Neural Network Based State Estimation Of Nonlinear Systems
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Neural Network Based State Estimation Of Nonlinear Systems
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Author : Heidar A. Talebi
language : en
Publisher: Springer
Release Date : 2010-05-06
Neural Network Based State Estimation Of Nonlinear Systems written by Heidar A. Talebi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-06 with Technology & Engineering categories.
"Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
Neural Network Based State Estimation Of Nonlinear Systems
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Author : Heidar A. Talebi
language : en
Publisher: Springer
Release Date : 2009-12-04
Neural Network Based State Estimation Of Nonlinear Systems written by Heidar A. Talebi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-04 with Technology & Engineering categories.
"Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
Neural Network Based State Estimation Of Nonlinear Systems
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Author : Heidar A. Talebi
language : en
Publisher: Springer
Release Date : 2009-12-14
Neural Network Based State Estimation Of Nonlinear Systems written by Heidar A. Talebi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-14 with Technology & Engineering categories.
"Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
Neural Network Based Adaptive Control Of Uncertain Nonlinear Systems
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Author : Kasra Esfandiari
language : en
Publisher: Springer Nature
Release Date : 2021-06-18
Neural Network Based Adaptive Control Of Uncertain Nonlinear Systems written by Kasra Esfandiari and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-18 with Technology & Engineering categories.
The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.
Artificial Higher Order Neural Networks For Modeling And Simulation
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Author : Zhang, Ming
language : en
Publisher: IGI Global
Release Date : 2012-10-31
Artificial Higher Order Neural Networks For Modeling And Simulation written by Zhang, Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-31 with Computers categories.
"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Network And Communication Technology Innovations For Web And It Advancement
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Author : Alkhatib, Ghazi I.
language : en
Publisher: IGI Global
Release Date : 2012-10-31
Network And Communication Technology Innovations For Web And It Advancement written by Alkhatib, Ghazi I. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-31 with Computers categories.
With the steady stream of new web based information technologies being introduced to organizations, the need for network and communication technologies to provide an easy integration of knowledge and information sharing is essential. Network and Communication Technology Innovations for Web and IT Advancement presents studies on trends, developments, and methods on information technology advancements through network and communication technology. This collection brings together integrated approaches for communication technology and usage for web and IT advancements.
Fault Diagnosis Of Nonlinear Systems Using A Hybrid Approach
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Author : Ehsan Sobhani-Tehrani
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-22
Fault Diagnosis Of Nonlinear Systems Using A Hybrid Approach written by Ehsan Sobhani-Tehrani and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-22 with Technology & Engineering categories.
Theincreasingcomplexityofspacevehiclessuchassatellites,andthecostreduction measures that have affected satellite operators are increasingly driving the need for more autonomy in satellite diagnostics and control systems. Current methods for detecting and correcting anomalies onboard the spacecraft as well as on the ground are primarily manual and labor intensive, and therefore, tend to be slow. Operators inspect telemetry data to determine the current satellite health. They use various statisticaltechniques andmodels,buttheanalysisandevaluation ofthelargevolume of data still require extensive human intervention and expertise that is prone to error. Furthermore, for spacecraft and most of these satellites, there can be potentially unduly long delays in round-trip communications between the ground station and the satellite. In this context, it is desirable to have onboard fault-diagnosis system that is capable of detecting, isolating, identifying or classifying faults in the system withouttheinvolvementandinterventionofoperators.Towardthisend,theprinciple goal here is to improve the ef?ciency, accuracy, and reliability of the trend analysis and diagnostics techniques through utilization of intelligent-based and hybrid-based methodologies.
Discrete Time Neural Observers
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Author : Alma Y Alanis
language : en
Publisher: Academic Press
Release Date : 2017-02-06
Discrete Time Neural Observers written by Alma Y Alanis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-06 with Computers categories.
Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their application in meaningful areas, such as electric three phase induction motors and anaerobic process, which show the applicability of such designs. The proposed schemes can be employed for different applications beyond those presented. The book presents solutions for the state estimation problem of unknown nonlinear systems based on two schemes. For the first one, a full state estimation problem is considered; the second one considers the reduced order case with, and without, the presence of unknown delays. Both schemes are developed in discrete-time using recurrent high order neural networks in order to design the neural observers, and the online training of the respective neural networks is performed by Kalman Filtering. - Presents online learning for Recurrent High Order Neural Networks (RHONN) using the Extended Kalman Filter (EKF) algorithm - Contains full and reduced order neural observers for discrete-time unknown nonlinear systems, with and without delays - Includes rigorous analyses of the proposed schemes, including the nonlinear system, the respective observer, and the Kalman filter learning - Covers real-time implementation and simulation results for all the proposed schemes to meaningful applications
Analysis And Synthesis Of Fault Tolerant Control Systems
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Author : Magdi S. Mahmoud
language : en
Publisher: John Wiley & Sons
Release Date : 2013-10-28
Analysis And Synthesis Of Fault Tolerant Control Systems written by Magdi S. Mahmoud and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-28 with Technology & Engineering categories.
In recent years, control systems have become more sophisticated in order to meet increased performance and safety requirements for modern technological systems. Engineers are becoming more aware that conventional feedback control design for a complex system may result in unsatisfactory performance, or even instability, in the event of malfunctions in actuators, sensors or other system components. In order to circumvent such weaknesses, new approaches to control system design have emerged which can tolerate component malfunctions while maintaining acceptable stability and performance. These types of control systems are often known as fault-tolerant control systems (FTCS). More precisely, FTCS are control systems which possess the ability to accommodate component failure automatically. Analysis and Synthesis of Fault-Tolerant Control Systems comprehensively covers the analysis and synthesis methods of fault tolerant control systems. It unifies the methods for developing controllers and filters for a wide class of dynamical systems and reports on the recent technical advances in design methodologies. MATLAB® is used throughout the book, to demonstrate methods of analysis and design. Key features: • Provides advanced theoretical methods and typical practical applications • Provides access to a spectrum of control design methods applied to industrial systems • Includes case studies and illustrative examples • Contains end-of-chapter problems Analysis and Synthesis of Fault-Tolerant Control Systems is a comprehensive reference for researchers and practitioners working in this area, and is also a valuable source of information for graduates and senior undergraduates in control, mechanical, aerospace, electrical and mechatronics engineering departments.
Variance Constrained Filtering For Stochastic Complex Systems
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Author : Jun Hu
language : en
Publisher: Springer Nature
Release Date : 2025-04-29
Variance Constrained Filtering For Stochastic Complex Systems written by Jun Hu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Mathematics categories.
This book is concerned with the variance-constrained optimized filtering problems and their potential applications for nonlinear time-varying dynamical systems. The distinguished features of this book are highlighted as follows. (1) A unified framework is provided for handling the variance-constrained filtering problems of nonlinear time-varying dynamical systems with incomplete information. (2) The application potentials of variance-constrained optimized filtering in networked time-varying dynamical systems are outlined. It contains some new concepts, new models and new methodologies with practical significance in control engineering and signal processing. It is a collection of several research results and thereby serves as a useful reference for upper undergraduate, postgraduate and engineers who are interested in studying (i) the variance-constrained filtering, (ii) recent advances affected by incomplete information and (iii) potential applications in practical engineering systems.