MCE-based Direct FTC Method for Dynamic Positioning of Underwater Vehicles with Thruster Redundancy

This paper presents an active model-based FTC (fault-tolerant control) method for the dynamic positioning of a class of underwater vehicles with thruster redundancy. Compared to the widely used state and parameter estimation methods, this proposed scheme directly utilizes the vehicle's motion control error (MCE) to construct a residual for detecting thruster faults and failures in the steady state of the control system. In the case of thruster fault identification, the most difficult aspect is that the actual control input with thruster faults is unknown. However, through a detailed and precise analyses of MCE variation trends in the case of thruster faults, highly useful information about this unknown control input can be extracted. This characteristic also serves as the foundation for the novel scheme proposed in this paper. As for control reconfiguration, it is straightforward since the thrust losses can be directly estimated as a result of the identification process. Numerical studies with the real world vehicle model are also carried out to demonstrate the effectiveness of the proposed method.

Publication Details

Journal
ArXiv.org
Published
2025-03-24
Primary Topic
Adaptive Control of Nonlinear Systems
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article

MCE-based Direct FTC Method for Dynamic Positioning of Underwater Vehicles with Thruster Redundancy

ArXiv.org
Adaptive Control of Nonlinear Systems
article

MCE-based Direct FTC Method for Dynamic Positioning of Underwater Vehicles with Thruster Redundancy

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Abstract

This paper presents an active model-based FTC (fault-tolerant control) method for the dynamic positioning of a class of underwater vehicles with thruster redundancy. Compared to the widely used state and parameter estimation methods, this proposed scheme directly utilizes the vehicle's motion control error (MCE) to construct a residual for detecting thruster faults and failures in the steady state of the control system. In the case of thruster fault identification, the most difficult aspect is that the actual control input with thruster faults is unknown. However, through a detailed and precise analyses of MCE variation trends in the case of thruster faults, highly useful information about this unknown control input can be extracted. This characteristic also serves as the foundation for the novel scheme proposed in this paper. As for control reconfiguration, it is straightforward since the thrust losses can be directly estimated as a result of the identification process. Numerical studies with the real world vehicle model are also carried out to demonstrate the effectiveness of the proposed method.

ArXiv.org
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Adaptive Control of Nonlinear Systems
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