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Author: Danilo Comminiello Publisher: Butterworth-Heinemann ISBN: 0128129778 Category : Technology & Engineering Languages : en Pages : 390
Book Description
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.
Author: Danilo Comminiello Publisher: Butterworth-Heinemann ISBN: 0128129778 Category : Technology & Engineering Languages : en Pages : 390
Book Description
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.
Author: Wei He Publisher: Springer ISBN: 9811075395 Category : Technology & Engineering Languages : en Pages : 202
Book Description
This book presents theoretical explorations of several fundamental problems in the dynamics and control of flexible beam systems. By integrating fresh concepts and results to form a systematic approach to control, it establishes a basic theoretical framework. It includes typical control design examples verified using MATLAB simulation, which in turn illustrate the successful practical applications of active vibration control theory for flexible beam systems. The book is primarily intended for researchers and engineers in the control system and mechanical engineering community, offering them a unique resource.
Author: Joaquim Filipe Publisher: Springer Science & Business Media ISBN: 1402056265 Category : Computers Languages : en Pages : 240
Book Description
This book is a collection of the best papers presented at the 2nd International Conference on Informatics in Control, Automation and Robotics (ICINCO). ICINCO brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. The research papers focused on real world applications, covering three main themes: Intelligent Control Systems, Optimization, Robotics and Automation and Signal Processing, Systems Modeling and Control.
Author: Thomas Carraro Publisher: Springer ISBN: 3319233211 Category : Mathematics Languages : en Pages : 424
Book Description
This book offers a comprehensive collection of the most advanced numerical techniques for the efficient and effective solution of simulation and optimization problems governed by systems of time-dependent differential equations. The contributions present various approaches to time domain decomposition, focusing on multiple shooting and parareal algorithms. The range of topics covers theoretical analysis of the methods, as well as their algorithmic formulation and guidelines for practical implementation. Selected examples show that the discussed approaches are mandatory for the solution of challenging practical problems. The practicability and efficiency of the presented methods is illustrated by several case studies from fluid dynamics, data compression, image processing and computational biology, giving rise to possible new research topics. This volume, resulting from the workshop Multiple Shooting and Time Domain Decomposition Methods, held in Heidelberg in May 2013, will be of great interest to applied mathematicians, computer scientists and all scientists using mathematical methods.
Author: Sohrab Rohani Publisher: Butterworth-Heinemann ISBN: 0081012241 Category : Technology & Engineering Languages : en Pages : 630
Book Description
Coulson and Richardson's Chemical Engineering: Volume 3B: Process Control, Fourth Edition, covers reactor design, flow modeling, and gas-liquid and gas-solid reactions and reactors. - Converted from textbooks into fully revised reference material - Content ranges from foundational through to technical - Added emerging applications, numerical methods and computational tools
Author: Andreas Potschka Publisher: Springer Science & Business Media ISBN: 3658044764 Category : Mathematics Languages : en Pages : 220
Book Description
Andreas Potschka discusses a direct multiple shooting method for dynamic optimization problems constrained by nonlinear, possibly time-periodic, parabolic partial differential equations. In contrast to indirect methods, this approach automatically computes adjoint derivatives without requiring the user to formulate adjoint equations, which can be time-consuming and error-prone. The author describes and analyzes in detail a globalized inexact Sequential Quadratic Programming method that exploits the mathematical structures of this approach and problem class for fast numerical performance. The book features applications, including results for a real-world chemical engineering separation problem.
Author: Stanley Steinberg Publisher: CRC Press ISBN: 0429610823 Category : Mathematics Languages : en Pages : 309
Book Description
Fundamentals of Grid Generation is an outstanding text/reference designed to introduce students in applied mathematics, mechanical engineering, and aerospace engineering to structured grid generation. It provides excellent reference material for practitioners in industry, and it presents new concepts to researchers. Readers will learn what boundary-conforming grids are, how to generate them, and how to devise their own methods. The text is written in a clear, intuitive style that doesn't get bogged down in unnecessary abstractions. Topics covered include planar, surface, and 3-D grid generation; numerical techniques; solution adaptivity; the finite volume approach to discretization of hosted equations; concepts from elementary differential geometry; and the transformation of differential operators to general coordinate systems. The book also reviews the literature on algebraic, conformal, orthogonal, hyperbolic, parabolic, elliptic, biharmonic, and variational approaches to grid generation. This unique volume closes with the author's original methods of variational grid generation.
Author: Society for Industrial and Applied Mathematics Publisher: ISBN: Category : Automatic control Languages : en Pages : 1042
Book Description
Contains research articles on the mathematics and applications of control theory and on those parts of optimization theory concerned with the dynamics of deterministic or stochastic systems in continuous or discrete time or otherwise dealing with differential equations, dynamics, infinite-dimensional spaces, or fundamental issues in variational analysis and geometry.
Author: Zhi-Hong Guan Publisher: Springer ISBN: 3030021610 Category : Computers Languages : en Pages : 295
Book Description
This book covers the fundamental principles, new theories and methodologies, and potential applications of hybrid intelligent networks. Chapters focus on hybrid neural networks and networked multi-agent networks, including their communication, control and optimization synthesis. This text also provides a succinct but useful guideline for designing neural network-based hybrid artificial intelligence for brain-inspired computation systems and applications in the Internet of Things. Artificial Intelligence has developed into a deep research field targeting robots with more brain-inspired perception, learning, decision-making abilities, etc. This text devoted to a tutorial on hybrid intelligent networks that have been identified in nature and engineering, especially in the brain, modeled by hybrid dynamical systems and complex networks, and have shown potential application to brain-inspired intelligence. Included in this text are impulsive neural networks, neurodynamics, multiagent networks, hybrid dynamics analysis, collective dynamics, as well as hybrid communication, control and optimization methods. Graduate students who are interested in artificial intelligence and hybrid intelligence, as well as professors and graduate students who are interested in neural networks and multiagent networks will find this textbook a valuable resource. AI engineers and consultants who are working in wireless communications and networking will want to buy this book. Also, professional and academic institutions in universities and Mobile vehicle companies and engineers and managers who concern humans in the loop of IoT will also be interested in this book.
Author: Danilo Comminiello
Author: Danilo Comminiello
Author: Wei He
Author: Joaquim Filipe
Author: Thomas Carraro
Author: Sohrab Rohani
Author: Andreas Potschka
Author: Stanley Steinberg
Author: Society for Industrial and Applied Mathematics
Author: 
Author: Zhi-Hong Guan