Event-Triggering State and Fault Estimation for a Class of Nonlinear Systems Subject to Sensor Saturations

• Main Authors: Cong Huang, Bo Shen, Lei Zou, Yuxuan Shen
• Format: Article
• Language: English
• Published: MDPI AG 2021-02-01
• Series: Sensors
• Subjects: event-triggering mechanism (ETM); nonlinear system; recursive estimator; sensor saturations; state and fault estimation
• Online Access: https://www.mdpi.com/1424-8220/21/4/1242

This paper is concerned with the state and fault estimation issue for nonlinear systems with sensor saturations and fault signals. For the sake of avoiding the communication burden, an event-triggering protocol is utilized to govern the transmission frequency of the measurements from the sensor to its corresponding recursive estimator. Under the event-triggering mechanism (ETM), the current transmission is released only when the relative error of measurements is bigger than a prescribed threshold. The objective of this paper is to design an event-triggering recursive state and fault estimator such that the estimation error covariances for the state and fault are both guaranteed with upper bounds and subsequently derive the gain matrices minimizing such upper bounds, relying on the solutions to a set of difference equations. Finally, two experimental examples are given to validate the effectiveness of the designed algorithm.