Event-triggered filtering for uncertain system with missing measurements
Xiujuan Zheng, Huajing Fang · 2016
The robust recursive filter is proposed for a class of multi-sensor system with parameter uncertainties, stochastic nonlinearities, event-triggered transmission and missing measurements in this paper. Both the parameter uncertainties and nonlinearities enter into the system in a random way characterized by random variables obeying the Gaussian distribution. By the event-triggered transmission, measurements are transmitted only when certain conditions are satisfied with different triggering thresholds. The missing measurements of each sensor has individual missing rates which are independent of each other. At each sampling time, the robust recursive filter is designed in the minimum-variance sense. A simulation example is employed to illustrate the effectiveness of the proposed method.