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

Abstract

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.