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State and fault estimation for nonlinear systems subject to censored measurements: A dynamic event-triggered case
(Wiley, 2022) Huang, Cong; Coskun, Serdar; Zhang, Xin; Mei, Peng
In this article, the state and fault estimation (SFE) issue is studied for nonlinear systems with parameter uncertainties subject to censored measurement under the dynamic event-triggering protocol. The well-known Tobit measurement model is introduced to characterize the censored measurement and the nonlinearity satisfies specific constraints. For the energy-saving purposes, a dynamic event-triggering protocol is employed to govern the measurement transmissions between the sensor and its corresponding estimator. The primary objective of the addressed problem is to design a dynamic event-triggering estimator to estimate the system state and fault signal simultaneously such that, the upper bound (UB) of the estimation error covariance is guaranteed at each iteration, then such UB is minimized by properly choosing the estimator gain. Moreover, the boundedness analysis of the designed SFE approach is conducted firstly and then a sufficient condition is presented to validate the estimation error is stable in mean-squared sense. Lastly, two experimental results are employed to validate the feasibility of the proposed estimation algorithm.