LEADER 04257nam 22006975 450 001 9911007454703321 005 20250531130238.0 010 $a981-9658-18-7 024 7 $a10.1007/978-981-96-5818-3 035 $a(CKB)39124530900041 035 $a(DE-He213)978-981-96-5818-3 035 $a(MiAaPQ)EBC32142885 035 $a(Au-PeEL)EBL32142885 035 $a(OCoLC)1528962895 035 $a(EXLCZ)9939124530900041 100 $a20250531d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRobust Filtering and Fault Detection for T-S Fuzzy Systems /$fby Xiao-Lei Wang, Guang-Hong Yang, Yu-Long Wang 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (XI, 148 p. 48 illus., 43 illus. in color.) 225 1 $aIntelligent Technologies and Robotics Series 311 08$a981-9658-17-9 327 $aIntroduction -- Fundamentals of T-S Fuzzy Systems -- Robust Filtering Theory -- Fault Detection Techniques for T-S Fuzzy Systems -- Filtering and Fault Detection Under Asynchronous Conditions -- Event-Triggered Robust Filtering -- Case Studies and Applications -- Future Directions and Research Areas. 330 $aThis book conducts an in-depth research on robust filtering and fault detection for a class of T-S fuzzy systems. On the basis of the existing research on T-S fuzzy theory, robust filtering theory, and fault diagnosis theory, some new and effective technologies are proposed to solve the problems of robust filtering and fault detection for a class T-S fuzzy systems, while overcoming the shortcomings and limitations of the existing solutions. This book introduces new design solutions for a class of T-S fuzzy systems to address the existing problems in the research of robust filtering and fault detection, namely 1) two new filtering methods are explored to obtain better filtering results than the existing approaches; 2) a new event-triggered filtering scheme is proposed for T-S fuzzy systems with bounded disturbances, which realizes that the designed observer gains in the absence of event-triggered mechanisms are also applicable to the case with event-triggered mechanisms; 3) two new methods are constructed to deal with the asynchronous problems of premise variables effectively, which overcome the defects and limitations of the existing ones; and 4) an effective fault detection scheme for handling measurement outliers is constructed, which can avoid the occurrence of false alarms. This book is intended to inspire researchers and engineers, offering deeper insights into robust filtering and fault detection for T-S fuzzy systems, and equipping them with the latest advancements in fuzzy system theory, robust filtering, and fault diagnosis. It also provides valuable theoretical references for engineers tackling practical engineering problems. 410 0$aIntelligent Technologies and Robotics Series 606 $aAutomatic control 606 $aRobotics 606 $aAutomation 606 $aTelecommunication 606 $aSystem theory 606 $aMathematical optimization 606 $aControl, Robotics, Automation 606 $aCommunications Engineering, Networks 606 $aComplex Systems 606 $aOptimization 615 0$aAutomatic control. 615 0$aRobotics. 615 0$aAutomation. 615 0$aTelecommunication. 615 0$aSystem theory. 615 0$aMathematical optimization. 615 14$aControl, Robotics, Automation. 615 24$aCommunications Engineering, Networks. 615 24$aComplex Systems. 615 24$aOptimization. 676 $a629.8 700 $aWang$b Xiao-Lei$4aut$4http://id.loc.gov/vocabulary/relators/aut$01169018 702 $aYang$b Guang-Hong$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aWang$b Yu-Long$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911007454703321 996 $aRobust Filtering and Fault Detection for T-S Fuzzy Systems$94389809 997 $aUNINA