A Unified Practical Predefined-Time Interval Type-2 Fuzzy NN-Based Fault-Tolerant Control for Robotic Manipulators

Fast response and safety operation are essential requirements for the tracking control of robotic manipulators. In this article, a unified predefined-time self-organizing interval type-2 fuzzy neural network control (SOIT2FNNC) framework is presented for robotic manipulators subject to actuator fail...

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Vydané v:IEEE transactions on fuzzy systems Ročník 33; číslo 9; s. 3267 - 3280
Hlavní autori: Zhao, Tao, Tian, Shiyu, Cheng, Hong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: IEEE 01.09.2025
Predmet:
Actuators
Control design
Convergence
Fault tolerance
Fault tolerant systems
Fault-tolerant control (FTC)
Fuzzy control
Fuzzy neural networks
Manipulator dynamics
model-free control
predefined-time control
robotic manipulators
Robots
self-organizing interval type-2 fuzzy neural network
Uncertainty
ISSN:1063-6706, 1941-0034
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Shrnutí:Fast response and safety operation are essential requirements for the tracking control of robotic manipulators. In this article, a unified predefined-time self-organizing interval type-2 fuzzy neural network control (SOIT2FNNC) framework is presented for robotic manipulators subject to actuator failures and uncertainties. Such a framework operates in a parallel structure where the model-free predefined-time controller guarantees the transient performance while the proposed network controller provides appropriate torques to handle failures and uncertainties, which leads to a solution for both normal and faulty conditions. Significant features of this study are that the control design does not depend on any information about system dynamics, and theoretically, the predefined-time convergence is accomplished by means of the online parameter learning algorithm. Moreover, a hierarchical self-organizing algorithm is embedded in the proposed network controller to overcome the network structure complexity and the input partition problem. Both numerical simulation and experiment results utilizing artificial faults are implemented to demonstrate the superiority of the proposed control scheme.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2025.3588146