04258nam a22005655i 4500 978-981-97-1541-1 DE-He213 20251030112616.0 cr nn 008mamaa 240705s2024 si | s |||| 0|eng d 9789819715411 978-981-97-1541-1 10.1007/978-981-97-1541-1 doi TJ212-225 TJFM bicssc GPFC bicssc TEC007000 bisacsh TJFM thema Rong, Hai-Jun. author. aut http://id.loc.gov/vocabulary/relators/aut 80118 Sequential Intelligent Dynamic System Modeling and Control [electronic resource] / by Hai-Jun Rong, Zhao-Xu Yang. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XI, 259 p. 69 illus., 12 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 1 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. The 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. Control engineering. Dynamics. 65524 Nonlinear theories. 65525 Computational intelligence. 64052 Control and Systems Theory. 65868 Applied Dynamical Systems. 65530 Computational Intelligence. 64052 Yang, Zhao-Xu. author. aut http://id.loc.gov/vocabulary/relators/aut 80119 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819715404 Printed edition: 9789819715428 Printed edition: 9789819715435 https://doi.org/10.1007/978-981-97-1541-1 ZDB-2-INR ZDB-2-SXIT 61385 61385