Abstract
The main objective of this paper is to develop an actuator and sensor fault estimation framework taking into account various uncertainty sources. In particular, these are divided into three groups: sensor measurement noise, process-external exogenous disturbances, as well as unknown fault dynamics. Unlike the approaches presented in the literature, here they are not processed in the same way but treated separately in a suitably tailored fashion. Finally, the approach resolves to minimizing their effect on the fault estimation error in either the or sense. As a result, a mixed performance–based actuator fault estimation framework is obtained, along with its convergence conditions. The final part of the paper presents performance analysis results obtained for a DC servo-motor. Subsequently, another three-tank-system-based example is presented. In both cases, the proposed approach is compared with an alternative one, which clearly exhibits its superiority.
Highlights
The problem of recovering immeasurable quantities has received considerable research attention. It was initiated with the advent of the celebrated Kalman filter and Luenberger observer [1,2], which are traditionally applied to the state estimation of linear systems
The research attention was focused on unknown input observers (UIOs) [2,3,4], which were used for both control and fault diagnosis (FD) [5,6] purposes
To propose a novel fault estimator structure capable of estimating possibly simultaneous sensor and actuator faults; the proposed estimator can tackle both an exogenous process disturbance with finite energy and a random measurement noise; the estimator design procedure allows the minimizing of noise/disturbance effects on both state and fault estimation errors; the estimator design procedure yields a fault estimator with a guaranteed trade-off between fault and state estimation quality
Summary
The problem of recovering immeasurable quantities has received considerable research attention. It is an obvious fact that their estimation quality can be impaired by external exogenous process disturbances and measurement noise To tackle this unappealing phenomenon, two main strategies can be distinguished, namely decoupling and attenuation. To propose a novel fault estimator structure capable of estimating possibly simultaneous sensor and actuator faults; the proposed estimator can tackle both an exogenous process disturbance with finite energy and a random measurement noise; the estimator design procedure allows the minimizing of noise/disturbance effects on both state and fault estimation errors; the estimator design procedure yields a fault estimator with a guaranteed trade-off between fault and state estimation quality.
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