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Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms
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.
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.
Cooperative Control of 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
Advances in Neural Networks – ISNN 2016
This book constitutes the refereed proceedings of the 13th International Symposium on Neural Networks, ISNN 2016, held in St. Petersburg, Russia in July 2016. The 84 revised full papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers cover many topics of neural network-related research including signal and image processing; dynamical behaviors of recurrent neural networks; intelligent control; clustering, classification, modeling, and forecasting; evolutionary computation; and cognition computation and spiking neural networks.
Iterative Learning Control for Flexible Structures
This book presents iterative learning control (ILC) to address practical issues of flexible structures. It is divided into four parts: Part I provides a general introduction to ILC and flexible structures, while Part II proposes various types of ILC for simple flexible structures to address issues such as vibration, input saturation, input dead-zone, input backlash, external disturbances, and trajectory tracking. It also includes simple partial differential equations to deal with the common problems of flexible structures. Part III discusses the design of ILC for flexible micro aerial vehicles and two-link manipulators, and lastly, Part IV offers a summary of the topics covered. Unlike most ...
