Distributed H∞ fuzzy filtering for nonlinear systems interconnected over graphs

Abstract

This article investigates the distributed fuzzy H ∞ filtering problem for a class of Takagi-Sugeno (T-S) fuzzy model-based nonlinear systems interconnected over an undirected graph. The system we consider consists of numbers of heterogeneous nonlinear sub-units interconnected over an undirected graph by sensing, computing, and communicating with each other. First, the system is represented by an undirected graph, a T-S fuzzy model-based state-space equation of each subsystem and an interconnection condition. Based on this model, the concepts of the well-posedness, stability, and contractiveness for the class of systems are introduced, and the distributed fuzzy filtering problem is established. By applying membership-dependent multi-Lyapunov functions, a sufficient condition on the well-posedness, stability, and contractiveness of the open-loop plant is then derived in terms of linear matrix inequalities (LMIs). And then, a distributed fuzzy filter inheriting the interconnected structure of the plant is designed such that the filtering error system is contractive, and a sufficient condition is correspondingly given to obtain the desired fuzzy filter parameters by solving a set of LMIs. Finally, a numerical simulation is exploited to show the validity of the proposed design method.

Fuzzy fractional factors in fuzzy graphs-II

“…Ullah et al [5] gave the theoretical analysis on complex q-rung orthopair fuzzy competition graphs. Xue et al [6] introduced distributed infinity fuzzy filtering algorithm. Josy et al [7] researched the neighborhood connectivity index in fuzzy graph setting.…”

Design of asynchronous switched Takagi–Sugeno model‐based H∞ filters with nonlinear consequent parts for switched nonlinear systems

“…Based on a nonquadratic Lyapunov–Krasovskii functional, sufficient conditions ensuring the convergence of the robust $$$ {H}_{\infty } $$$ filter with measurable premise variables have been formulated in terms of LMIs. Moreover, the design of a distributed fuzzy $$$ {H}_{\infty } $$$ filter for a class of nonlinear systems interconnected over an undirected graph has been investigated in Reference 29. T‐S fuzzy model of each subsystem was developed.…”

Minimum‐variance recursive state estimation for complex networks with stochastic switching topologies and random quantization under try‐once‐discard protocol

“…So far, a rich body of state estimation schemes have been presented for dynamical complex networks based on the directly available output measurements 8‐11 . To be more specific, the $$$ {H}_{\infty } $$$ estimation strategies have been developed in References 12 and 13, where the effectiveness of presented algorithms has been shown. Different from the $$$ {H}_{\infty } $$$ performance index, the state estimation issues under minimum mean‐square error sense have been addressed in References 14 and 15.…”