Home /Research /Adaptive Fuzzy Fault Tolerant Control for Robot Manipulators With Fixed-Time Convergence
MANIPULATION

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

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

Year
2023
Citations
76

Abstract

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.

Keywords

Control theory (sociology)BacksteppingRobustness (evolution)Computer scienceFault toleranceConvergence (economics)RobotFuzzy logicControl engineeringFuzzy control system

Related papers

Browse all MANIPULATION papers