Active fault diagnosis of 2 DoF helicopter using particle filter-based log-likelihood ratio

DOI10.1080/00207179.2021.1959067zbMath1505.93265OpenAlexW3188705748MaRDI QIDQ5056553

M. Raghappriya, S. Kanthalakshmi

Publication date: 8 December 2022

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2021.1959067

zbMATH Keywords

likelihood ratiofault diagnosisparticle filtersensornon-linear filteringactuator and component faults

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10)

Cites Work

• Simultaneous state and parameter estimation based actuator fault detection and diagnosis for an unmanned helicopter
• Likelihood function modeling of particle filter in presence of non-stationary non-Gaussian measurement noise
• Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed
• Sensor/actuator fault diagnosis based on statistical analysis of innovation sequence and Robust Kalman Filtering
• Extended state observer‐based sliding mode fault‐tolerant control for unmanned autonomous helicopter with wind gusts
• Sensor bias fault isolation in a class of nonlinear systems

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