Adaptive fuzzy fault tolerant control for robot manipulators with fixed-time convergence

Mien Van, Yuzhu Sun, Stephen Mcllvanna, Nguyen Minh Nhat, Mohammad Omar Khyam, Dariusz Ceglarek

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This paper aims to resolve the three major issues of fault tolerant control (FTC) for robot manipulators: (i) the faster response, lower tracking errors, lower chattering and higher robustness of the FTC, (ii) the requirement of partial or full knowledge of robot dynamics for the design of modelbased FTC, and (iii) the global fixed-time convergence of the system. First, a fixed-time controller based on a backstepping control is designed and its disadvantages are analysed. 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.
Original languageEnglish
JournalIEEE Transactions on Fuzzy Systems
Early online date22 Feb 2023
Publication statusEarly online date - 22 Feb 2023


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