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This paper addresses the fault detection filtering issue for a class of discrete system with network-induced nonlinear characteristics. The communication limitations, including measurements quantization, signal transmission delay, and data packet dropout, frequent in many practical networked control systems (NCSs) are considered. By transforming the residual system into an input-output form consisting two interconnected subsystems via a two-term approximation to the state delay variables, sufficient conditions are established. Under these conditions, the residual system is stochastically stable with a prescribed H∞ level with the help of the scaled small gain (SSG) theorem developed for stochastic systems. Furthermore, the fault detection filter design approach is presented. A numerical example is also provided to demonstrate the effectiveness of the proposed method.Index Terms-Data packet dropout, fault detection, quantization, signal transmission delay. 1551-3203

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This study addresses the H ∞ filtering design issue for a class of time-delay Markov jump system with nonlinear characteristics. A stochastic system with sensor saturation and intermittent measurements is considered in the authors study. Random noise depending on state and external-disturbance are also taken into account. A decomposition approach and a bernoulli process are utilised to model the characteristic of sensor saturation and missing measurements, respectively. By transforming the filtering error system into an input-output form, sufficient conditions for the stochastic stability of the system with a prescribed H ∞ level are presented with the help of Scaled Small Gain theorem developed for stochastic systems. Based on the proposed conditions, the rubost filter design approach is proposed. A numerical example is finally provided to demonstrate effectiveness of the proposed approahc. NomenclatureThroughout this paper, R n represents the n-dimensional Euclidean space, R n×m is the set of all n × m real matrices, the superscripts '−1' and 'T', respectively, stand for the matrix inverse and matrix transpose. Sym{A} is the shorten notation for A + A T , and the notation P > 0 (respectively, P ≥ 0), for P ∈ R n×n means that P is real symmetric and positive definite (respectively, semidefinite). The symmetric elements of the symmetric matrix is represented by an asterisk ( * ), and the block-diagonal matrices are denoted by diag{. . .}. G 1 • G 2 means the series connection of mapping G 1 and G 2 . E{·} denotes the expectation operator with respect to probability measure, and for vector x(k), x E2 = E{ ∞ n=0 x(n) 2 } 1 2 .

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This paper addresses theℋ∞filtering problem for time-delayed Markov jump systems (MJSs) with intermittent measurements. Within network environment, missing measurements are taken into account, since the communication channel is supposed to be imperfect. A Bernoulli process is utilized to describe the phenomenon of the missing measurements. The original system is transformed into an input-output form consisting of two interconnected subsystems. Based on scaled small gain (SSG) theorem and proposed Lyapunov-Krasovskii functional (LKF), the scaled small gains of the subsystems are analyzed, respectively. New conditions for the existence of theℋ∞filters are established, and the correspondingℋ∞filter design scheme is proposed. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed approach.

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