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Remaining Useful Life (RUL) Control of Controlled Systems under Degradation
  • Mônica S. Félix,
  • John J. Martinez,
  • Christophe Berenguer
Mônica S. Félix
Universite Grenoble Alpes Ense3
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John J. Martinez
Universite Grenoble Alpes Ense3

Corresponding Author:john.martinez@gipsa-lab.fr

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Christophe Berenguer
Universite Grenoble Alpes Ense3
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Abstract

Remaining Useful Life (RUL) has become widely recognized as a key metric for evaluating system reliability within the field of Prognostic and Health Management (PHM). It plays a crucial role in predicting a system’s health status and its expected lifespan. While significant efforts have been directed towards accurately estimating RUL, the process of decision-making regarding health management and potential adjustments to equipment lifespan still poses questions. This study introduces a state-space methodology designed to effectively manage RUL and, thus, the end-of-life of a degrading system, particularly focusing on controlled operation systems. Through an investigation of the relationship between the operational dynamics of the system and its aging process, the study specifically concentrates on regulating the degradation rate experienced during operation. A robust design method of an observer and a controller is presented to effectively govern the degradation trajectory, allowing for the achievement of an acceptable level of deterioration within a desired average lifetime. To demonstrate the performance and practical application of the proposed approach, it is applied to a variable-speed wind turbine with a flexible shaft subjected to torsion effects. The results highlight the benefits of using RUL control as a Health-Aware Control (HAC) strategy, aiming to find an optimal balance between reliability and production objectives. This study makes a valuable contribution to the field of reliability engineering by providing insight into managing the end-of-life of controlled processes suffering from aging. It is showed that the RUL control problem can be conveniently expressed as the problem of controlling a polytopic uncertain system. For this reason, a discrete-time robust LQR controller design is presented for solving the polytopic control design problem.
05 Jun 2024Submitted to International Journal of Robust and Nonlinear Control
05 Jun 2024Submission Checks Completed
05 Jun 2024Assigned to Editor
05 Jun 2024Review(s) Completed, Editorial Evaluation Pending
08 Jun 2024Reviewer(s) Assigned