SinceinitiatedbyLot?A. Zadehin1965,fuzzysettheoryhastriggeredacons- erably large body of areas to blossom. A fuzzy system is, in a very broad sense, anyfuzzylogic-basedsystemwherefuzzylogiccanbeusedeither asthebasisfor the representation of di?erent forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse ?elds of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem's behavior and build useful mathematical models. Di?erent types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems. There has been an - creasing amount of work on analysis and synthesis of fuzzy systems based on T-S fuzzy models. Since 2000, T-S fuzzy model approach has been extended to tackleanalysisandcontrolproblemsofnonlinear systemswith time delay. So far extensive results have been presented for investigating T-S fuzzy systems with time delay, many of which adopt an easy and popular scheme, say, linear matrix inequality (LMI) based method. However, there lacks of a monograph in this direction to provide the state-of-the-art of coverage of this new growing area.

Up-to-date developments in the analysis and control area for nonlinear time-delay systems using T-S fuzzy model approach Comprehensive monograph on T-S fuzzy systems with time delay

Autorentext

Ziye Zhang received the B.Sc. degree in mathematics from Yantai University, Yantai, China, in 2002, the M.Sc. degree in mathematics from Lanzhou University, Lanzhou, China, in 2005, and the Ph.D. degree from the Institute of Complexity Science, Qingdao University, Qingdao, China, in 2015. She is currently Associate Professor with the College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China. Her current research interests include systems analysis, fuzzy control, filter design, and neural networks. Zhen Wang is currently Professor at College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China. He received Ph.D. degree from School of Automation, Nanjing University of Science and Technology, China, in 2013. Jian Chen is Associate Professor at School of information and Control Engineering, Qingdao University of Technology, Qingdao, China. She received her Ph.D. degree from Institute of Complexity Science, Qingdao University, in 2017. Her research interest includes systems analysis and control. Chong Lin is Professor at Institute of Complexity Science, Qingdao University, China. He received Ph.D. from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, in 1999.

Inhalt
Stability Analysis of T-S Fuzzy Systems.- Extension to Fuzzy Large-Scale Systems.- Stabilization Methods for T-S Fuzzy Systems.- Variable Structure Control for T-S Fuzzy Systems.- Observer-Based Fuzzy Control: Delay-Independent Method.- Observer-Based Fuzzy Control: Delay-Dependent Method.- Output Tracking Control for T-S Fuzzy Systems.- Fuzzy Filter Design for T-S Fuzzy Systems.- Descriptor Method for T-S Fuzzy Control Systems.