Fault detection and isolation in robotic manipulators via neural networks: A comparison among three architectures for residual analysis

DOI10.1002/rob.1029zbMath0986.68154OpenAlexW2084559623MaRDI QIDQ2744214

Marco H. Terra, Renato Tinós

Publication date: 13 June 2002

Published in: Journal of Robotic Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rob.1029

zbMATH Keywords

robotic manipulatorsartificial neural networks-based fault detection

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Artificial intelligence for robotics (68T40)

Related Items (1)

Dynamic learning-based fault tolerant control for robotic manipulators with actuator faults

Uses Software

• Robotics

Cites Work

• Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy - a survey and some new results
• Fuzzy logic and neural network applications to fault diagnosis
• Application of artificial neural networks in process fault diagnosis
• Confidence estimation of GMDH neural networks and its application in fault detection systems
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