 29 (13) :4348-4365
[9]   Real-time failure-tolerant control of kinematically redundant manipulators [J].
Groom, KN ;
Maciejewski, AA ;
Balakrishnan, V .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 1999, 15 (06) :1109-1116
[10]   Event-Triggered Robust Adaptive Sliding Mode Fault-Tolerant Control For Nonlinear Systems [J].
Guo, Bin ;
Chen, Yong .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (11) :6982-6992