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Experimental Study on Support Vector Machine-Based Early Detection for Sensor Faults and Operator-Based Robust Fault Tolerant Control
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Experimental Study on Support Vector Machine-Based Early Detection for Sensor Faults and Operator-Based Robust Fault Tolerant Control
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Journal Article
Experimental Study on Support Vector Machine-Based Early Detection for Sensor Faults and Operator-Based Robust Fault Tolerant Control
2022
Overview
Considering sensor faults for a thermoelectric cooler actuated by Peltier devices, this work proposes an operator-based robust nonlinear fault tolerant controller (FTC) integrated with early fault detection using a support vector machine (SVM). Firstly, a physical model is formulated based on the law of heat transfer, and the estimated model is derived based on Volterra identification. Then, an operator-based robust nonlinear control system is employed to compensate for uncertainties and to eliminate the effects of coupling. Furthermore, FTC integrated with SVM-based early fault detection is designed to improve the safety performance in the case of sensor faults. The simulation results indicate that SVM-based fault detection can shorten the detection time in comparison to the conventional method without the SVM classier. The experiment results are utilized to verify the tracking performance of the proposed FTC method in the case study.
Publisher
MDPI AG
Subject
