An Impulsive Approach to State Estimation for Multirate Singularly Perturbed Complex Networks Under Bit Rate Constraints
Abstract
In this article, the problem of ultimately bounded state estimation is investigated for discrete-time multirate singularly perturbed complex networks under the bit rate constraints, where the sensor sampling period is allowed to differ from the updating period of the networks. The facilitation of communication between sensors and the remote estimator through wireless networks, which are subject to bit rate constraints, involves the use of a coding-decoding mechanism. For efficient estimation in the presence of periodic measurements, a specialized impulsive estimation method is developed, which aims to carry out impulsive corrections precisely at the instants when the measurement signal is received by the estimator. By employing the iteration analysis method under the impulsive mechanism, a sufficient condition is established that ensures the exponential boundedness of the estimation error dynamics. Furthermore, an optimization algorithm is introduced for addressing the challenges related to bit rate allocation and the design of desired estimator gains. Within the presented theoretical framework, the correlation between estimation performance and bit rate allocation is elucidated. Finally, a simulation example is provided to demonstrate the validity of the proposed estimation approach.10.13039/501100019033-Key Area Research and Development Program of Guangdong Province (Grant Number: 2021B0101410005); 10.13039/501100003453-Natural Science Foundation of Guangdong Province of China (Grant Number: 2021A1515011634 and 2021B1515420008); 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: U22A2044 and 62206063); Local Innovative and Research Teams Project of Guangdong Special Support Program of China (Grant Number: 2019BT02X353); 10.13039/501100004543-China Scholarship Council (Grant Number: 202208440312)Similar works
Full text
Last time updated on 27/03/2025
This paper was published in Brunel University Research Archive.
Having an issue?
Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.