Robust Observer-Based Actuator and Sensor Fault Estimation for Discrete-Time Systems
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In this paper, a robust fault estimation method based on unknown input observer (UIO) is proposed to estimate states, actuator and sensor faults simultaneously in a discrete-time system. The UIO is designed by using an \(H_\infty \) technique, which is developed to both maintain the estimation error stable and reduce the disturbances that cannot be decoupled. In the first part of this paper, the observer is addressed for discrete-time linear systems subjected to sensor noise and process disturbances. In sequence, the method is extended to handle Lipschitz nonlinear systems. The proposed method is validated through two numerical examples, and a comparison between the proposed techniques and Extended Kalman Filter is presented. The results show the proposed approach as a better observer in terms of state and fault estimation, and process disturbance and sensor noise rejection.
KeywordsFault estimation Discrete-time system Robust control Linear matrix inequality (LMI) Unknown input observer (UIO)
This work is supported by the Coordination for the Improvement of Higher Education Personnel—CAPES—and the Laboratory of Automation in Petroleum—LAUT/DCA/UFRN.
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