Optimal filter for MJL system with delayed modes and observations

Optimal sequential fusion estimation for sampled‐data systems with random delays and multiplicative noise

“…Obviously, (47) can be seen as the discrete‐time filtering algebraic Riccati equation with constant parameters. Using (55) and by following the similar line as in Theorem 2 of Reference 35, it is obtained that there exists a unique stabilizing solution to (47). Thus, it can be deduced that CAREs (47) and (48) have a unique set of stabilizing solutions, denoted as $$$ {\tilde{Y}}_{gl}(i) $$$ $$$ \left(g=d,d-1,\dots, 0;i=0,\dots, d\right) $$$.…”

“…Generally, the fusion strategies can be categorized into the centralized fusion (CF) and the distributed fusion (DF), according to the different treatments of measurement data. The CF method 35,36 has provided an optimal estimation using the augmented measurement equations, which, however, induces large communication burdens and increases the computational cost.…”

Optimal H2 filtering for measurement‐delay systems with multiplicative noise and sampled data

“…23 Lemma 1. Under Assumption 1, if the additive noises v(t) and v d (s) are ignored in (13) and (14), then the following stochastic system with jumps…”

“…In order to reduce the computational burden, the reorganized observation technique has been proposed, which just needs to solve a set of Riccati equations with the same dimension as the original system. Moreover, the filtering problem for discrete-time linear systems with Markov jumps and packet losses was considered, 13 and the estimation problem for discrete-time linear systems influenced by periodic coefficients and multiplicative noise was investigated. 14 It needs to point out that the systems mentioned above are all in continuous time domain or discrete time domain, respectively.…”

Upper bound filter under interval constraints and multiplicative noises

“…With the rapid development of information and communication technologies, the study of filtering problem for dynamic systems has gradually received much attention due to its wide applications in networked control systems [1–6], smart grids [7, 8], cyber‐physical systems [9, 10], target tracking [11, 12] and so on. The filter design is actually pursuing an optimal function to utilise the obtained available measurement information to estimate the interested state at the current epoch.…”