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Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer

1
Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 291, Korea
2
Department of Creative Convergence Engineering, Hanbat National University, Daejeon 341-58, Korea
*
Authors to whom correspondence should be addressed.
Energies 2019, 12(8), 1412; https://doi.org/10.3390/en12081412
Received: 1 February 2019 / Revised: 3 April 2019 / Accepted: 4 April 2019 / Published: 12 April 2019
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Abstract

This study seeks an advanced sensor fault diagnosis algorithm for DC/DC boost converters governed by nonlinear dynamics with parameter and load uncertainties. The proposed algorithm is designed with a combination of proportional-type state observer and disturbance observer (DOB) without integral actions. The convergence, performance recovery and offset-free properties of the proposed algorithm are derived by analyzing the estimation error dynamics. An optimization process to assign the optimal feedback gain for the state observer is also provided. Finally, a fault diagnosis criteria is introduced to identify the location and type of sensor faults online using normalized residuals. The experimental results verify the effectiveness of the suggested technique under variable operating conditions and three types of sensor faults using a prototype 3 kW DC/DC boost converter. View Full-Text
Keywords: DC/DC boost converter; nonlinear dynamics; parameter variation; fault diagnosis; convergence analysis DC/DC boost converter; nonlinear dynamics; parameter variation; fault diagnosis; convergence analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Choi, K.; Kim, K.-S.; Kim, S.-K. Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer. Energies 2019, 12, 1412.

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