03837nam a22004695i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001700167072001700184072002300201072001600224100007600240245012000316250001800436264007200454300006400526336002600590337002600616338003600642347002400678505092900702520125601631650002502887650001402912650002402926650003202950650003202982650003103014650003203045700007603077710003403153773002603187776003603213776003603249776003603285856004603321978-981-97-1541-1DE-He21320251030112616.0cr nn 008mamaa240705s2024    si |    s    |||| 0|eng d  a97898197154117 a10.1007/978-981-97-1541-12doi 4aTJ212-225 7aTJFM2bicssc 7aGPFC2bicssc 7aTEC0070002bisacsh 7aTJFM2thema1 aRong, Hai-Jun.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aSequential Intelligent Dynamic System Modeling and Controlh[electronic resource] /cby Hai-Jun Rong, Zhao-Xu Yang.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXI, 259 p. 69 illus., 12 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 a1 Fuzzy Inference Systems -- 2 Neural Networks -- 3 Optimization Algorithms -- 4 Modeling and Control of Nonlinear Dynamic Systems -- 5 Online Sequential Fuzzy Extreme Learning Machine -- 6 Sequential Adaptive Fuzzy Inference System -- 7 Evolving Fuzzy Systems based on Data Clouds -- 8 Stability of A Class of Evolving Fuzzy Systems -- 9 Adaptive Self-Learning Fuzzy Autopilot Design for Uncertain Bank-to-Turn Missiles -- 10 Self-Evolving Fuzzy Model-based Controller for Hypersonic Vehicle -- 11 Self-Evolving Data Cloud-based PID-like Controller for Nonlinear Uncertain Systems -- 12 Adaptive Nonparametric Evolving Fuzzy Controller for Nonlinear Uncertain Systems with Dead Zone -- 13 Adaptive Backstepping Neural Controller for Magnetic Bearing System -- 14 Simplified Adaptive Backstepping Neural Controller for Magnetic Bearing System -- 15 Robust Kernel-based Model Reference Adaptive Control for Unstable Aircraft.  aThe book offers novel research results of sequential intelligent dynamic system modeling and control in a unified framework from theory proposals to real applications. It covers an in-depth study of various learning algorithms for the permanent adaptation of intelligent model parameters as well as of structural parts of the model. The comprehensive researches on sequential fuzzy and neural controller design schemes for some complex real applications are included. This is particularly suited for readers who are interested to learn practical solutions for controlling nonlinear systems that are uncertain and varied at any time. In addition, the organization of the book from addressing fundamental concepts, and presenting novel intelligent models to solving real applications is one of the major features of the book, which makes it a valuable resource for both beginners and researchers wanting to further their understanding and study about realtime online intelligent modeling and control of nonlinear dynamic systems. The book can benefit researchers, engineers, and graduate students in the fields of control engineering, artificial intelligence, computational intelligence, intelligent control, nonlinear system modeling, and control, etc. 0aControl engineering. 0aDynamics. 0aNonlinear theories. 0aComputational intelligence.14aControl and Systems Theory.24aApplied Dynamical Systems.24aComputational Intelligence.1 aYang, Zhao-Xu.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981971540408iPrinted edition:z978981971542808iPrinted edition:z978981971543540uhttps://doi.org/10.1007/978-981-97-1541-1