Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models, Jan Treur
Автор: S.S. Ge; C.C. Hang; T.H. Lee; Tao Zhang Название: Stable Adaptive Neural Network Control ISBN: 1441949321 ISBN-13(EAN): 9781441949325 Издательство: Springer Рейтинг: Цена: 28732.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen a rapid development of neural network control tech- niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec- tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.
Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic architecture of control science and engineering.
Introduces nonlinear systems' basic knowledge, analysis and control methods, along with applications in various fields
Offers instructive examples and simulations, including source codes
Provides the basic architecture of control science and engineering
Автор: George A. Rovithakis; Manolis A. Christodoulou Название: Adaptive Control with Recurrent High-order Neural Networks ISBN: 1447112016 ISBN-13(EAN): 9781447112013 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ...
Описание: This book addresses the topic of fractional-order modeling of nuclear reactors. Approaching neutron transport in the reactor core as anomalous diffusion, specifically subdiffusion, it starts with the development of fractional-order neutron telegraph equations. Using a systematic approach, the book then examines the development and analysis of various fractional-order models representing nuclear reactor dynamics, ultimately leading to the fractional-order linear and nonlinear control-oriented models. The book utilizes the mathematical tool of fractional calculus, the calculus of derivatives and integrals with arbitrary non-integer orders (real or complex), which has recently been found to provide a more compact and realistic representation to the dynamics of diverse physical systems.Including extensive simulation results and discussing important issues related to the fractional-order modeling of nuclear reactors, the book offers a valuable resource for students and researchers working in the areas of fractional-order modeling and control and nuclear reactor modeling.
Описание: Artificial Higher Order Neural Networks for Modeling and Simulation introduces artificial Higher Order Neural Networks (HONNs) to professionals working in the fields of modeling and simulation, and explains that HONN is an open-box artificial neural network tool as compared to traditional artificial neural networks. Including details of the most popular HONN models, this book provides an opportunity for practitioners in the field of modeling and simulations to understand and know how to use HONNS in their area of expertise.
Описание: Chapter 1. Fractional Calculus.- Chapter 2. Introduction to Nuclear Reactor Modeling.- Chapter 3. Development and Analysis of Fractional-order Neutron Telegraph Equation.- Chapter 4. Development and Analysis of Fractional-order Point Reactor Kinetics Model.- Chapter 5. Further Developments using Fractional-order Point Reactor Kinetics Model.- Chapter 6. Development and Analysis of Fractional-order Point Reactor Kinetics Models with Reactivity Feedback.- Chapter 7. Development and Analysis of Fractional-order Two-Group Models.
Описание: This volume contains results gained from the EU-funded 6th Framework project ADIGMA (Adaptive Higher-order Variational Methods for Aerodynamic Applications in Industry).
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