1.

Record Nr.

UNINA9910999684703321

Autore

Hu Jun

Titolo

Variance-Constrained Filtering for Stochastic Complex Systems : Theories and Algorithms / / by Jun Hu, Zidong Wang, Chaoqing Jia

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025

ISBN

981-9626-37-4

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (XV, 310 p. 127 illus., 121 illus. in color.)

Collana

Intelligent Control and Learning Systems, , 2662-5466 ; ; 18

Disciplina

515.39

Soggetti

Dynamics

Nonlinear theories

Automatic control

System theory

Control theory

Dynamical Systems

Applied Dynamical Systems

Control and Systems Theory

Systems Theory, Control

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Introduction -- Recursive Filtering and Boundedness Analysis with ROQ -- Resilient Filtering with Stochastic Uncertainties and Incomplete Measurements -- Event-Triggered Resilient Filtering with Stochastic Uncertainties and SPDs -- Event-triggered Filtering with Missing Measurements -- Fault Estimation Against Randomly Occurring Deception Attacks -- Fault Estimation with Packet Dropouts and ROUs -- Fault Estimation with Randomly Occurring Faults and Sensor Saturations -- State Estimation for Complex Networks with Missing Measurements -- Quantized State Estimation for Complex Networks with Uncertain Inner Coupling -- Event-Based State Estimation for Complex Networks under UOPs -- Event-Based State Estimation for Complex Networks with Fading Observations and UST -- State Estimation for Complex Networks with Uncertain Observations and Coupling Strength -- Conclusions and Future Work.



Sommario/riassunto

This book is concerned with the variance-constrained optimized filtering problems and their potential applications for nonlinear time-varying dynamical systems. The distinguished features of this book are highlighted as follows. (1) A unified framework is provided for handling the variance-constrained filtering problems of nonlinear time-varying dynamical systems with incomplete information. (2) The application potentials of variance-constrained optimized filtering in networked time-varying dynamical systems are outlined. It contains some new concepts, new models and new methodologies with practical significance in control engineering and signal processing. It is a collection of several research results and thereby serves as a useful reference for upper undergraduate, postgraduate and engineers who are interested in studying (i) the variance-constrained filtering, (ii) recent advances affected by incomplete information and (iii) potential applications in practical engineering systems.