Target Tracking and Data Fusion in Sensor Networks
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Abstract
Abstract
A new fault-tolerant estimating approach for unmanned aerial vehicle (UAV) dynamics in the presence of sensor/actuator faults is proposed, which is both adaptive and robust. This study discusses how to choose between adaptive and robust approaches when a sensor or actuator fails. We provide an adaptive method with Q-adaptation as well as a robust method with R-adaptation. The Kalman filter detects faults using the chi-square distribution of the normalized quadratic innovation function (NQI). After detecting a fault, it is recommended to run both R-adaptive and Q-adaptive Kalman filters concurrently and compare their estimation capabilities to distinguish between sensor and actuator faults. As a performance criterion, the mean-squared residuals between estimation and extrapolation values of robust and adaptive filters are proposed.
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@article{Hajiyev2026Robust,
title = {Robust Adaptive Kalman Filter against Sensor/Actuator Faults},
author = {Chingiz Hajiyev},
journal = {WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL},
year = {2026},
doi = {10.37394/23203.2026.21.16},
url = {https://doi.org/10.37394/23203.2026.21.16}
}FAQ
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