Recursive zonotopic set-membership approach for system-level prognostics with application to linear parameter-varying systems

A robust recursive zonotopic set-membership approach for remaining useful life forecasting with application to linear parameter-varying systems is proposed in this paper. The proposed approach addresses systems with degraded components formulated as a system-level prognostics problem. Thus, the critical degraded components of the system are augmented to the states resulting a nonlinear system that is reformulated as a linear parameter-varying model. Hence, joint estimation of states and parameters is adopted in a zonotopic set-membership scheme with an optimal linear matrix inequality-based tuning and assuming unknown-but-bounded noises and uncertainties. As a result, a recursive zonotopic set-membership approach is proposed for remaining useful life forecasting based on the prediction of the failure precursors of degraded systems. Finally, this approach is tested on a DC-DC converter case study with unknown degradation behaviors, and the obtained results show the estimation and the forecasting accuracy of this methodology.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes a robust recursive zonotopic set-membership approach for remaining useful life forecasting of linear parameter-varying systems with degraded components. The approach formulates the degraded components as a system-level prognostics problem and reformulates it as a linear parameter-varying model. It adopts joint estimation of states and parameters in a zonotopic set-membership scheme with optimal tuning based on linear matrix inequality. The approach is applied to predict the failure precursors of degraded systems and tested on a DC-DC converter case study with unknown degradation behaviors, demonstrating its estimation and forecasting accuracy.