A survey of models of degradation for control applications

Zagórowska, Marta; Wu, Ouyang; Ottewill, James R.; Reble, Marcus; Thornhill, Nina F.

doi:10.1016/j.arcontrol.2020.08.002

Cited by 26 publications

(22 citation statements)

References 148 publications

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“…of ( 8). (ii) Fault 1 occurrence (Figure 2 red-dashed path): The plant (1) assumes the model configuration (6) with j = 1. Then,…”

Section: F I G U R Ementioning

confidence: 99%

“…Then, the proposition statement directly follows. ▪ Finally, the determination to be performed offline of the terminal regions  j 0 , j = 0, 1, … , l, with related control gains K j , j = 0, 1, … , l, are here introduced by considering the system dynamics (6). It can be performed by exploiting switching stability arguments and technicalities proposed in References 22 and 23:…”

Section: F I G U R E 2 Healthy-to-faulty Transitionsmentioning

confidence: 99%

“…Proposition 2. Given the switching system (6), there exist pairs ( j 0 , K j ), j = 0, 1, … , l, with  j 0 ≠ ∅ robustly invariant sets with associated K j stabilizing state feedback control laws for each model configuration of (6) complying with the input constraints (3), if the following set-valued inclusions are satisfied:…”

Section: F I G U R E 2 Healthy-to-faulty Transitionsmentioning

confidence: 99%

“…For these reasons, prognostics and health monitoring (PHM) for actuators are gaining interest among researchers 3,5,6 . Among them, a particular focus is related to the determination of the actuators' healthy status in order to estimate their time‐to‐failure or remaining‐useful‐lifetime (RUL) 7 .…”

Section: Introductionmentioning

confidence: 99%

“…For these reasons, prognostics and health monitoring (PHM) for actuators are gaining interest among researchers. 3,5,6 Among them, a particular focus is related to the determination of the actuators' healthy status in order to estimate their time-to-failure or remaining-useful-lifetime (RUL). 7 The latter quantity can be exploited in a maintenance plan to schedule future interventions to prevent undesired monitored device crash.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Predictive maintenance of actuators in linear systems: A receding horizon set‐theoretic approach

Tedesco

Akram

Forouzanfar

et al. 2022

Intl J Robust & Nonlinear

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This work is focused on a model predictive control (MPC) based approach for the regulation of systems whose actuators are subject to loss of effectiveness. Such a degradation process, whose evolution is assumed to be measurable and predictable, can lead to actuators breakdown whenever certain thresholds are exceeded. Within this context, if the control problem is defined with ad hoc operational constraints and/or running costs, the intrinsic MPC capability of mitigating faulty events arises. To this end, the proposed control scheme consists of two modules: the former is in charge of performing a prognostic activity on actuators' health, while the second one reconfigures the control law on the basis of actuators' degradation information. The core of the proposed method relies on modeling healthy and faulty plant configurations via a switching systems paradigm that is instrumental to offline determine sequences of precomputed inner approximations of one-step ahead controllable sets. Such regions are online selected by a switching logic in order to determine a control signal properly weighted on the basis of the measured actuators degradation level.

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“…of ( 8). (ii) Fault 1 occurrence (Figure 2 red-dashed path): The plant (1) assumes the model configuration (6) with j = 1. Then,…”

Section: F I G U R Ementioning

confidence: 99%

Section: F I G U R E 2 Healthy-to-faulty Transitionsmentioning

confidence: 99%

Section: F I G U R E 2 Healthy-to-faulty Transitionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Predictive maintenance of actuators in linear systems: A receding horizon set‐theoretic approach

Tedesco

Akram

Forouzanfar

et al. 2022

Intl J Robust & Nonlinear

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show abstract

Health Indices Construction for Stochastically Deteriorating Feedback Control Systems

Gong

Huynh

Langeron

et al. 2022

Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future

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Degradation Simulator for Infinite Horizon Controlled Linear Time-Invariant Systems

Dadash

Björsell

2023

Studies in Systems, Decision and Control

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Diagnosis, fault prediction, and Remaining Useful Life (RUL) estimation are among the predictive maintenance research subjects used for maintenance cost reduction. Using the available data with different machine learning methods, especially deep learning methods, the accuracy of estimation and prediction of faults and RUL have increased dramatically. However, due to the statistical nature of the machine learning methods and the limitations of available datasets, physically interpreting this information might be impossible. On the other hand, controlling the degradation and faults in the machines as the optimum predictive maintenance solution needs the physical interpretation of the method's outcome. In order to test the new process-based methods for degradation and fault control, datasets with more information are required (compared to available datasets). In this article, we introduce an open-source degradation simulator for linear systems. This simulator can simulate the degradation in closed-loop machines whose dynamics are known. It is also possible to simulate different degradation models for different system parts simultaneously by adding different processes and output noise to the system. This simulator can generate enough data to test new machine learning-based predictive maintenance methods.

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A survey of models of degradation for control applications

Cited by 26 publications

References 148 publications

Predictive maintenance of actuators in linear systems: A receding horizon set‐theoretic approach

Predictive maintenance of actuators in linear systems: A receding horizon set‐theoretic approach

Health Indices Construction for Stochastically Deteriorating Feedback Control Systems

Degradation Simulator for Infinite Horizon Controlled Linear Time-Invariant Systems

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