Bibliographic Review on Distributed Kalman Filtering

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this paper, a bibliographical review on distributed Kalman filtering (DKF) is provided.\ud The paper contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area

Self-triggered Stabilization of Contracting Systems under Quantization

We propose self-triggered control schemes for nonlinear systems with quantized state measurements. Our focus lies on scenarios where both the controller and the self-triggering mechanism receive only the quantized state measurement at each sampling time. We assume that the ideal closed-loop system without quantization or self-triggered sampling is contracting. Moreover, a growth rate of the open-loop system is assumed to be known. We present two control strategies that yield the closed-loop stability without Zeno behavior. The first strategy is implemented under logarithmic quantization and imposes no time-triggering condition other than setting an upper bound on inter-sampling times. The second one is a joint design of zooming quantization and periodic self-triggered sampling, where the adjustable zoom parameter for quantization changes based on inter-sampling times and is also used for the threshold of self-triggered sampling. In both strategies, we employ a trajectory-based approach for stability analysis, where contraction theory plays a key role.Comment: 26 pages, 10 figure

Genetic-Algorithm-Assisted Sliding-Mode Control for Networked State-Saturated Systems over Hidden Markov Fading Channels

National Natural Science Foundation of China under Grants 61903143, 61933007, 61873058, 61873148, 61673174 and 61773162; Research Fund for the Taishan Scholar Project of Shandong Province of China; Shanghai Sailing Program of China under Grant 19YF1412100; 111 Project of China under Grant B17017; Royal Society of the U.K.; Alexander von Humboldt Foundation of Germany

Stabilization and Optimal Control for Discrete-time Markov Jump Linear System with Multiplicative Noises and Input Delays: A Complete Solution

Engineering and Physical Sciences Research Council (EPSRC); Royal Society of the UK; National Postdoctoral Program for Innovative Talents in China (Grant Number: BX20180202); Alexander von Humboldt Foundation of Germany; Natural Science Foundation of Shandong Province (Grant Number: ZR2021MF069)