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yang x finite time control networked systems 2025

Type:: E-books
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Uploaded On:: April 5, 2025, 7 a.m.
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Textbook in PDF format 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. Introduction Preliminaries Finite-Time Control of Continuous Systems Without Delay Finite-Time Control of Continuous Systems with Delay Fixed-Time Control of Continuous Systems Finite-Time and Fixed-Time Control of Differential Equations with Discontinuous State Neural Networks Neural Networks with Mixed Delays and Mismatched Parameters Neural Networks with Proportional Delays and Markovian Switching Coupled Neural Networks Coupled Neural Networks with Mixed Delays Nonidentical Perturbations Coupled Neural Networks with Mixed Delays and Markovian Switching Coupled Neural Networks with Nonidentical Perturbations Competitive Neural Networks Complex-Valued Neural Networks Inertial Neural Networks BAM Fuzzy Neural Networks Complex Networks

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yang x finite time control networked systems 2025

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