Shun-Yan Ren – författare

Cooperative Control for Nonlinear Multiagent Systems: Passivity-Based and Non-Passivity-Based Approaches focuses on the cooperative control of nonlinear multiagent systems containing passivity-based or non-passivity-based consensus, lag consensus, and formation control of multiagent systems. The book provides professional and convenient guidance for those who want to know basic knowledge, advancements, and processes for designing and analyzing cooperative control for nonlinear multiagent systems.Currently, there are a lack of reference titles that systematically introduce students, researchers, and technologists to the backgrounds, developments, and designs protocols for cooperative control (contains passivity-based or not passivity-based consensus, lag consensus, formation control) of nonlinear multiagent systems.Constructs the frameworks of passivity analysis, consensus control, lag consensus control, and formation control for multiagent systemsHelps readers learn novel control methodsIncludes systematic introductions and detailed implementations on how control protocols solve problems in nonlinear multiagent systems

Cooperative Control for Nonlinear Multiagent Systems: Passivity-Based and Non-Passivity-Based Approaches focuses on the cooperative control of nonlinear multiagent systems containing passivity-based or non-passivity-based consensus, lag consensus, and formation control of multiagent systems. The book provides professional and convenient guidance for those who want to know basic knowledge, advancements, and processes for designing and analyzing cooperative control for nonlinear multiagent systems.Currently, there are a lack of reference titles that systematically introduce students, researchers, and technologists to the backgrounds, developments, and designs protocols for cooperative control (contains passivity-based or not passivity-based consensus, lag consensus, formation control) of nonlinear multiagent systems.- Constructs the frameworks of passivity analysis, consensus control, lag consensus control, and formation control for multiagent systems- Helps readers learn novel control methods- Includes systematic introductions and detailed implementations on how control protocols solve problems in nonlinear multiagent systems

Highly comprehensive resource for studying neural networks, complex networks, synchronization, passivity, and associated applications Dynamical Behaviors of Multiweighted Complex Network Systems discusses the dynamical behaviors of various multiweighted complex dynamical networks, with detailed insight on synchronization for directed and undirected complex networks (CNs) with multiple state or delayed state couplings subject to recoverable attacks, along with passivity and synchronization for coupled neural networks with multi-weights (CNNMWs) by virtue of devised proportional-integral-derivative (PID) controllers. The book also investigates finite-time synchronization (FTS) and H-infinity synchronization for two types of coupled neural networks (CNNs) and focuses on finite-time passivity (FTP) and finite-time synchronization (FTS) for complex dynamical networks with multiple state/derivative couplings based on the proportional-derivative (PD) control method. Final chapters consider finite-time output synchronization and H-infinity output synchronization problems, and multiple weighted coupled reaction-diffusion neural networks (CRDNNs) with and without coupling delays. Other topics covered in Dynamical Behaviors of Multiweighted Complex Network Systems include: Criteria of FTP for complex dynamical networks with multiple state couplings (CDNMSCs), formulated by utilizing the PD controllerFinite-time passivity (FTP) concepts for the spatially and temporally systems with different dimensions of output and inputFTS and finite time H-infinity synchronization problems for CDNs with multiple state/derivative couplings by utilizing state feedback control approach and selecting suitable parameter adjustment schemesAdaptive output synchronization and output synchronization of CDNs with multiple output or output derivative couplings, and other adaptive control schemesEnabling readers to understand foundational concepts and grasp the latest research, Dynamical Behaviors of Multiweighted Complex Network Systems is essential for all who study neural networks, complex networks, synchronization, passivity, and their applications.

Highly comprehensive resource for studying neural networks, complex networks, synchronization, passivity, and associated applications

Dynamical Behaviors of Multiweighted Complex Network Systems discusses the dynamical behaviors of various multiweighted complex dynamical networks, with detailed insight on synchronization for directed and undirected complex networks (CNs) with multiple state or delayed state couplings subject to recoverable attacks, along with passivity and synchronization for coupled neural networks with multi-weights (CNNMWs) by virtue of devised proportional-integral-derivative (PID) controllers.

The book also investigates finite-time synchronization (FTS) and H-infinity synchronization for two types of coupled neural networks (CNNs) and focuses on finite-time passivity (FTP) and finite-time synchronization (FTS) for complex dynamical networks with multiple state/derivative couplings based on the proportional-derivative (PD) control method. Final chapters consider finite-time output synchronization and H-infinity output synchronization problems, and multiple weighted coupled reaction-diffusion neural networks (CRDNNs) with and without coupling delays.

Other topics covered in Dynamical Behaviors of Multiweighted Complex Network Systems include:

Criteria of FTP for complex dynamical networks with multiple state couplings (CDNMSCs), formulated by utilizing the PD controller Finite-time passivity (FTP) concepts for the spatially and temporally systems with different dimensions of output and input FTS and finite time H-infinity synchronization problems for CDNs with multiple state/derivative couplings by utilizing state feedback control approach and selecting suitable parameter adjustment schemes Adaptive output synchronization and output synchronization of CDNs with multiple output or output derivative couplings, and other adaptive control schemes

Enabling readers to understand foundational concepts and grasp the latest research, Dynamical Behaviors of Multiweighted Complex Network Systems is essential for all who study neural networks, complex networks, synchronization, passivity, and their applications.

Highly comprehensive resource for studying neural networks, complex networks, synchronization, passivity, and associated applications

Dynamical Behaviors of Multiweighted Complex Network Systems discusses the dynamical behaviors of various multiweighted complex dynamical networks, with detailed insight on synchronization for directed and undirected complex networks (CNs) with multiple state or delayed state couplings subject to recoverable attacks, along with passivity and synchronization for coupled neural networks with multi-weights (CNNMWs) by virtue of devised proportional-integral-derivative (PID) controllers.

The book also investigates finite-time synchronization (FTS) and H-infinity synchronization for two types of coupled neural networks (CNNs) and focuses on finite-time passivity (FTP) and finite-time synchronization (FTS) for complex dynamical networks with multiple state/derivative couplings based on the proportional-derivative (PD) control method. Final chapters consider finite-time output synchronization and H-infinity output synchronization problems, and multiple weighted coupled reaction-diffusion neural networks (CRDNNs) with and without coupling delays.

Other topics covered in Dynamical Behaviors of Multiweighted Complex Network Systems include:

Criteria of FTP for complex dynamical networks with multiple state couplings (CDNMSCs), formulated by utilizing the PD controller Finite-time passivity (FTP) concepts for the spatially and temporally systems with different dimensions of output and input FTS and finite time H-infinity synchronization problems for CDNs with multiple state/derivative couplings by utilizing state feedback control approach and selecting suitable parameter adjustment schemes Adaptive output synchronization and output synchronization of CDNs with multiple output or output derivative couplings, and other adaptive control schemes

Enabling readers to understand foundational concepts and grasp the latest research, Dynamical Behaviors of Multiweighted Complex Network Systems is essential for all who study neural networks, complex networks, synchronization, passivity, and their applications.

This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.

This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.

This book introduces recent results on output synchronization of complex dynamical networks with single and multiple weights. It discusses novel research ideas and a number of definitions in complex dynamical networks, such as H-Infinity output synchronization, adaptive coupling weights, multiple weights, the relationship between output strict passivity and output synchronization. Furthermore, it methodically edits the research results previously published in various flagship journals and presents them in a unified form. The book is of interest to university researchers and graduate students in engineering and mathematics who wish to study output synchronization of complex dynamical networks.

This book introduces recent results on output synchronization of complex dynamical networks with single and multiple weights. It discusses novel research ideas and a number of definitions in complex dynamical networks, such as H-Infinity output synchronization, adaptive coupling weights, multiple weights, the relationship between output strict passivity and output synchronization. Furthermore, it methodically edits the research results previously published in various flagship journals and presents them in a unified form. The book is of interest to university researchers and graduate students in engineering and mathematics who wish to study output synchronization of complex dynamical networks.

This book introduces recent results on output synchronization of complex dynamical networks with single and multiple weights. It discusses novel research ideas and a number of definitions in complex dynamical networks, such as H-Infinity output synchronization, adaptive coupling weights, multiple weights, the relationship between output strict passivity and output synchronization. Furthermore, it methodically edits the research results previously published in various flagship journals and presents them in a unified form. The book is of interest to university researchers and graduate students in engineering and mathematics who wish to study output synchronization of complex dynamical networks.

This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.

This book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.

This book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.