This paper considers the design of a proportional integral observer (PIO) for simultaneous disturbance attenuation and fault detection. Unlike a proportional observer, an integral observer alone suffices to achieve good convergence and filtering properties when sensor noise is present in the system. On the other hand, a proportional integral observer makes it possible to decouple the modeling uncertainties while estimating states and faults with satisfactory convergence properties. We show that a generalized P I 0 structure, a proportional integral fading observer (PIFO), facilitates the design procedure for achieving the above goal.
This paper proposes a general observer structure which can be employed in various estimation and control problems. The starting point is the proportional integral (PI) observer which has been shown to be effective not only in loop transfer recovery (LTR) but also in estimating and accommodating disturbances. The connections of PI observer to disturbance observer (DO) and unknown input observer (UIO) are established. We show that PI structure can be further generalized to PI adaptive observer and PI observer with fading property. The PI adaptive (PIA) observer expands the applicability of integral action to systems with unknown parameters, while the PI fading (PIF) observer can also accommodate transitory disturbances of unknown origin. It is also shown that, when process and sensor noises are present, a PI Kalman filter can be used to achieve the same goal. A systematic design procedure is developed for estimating both the state and the unknown inputs of a dynamic system. The results presented in this paper is applicable directly to fault detection and isolation (FDI) of systems under sensor and / or actuator failures.
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