An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

A robot manipulator is a multi-degree-of-freedom and nonlinear system that is used in various applications, including the medical area and automotive industries. Uncertain conditions in which a robot manipulator operates, as well as its nonlinearities, represent challenges for fault diagnosis and fa...

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Bibliographic Details
Main Authors: Farzin Piltan, Alexander E. Prosvirin, Muhammad Sohaib, Belem Saldivar, Jong-Myon Kim
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Applied Sciences
Subjects:
fault diagnosis
variable structure observer
backstepping algorithm
neural network
machine learning technique
support vector machine
adaptive method
fuzzy logic approach
Online Access:https://www.mdpi.com/2076-3417/10/4/1344

Internet

https://www.mdpi.com/2076-3417/10/4/1344

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