Infinite-Horizon Degradation Control Based on Optimization of Degradation-Aware Cost Function

Author:

Dadash Amirhossein Hosseinzadeh1ORCID,Björsell Niclas1ORCID

Affiliation:

1. Department of Electronics, Mathematics and Sciences, University of Gävle, 80176 Gävle, Sweden

Abstract

Controlling machine degradation enhances the accuracy of the remaining-useful-life estimation and offers the ability to control failure type and time. In order to achieve optimal degradation control, the system controller must be cognizant of the consequences of its actions by considering the degradation each action imposes on the system. This article presents a method for designing cost-aware controllers for linear systems, to increase system reliability and availability through degradation control. The proposed framework enables learning independent of the system’s physical structure and working conditions, enabling controllers to choose actions that reduce system degradation while increasing system lifetime. To this end, the cost of each controller’s action is calculated based on its effect on the state of health. A mathematical structure is proposed, to incorporate these costs into the cost function of the linear–quadratic controller, allowing for optimal feedback for degradation control. A simulation validates the proposed method, demonstrating that the optimal-control method based on the proposed cost function outperforms the linear–quadratic regulator in several ways.

Funder

European Commission within the European Regional Development Fund

Swedish Agency for Economic and Regional Growth, Region Gävleborg

Publisher

MDPI AG

Reference39 articles.

1. The Hanoverian Supply Chain Model: Modelling the impact of production planning and control on a supply chain’s logistic objectives;Schmidt;Prod. Eng.,2017

2. Toward a big data-based approach: A review on degradation models for prognosis of critical infrastructure;Prakash;J. Nondestruct. Eval. Diagn. Progn. Eng. Syst.,2021

3. Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time;Ayvaz;Expert Syst. Appl.,2021

4. Nelson, W.B. (2009). Accelerated Testing: Statistical Models, Test Plans, and Data Analysis, John Wiley & Sons.

5. Integrated optimization of quality and maintenance: A literature review;Farahani;Comput. Ind. Eng.,2021

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