Finite-Time Control of Networked Systems Finite-Time Control of Networked Systems
Intelligent Control and Learning Systems

Finite-Time Control of Networked Systems

Xinsong Yang and Others
    • $149.99
    • $149.99

Publisher Description

This book mainly provides recent advances in finite-time and fixed-time control issues for complex networks and neural networks. It is well known that finite-time techniques have more advantages over asymptotical ones. Besides fast convergence rates, finite-time techniques have better robustness and disturbance rejection properties. However, it is challenging to deal with time delay in studying finite-time control. For readers’ easy understanding, the finite-time control issue for systems with and without time delays is separately introduced in this book. Moreover, the issues of finite-time and fixed-time control for differential equations with discontinuous states on the right-hand side are also considered. Many interesting results concerning finite-time and fixed-time synchronization are provided in the form of lemmas, theorems, or corollaries, accompanied by systematic theoretical analysis for the proof of their sufficient conditions, controller design, and new analysis techniques. Each new result is verified by at least one numerical example with detailed data analysis. Therefore, this book is an advantageous tool and is beneficial for interested experts and scholars in the control field.

GENRE
Science & Nature
RELEASED
2025
March 31
LANGUAGE
EN
English
LENGTH
432
Pages
PUBLISHER
Springer Nature Singapore
SELLER
Springer Nature B.V.
SIZE
62.4
MB
Variance-Constrained Filtering for Stochastic Complex Systems Variance-Constrained Filtering for Stochastic Complex Systems
2025
Analysis and Design of Delayed Neural Networks Analysis and Design of Delayed Neural Networks
2025
Fault Diagnosis and Fault-Tolerant Control of Nonlinear Systems with Higher System Input Powers Fault Diagnosis and Fault-Tolerant Control of Nonlinear Systems with Higher System Input Powers
2025
Dynamic Neural Networks for Motion Control of Redundant Manipulators Dynamic Neural Networks for Motion Control of Redundant Manipulators
2025
Robust Iterative Learning Control of Industrial Batch Systems Robust Iterative Learning Control of Industrial Batch Systems
2025
Discrete-Time Adaptive Iterative Learning Control Discrete-Time Adaptive Iterative Learning Control
2022