Data-Driven State Prediction and Sensor Fault Diagnosis for Multi-Agent Systems with Application to a Twin Rotational Inverted Pendulum

Data-Driven State Prediction and Sensor Fault Diagnosis for Multi-Agent Systems with Application to a Twin Rotational Inverted Pendulum

When a multi-agent system is subjected to faults, it is necessary to detect and classify the faults in time. This paper is motivated to propose a data-driven state prediction and sensor fault classification technique. Firstly, neural network-based state prediction model is trained through historical...

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Bibliographic Details
Main Authors: Xin Lu, Xiaoxu Liu, Bowen Li, Jie Zhong
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Processes
Subjects:
data-driven
state prediction
fault classification
multi-agent system
Online Access:https://www.mdpi.com/2227-9717/9/9/1505

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