1. Recursive filtering for stochastic parameter systems with measurement quantizations and packet disorders
- Author
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Fuad E. Alsaadi, Zidong Wang, Dan Liu, and Yurong Liu
- Subjects
Recursive filtering ,0209 industrial biotechnology ,Logarithm ,Computer science ,Stochastic process ,Network packet ,Applied Mathematics ,020206 networking & telecommunications ,02 engineering and technology ,Filter (signal processing) ,Computational Mathematics ,020901 industrial engineering & automation ,Transmission (telecommunications) ,Stochastic parameter systems ,0202 electrical engineering, electronic engineering, information engineering ,Filtering problem ,Recursive filter ,Packet disorders ,Measurement quantizations ,Algorithm ,Communication channel - Abstract
In this paper, the recursive filtering problem is put forward for stochastic parameter systems subject to quantization effects and packet disorders. Before entering communication networks, measurement outputs are quantized by logarithmic quantizers. The packet disorders result from transmission delays which are provoked by communication constraints and occur randomly in the sensor-to-filter channel. In case of measurement quantizations and packet disorders, the objective of this paper is to devise a novel recursive filter approach that is capable of 1) guaranteeing desired upper bounds on the resultant filtering error covariances; and 2) minimizing such upper bounds by acquiring appropriate filter gains. Furthermore, sufficient conditions are established to ensure the mean-square boundedness of filtering errors by means of stochastic analysis techniques. At last, simulations are given to validate the applicability of our designed approach.
- Published
- 2021