Remaining Useful Lifetime Prognosis of Controlled Systems: A Case of Stochastically Deteriorating Actuator

This paper addresses the case of automatic controlled system which deteriorates during its operation because of components’ wear or deterioration. Depending on its specific closed-loop structure, the controlled system has the ability to compensate for disturbances affecting the actuators which can r...

Full description

Saved in:
Bibliographic Details
Published inMathematical problems in engineering Vol. 2015; no. 2015; pp. 1 - 16
Main Authors Nguyen, Danh Ngoc, Grall, Antoine, Dieulle, Laurence
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2015
Hindawi Limited
Subjects
Actuators
Closed loops
Computer Science
Computer simulation
Control systems
Controllers
Deterioration
Dynamical systems
Dynamics
Engineering Sciences
Feedback control systems
Markov processes
Mathematical models
Mathematics
Monte Carlo simulation
Optimization and Control
Prognosis
Proportional integral derivative
Random variables
Service life assessment
Systems and Control
Systems design
Online AccessGet full text

Cover

More Information
Summary:This paper addresses the case of automatic controlled system which deteriorates during its operation because of components’ wear or deterioration. Depending on its specific closed-loop structure, the controlled system has the ability to compensate for disturbances affecting the actuators which can remain partially hidden. The deterioration modeling and the Remaining Useful Lifetime (RUL) estimation for such closed-loop dynamic system have not been addressed extensively. In this paper, we consider a controlled system with Proportional-Integral-Derivative controller. It is assumed that the actuator is subject to shocks that occur randomly in time. An integrated model is proposed to jointly describe the state of the controlled process and the actuator deterioration. Only the output of the controlled system is available to assess its health condition. By considering a Piecewise Deterministic Markov Process, the RUL of the system can be estimated by a two-step approach. In the first step referred as the “Diagnosis” step, the system state is estimated online from the available monitoring observations by using a particle filtering method. In the second step referred as the “Prognosis” step, the RUL is estimated as a conditional reliability by Monte Carlo simulation. To illustrate the approach, a simulated tank level control system is used.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1024-123X
1563-5147
DOI:10.1155/2015/356916