Titlebook: Control and Filtering of Fuzzy Systems Under Communication Channels; Xiao-Heng Chang,Jun Xiong,Bo Wu Book 2023 The Editor(s) (if applicabl

皺紋

書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels影響因子(影響力)




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels影響因子(影響力)學科排名




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels網(wǎng)絡(luò)公開度




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels網(wǎng)絡(luò)公開度學科排名




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels被引頻次




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels被引頻次學科排名




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels年度引用




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels年度引用學科排名




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels讀者反饋




書目名稱Control and Filtering of Fuzzy Systems Under Communication Channels讀者反饋學科排名

Complement

吹牛者

關(guān)心

小故事

Book 2023zy models. By fully considering different network-induced phenomena, such as signal quantizations, time-delays, data packet dropouts, communication protocols, cyber attacks, and so on, some significant strategies are provided for various performance analysis and different controller/filter synthesis

corporate

Introduction and Preview,agi–Sugeno (T–S) fuzzy model and some interesting results have been published in the open literature. In this monograph, some novel advances on the study of nonlinear networked systems based on T–S fuzzy model will be given. Firstly, the various robust control strategies for nonlinear networked syst

corporate

Fuzzy Robust , Control with Dynamic Quantization, transmission to reduce the communication burden. Firstly, the robust . control is addressed for uncertain discrete-time T–S fuzzy systems with the control input quantization via a two-step design approach and the fuzzy Lyapunov functional method. Secondly, a new two-step strategy is proposed to onl

凈禮

Veneer

https://doi.org/10.1007/978-3-658-17033-2nd measurement output quantization on continuous-time T–S fuzzy systems, the resilient . control problem is solved based on two descriptor representation approaches, and a novel adjusting rule is given for dynamic quantizers’ parameters. Finally, some examples are provided to show the feasibility an

Pert敏捷

Vorausschauender Motion-Cueing-Algorithmus, in which the measurement output and the performance output signals of the system are quantized by two dynamic quantizers. And the conditions are given to ensure the filtering error system is asymptotically stable with the prescribed . performance index. Finally, some examples are given to demonstra