Fault-Tolerant Prescribed Performance Control of Ship Autopilot System Against Multiplicative Sensor Fault

This paper investigates the tracking control issue for the ship autopilot system with multiplicative sensor fault and unknown disturbance. In order to resolve this problem, we put forward a fault tolerant prescribed performance control approach. Two barrier functions are included in the control law to address the error constraint. It accomplishes reference tracking with the prescribed rate and precision, without the speciffc information about the multiplicative sensor fault and disturbance. Moreover, the proposed control preserves the simplicity of the controller, without identiffcation, approximation, estimation, or derivation. At last, a simulation study is given to demonstrate the aforementioned theoretical finding.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/icaisisas64483.2025.11051772
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Fault-Tolerant Prescribed Performance Control of Ship Autopilot System Against Multiplicative Sensor Fault

Jin-Xi Zhang, Hongwei Jia
Fault Detection and Control Systems
article

Fault-Tolerant Prescribed Performance Control of Ship Autopilot System Against Multiplicative Sensor Fault

Jin-Xi Zhang, Hongwei Jia
article en

Abstract

This paper investigates the tracking control issue for the ship autopilot system with multiplicative sensor fault and unknown disturbance. In order to resolve this problem, we put forward a fault tolerant prescribed performance control approach. Two barrier functions are included in the control law to address the error constraint. It accomplishes reference tracking with the prescribed rate and precision, without the speciffc information about the multiplicative sensor fault and disturbance. Moreover, the proposed control preserves the simplicity of the controller, without identiffcation, approximation, estimation, or derivation. At last, a simulation study is given to demonstrate the aforementioned theoretical finding.

State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Liaoning Province, State Key Laboratory of Industrial Control Technology, Research and Development
Openalex Percentile: Top 82%
Fault Detection and Control Systems
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