Advances In State And Parameter Estimation
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Advances In State And Parameter Estimation
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Author : Jitendra R. Raol
language : en
Publisher: CRC Press
Release Date : 2025-05-27
Advances In State And Parameter Estimation written by Jitendra R. Raol and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-27 with Technology & Engineering categories.
This book deals with the basics of parameter estimation and state estimation as the fundamental building blocks of mathematical modelling activity in the broader field of control theory. All the methods are validated using MATLAB®-based implementations with realistically simulated data for general dynamic systems, as well as for aircraft parameter estimation. This book includes several illustrative examples and chapter-end exercises. Features: Provides comprehensive coverage of all issues related to parameter and state estimation. Discusses advanced topics related to Kalman filter, stability analysis, image centroid tracking and neural networks for parameter estimation. Explores convergence and stability results for the discussed methods. Reviews the estimation of parameters in linear/nonlinear models, and distributed fitting. Includes MATLAB®-based illustrative examples, and exercises. This book is aimed at researchers and graduate students in systems and control, signal processing, estimation theory, engineering mathematics, and aerospace engineering.
Advances In Nonlinear Observer Design For State And Parameter Estimation In Energy Systems
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Author : Andreu Cecilia
language : en
Publisher: Springer Nature
Release Date : 2023-08-28
Advances In Nonlinear Observer Design For State And Parameter Estimation In Energy Systems written by Andreu Cecilia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-28 with Technology & Engineering categories.
This book reports on a set of advances relating to nonlinear observer design, with a special emphasis on high-gain observers. First, it covers the design of filters and their addition to the observer for reducing noise, a topic that has been so far neglected in the literature. Further, it describes the adaptive re-design of nonlinear observers to reduce the effect of parametric uncertainty. It discusses several limitations of classical methods, presenting a set of successfull solutions, which are mathematically formalised through Lyapunov stability analysis, and in turn validated via numerical simulations. In the second part of the book, two applications of the adaptive nonlinear observers are described, such in the estimation of the liquid water in a hydrogen fuel cell and in the solution of a common cybersecurity problem, i.e. false data injection attacks in DC microgrids. All in all, this book offers a comprehensive report on the state-of-the-art in nonlinear observer design for energy systems, including mathematical demonstrations, and numerical and and experimental validations.
Advanced State Space Methods For Neural And Clinical Data
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Author : Zhe Chen
language : en
Publisher: Cambridge University Press
Release Date : 2015-10-15
Advanced State Space Methods For Neural And Clinical Data written by Zhe Chen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-15 with Computers categories.
An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.
Advances In State And Parameter Estimation
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Author : Jitendra R. Raol
language : en
Publisher:
Release Date : 2025
Advances In State And Parameter Estimation written by Jitendra R. Raol and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Control theory categories.
"This book deals with basics of parameter estimation and state estimation as the fundamental building blocks of mathematical modelling activity in the broader field of control theory. All the methods are validated using MATLAB® based implementations with realistically simulated data for general dynamic systems, as well as for aircraft parameter estimation. This book includes several illustrative examples and chapter-end exercises. Features: Provides comprehensive coverage of all issues related to parameter and state estimation. Discusses advanced topics related to Kalman filter, stability analysis, image centroid-tracking and neural networks for parameter estimation. Explores convergence and stability results for the discussed methods. Reviews estimation of parameters in linear/nonlinear models, and distributed fitting. Includes MATLAB® based illustrative examples, and exercises. This book is aimed at researchers and graduate students in systems and control, signal processing, estimation theory, engineering mathematics, and aerospace engineering"-- Provided by publisher.
Model Calibration And Parameter Estimation
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Author : Ne-Zheng Sun
language : en
Publisher: Springer
Release Date : 2015-07-01
Model Calibration And Parameter Estimation written by Ne-Zheng Sun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-01 with Mathematics categories.
This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get familiar with advanced methods for modeling complex systems. Algorithms for mathematical tools used in this book, such as numerical optimization, automatic differentiation, adaptive parameterization, hierarchical Bayesian, metamodeling, Markov chain Monte Carlo, are covered in details. This book can be used as a reference for graduate and upper level undergraduate students majoring in environmental engineering, hydrology, and geosciences. It also serves as an essential reference book for professionals such as petroleum engineers, mining engineers, chemists, mechanical engineers, biologists, biology and medical engineering, applied mathematicians, and others who perform mathematical modeling.
Modelling And Parameter Estimation Of Dynamic Systems
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Author : J.R. Raol
language : en
Publisher: IET
Release Date : 2004-08-13
Modelling And Parameter Estimation Of Dynamic Systems written by J.R. Raol and has been published by IET this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-13 with Mathematics categories.
This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation.
Advances In Process Control With Real Applications
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Author : Ch. Venkateswarlu
language : en
Publisher: Elsevier
Release Date : 2025-06-18
Advances In Process Control With Real Applications written by Ch. Venkateswarlu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-18 with Technology & Engineering categories.
Advances in Process Control with Real Applications presents various advanced controllers, including the formulation, design, and implementation of various advanced control strategies for a wide variety of processes. These strategies include generalized predictive control with and without constraints; linear and nonlinear model predictive control; dynamic matrix control; nonlinear control, such as generic model control, globally linearizing control, and nonlinear internal model control; optimal and optimizing control; inferential control; intelligent control based on fuzzy reasoning and neural networks; and controllers based on stochastic and evolutionary optimization.This book will be highly beneficial to students, researchers, and industry professionals working in process design, process monitoring, process systems engineering, process operations and control, and related areas. - Describes various advanced controllers for the control of complex nonlinear processes - Provides the fundamentals, algorithms, approaches, control strategies, and implementation procedures systematically - Highlights the significance and importance of advanced process control with many real applications
Advanced Signal Processing Handbook
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Author : Stergios Stergiopoulos
language : en
Publisher: CRC Press
Release Date : 2017-09-08
Advanced Signal Processing Handbook written by Stergios Stergiopoulos and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-08 with Technology & Engineering categories.
Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems. The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes.
Advanced Control Of Chemical Processes Adchem 91
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Author : K. Najim
language : en
Publisher: Elsevier
Release Date : 2014-05-23
Advanced Control Of Chemical Processes Adchem 91 written by K. Najim and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-23 with Technology & Engineering categories.
This volume contains 40 papers which describe the recent developments in advanced control of chemical processes and related industries. The topics of adaptive control, model-based control and neural networks are covered by 3 survey papers. New adaptive, statistical, model-based control and artificial intelligence techniques and their applications are detailed in several papers. The problem of implementation of control algorithms on a digital computer is also considered.
Advanced Control Of Chemical Processes 1994
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Author : D. Bonvin
language : en
Publisher: Elsevier
Release Date : 2014-05-23
Advanced Control Of Chemical Processes 1994 written by D. Bonvin and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-23 with Technology & Engineering categories.
This publication brings together the latest research findings in the key area of chemical process control; including dynamic modelling and simulation - modelling and model validation for application in linear and nonlinear model-based control: nonlinear model-based predictive control and optimization - to facilitate constrained real-time optimization of chemical processes; statistical control techniques - major developments in the statistical interpretation of measured data to guide future research; knowledge-based v model-based control - the integration of theoretical aspects of control and optimization theory with more recent developments in artificial intelligence and computer science.