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**Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems.**
*(English)*
Zbl 1342.93075

Summary: The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties Randomly Occuring Uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed
in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.

### MSC:

93C42 | Fuzzy control/observation systems |

93E11 | Filtering in stochastic control theory |

93E10 | Estimation and detection in stochastic control theory |

93C10 | Nonlinear systems in control theory |

### Keywords:

Takagi-Sugeno fuzzy models; networked systems; nonlinear systems; randomly occuring uncertainties
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\textit{S. Zhang} et al., Abstr. Appl. Anal. 2015, Article ID 856390, 8 p. (2015; Zbl 1342.93075)

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