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Modeling Estimation And Control


Modeling Estimation And Control
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Modeling Estimation And Control


Modeling Estimation And Control
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Author : Alessandro Chiuso
language : en
Publisher: Springer
Release Date : 2007-10-24

Modeling Estimation And Control written by Alessandro Chiuso and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-24 with Technology & Engineering categories.


This Festschrift is intended as a homage to our esteemed colleague, friend and maestro Giorgio Picci on the occasion of his sixty-?fth birthday. We have knownGiorgiosince our undergraduatestudies at the University of Padova, wherewe?rst experiencedhisfascinatingteachingin theclass ofSystem Identi?cation. While progressing through the PhD program, then continuing to collaborate with him and eventually becoming colleagues, we have had many opportunitiesto appreciate the value of Giorgio as a professor and a scientist, and chie?y as a person. We learned a lot from him and we feel indebted for his scienti?c guidance, his constant support, encouragement and enthusiasm. For these reasons we are proud to dedicate this book to Giorgio. The articles in the volume will be presented by prominent researchers at the "--Ternational Conference on Modeling, Estimation and Control: A Symposium in Honor of Giorgio Picci on the Occasion of his Sixty-Fifth Birthday", to be held in Venice on October 4-5, 2007. The material covers a broad range of topics in mathematical systems theory, esti- tion, identi?cation and control, re?ecting the wide network of scienti?c relationships established during the last thirty years between the authors and Giorgio. Critical d- cussion of fundamental concepts, close collaboration on speci?c topics, joint research programs in this group of talented people have nourished the development of the?eld, where Giorgio has contributed to establishing several cornerstones.



Stochastic Models Estimation And Control


Stochastic Models Estimation And Control
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Author : Peter S. Maybeck
language : en
Publisher: Academic Press
Release Date : 1982-08-25

Stochastic Models Estimation And Control written by Peter S. Maybeck and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982-08-25 with Mathematics categories.


This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.



Hidden Markov Models


Hidden Markov Models
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Author : Robert J Elliott
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-27

Hidden Markov Models written by Robert J Elliott 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 2008-09-27 with Science categories.


As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.



Modelling And Parameter Estimation Of Dynamic Systems


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.



Dynamical Modelling Estimation In Wastewater Treatment Processes


Dynamical Modelling Estimation In Wastewater Treatment Processes
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Author : D. Dochain
language : en
Publisher: IWA Publishing
Release Date : 2001-12-01

Dynamical Modelling Estimation In Wastewater Treatment Processes written by D. Dochain and has been published by IWA Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-12-01 with Science categories.


Environmental quality is becoming an increasing concern in our society. In that context, waste and wastewater treatment, and more specifically biological wastewater treatment processes play an important role. In this book, we concentrate on the mathematical modelling of these processes. The main purpose is to provide the increasing number of professionals who are using models to design, optimise and control wastewater treatment processes with the necessary background for their activities of model building, selection and calibration. The book deals specifically with dynamic models because they allow us to describe the behaviour of treatment plants under the highly dynamic conditions that we want them to operate (e.g. Sequencing Batch Reactors) or we have to operate them (e.g. storm conditions, spills). Further extension is provided to new reactor systems for which partial differential equation descriptions are necessary to account for their distributed parameter nature (e.g. settlers, fixed bed reactors). The model building exercise is introduced as a step-wise activity that, in this book, starts from mass balancing principles. In many cases, different hypotheses and their corresponding models can be proposed for a particular process. It is therefore essential to be able to select from these candidate models in an objective manner. To this end, structure characterisation methods are introduced. Important sections of the book deal with the collection of high quality data using optimal experimental design, parameter estimation techniques for calibration and the on-line use of models in state and parameter estimators. Contents Dynamical Modelling Dynamical Mass Balance Model Building and Analysis Structure Characterisation (SC) Structural Identifiability Practical Identifiability and Optimal Experiment Design for Parameter Estimation (OED/PE) Estimation of Model Parameters Recursive State and Parameter Estimation Glossary Nomenclature



Dynamic Estimation And Control Of Power Systems


Dynamic Estimation And Control Of Power Systems
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Author : Singh Abhinav
language : en
Publisher: Academic Press
Release Date : 2018-10-08

Dynamic Estimation And Control Of Power Systems written by Singh Abhinav and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-08 with Technology & Engineering categories.


Dynamic estimation and control is a fast growing and widely researched field of study that lays the foundation for a new generation of technologies that can dynamically, adaptively and automatically stabilize power systems. This book provides a comprehensive introduction to research techniques for real-time estimation and control of power systems. Dynamic Estimation and Control of Power Systems coherently and concisely explains key concepts in a step by step manner, beginning with the fundamentals and building up to the latest developments of the field. Each chapter features examples to illustrate the main ideas, and effective research tools are presented for signal processing-based estimation of the dynamic states and subsequent control, both centralized and decentralized, as well as linear and nonlinear. Detailed mathematical proofs are included for readers who desire a deeper technical understanding of the methods. This book is an ideal research reference for engineers and researchers working on monitoring and stability of modern grids, as well as postgraduate students studying these topics. It serves to deliver a clear understanding of the tools needed for estimation and control, while also acting as a basis for readers to further develop new and improved approaches in their own research.



Modeling Estimation And Control Of Systems With Uncertainty


Modeling Estimation And Control Of Systems With Uncertainty
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Author : G. B. Dimasi
language : en
Publisher:
Release Date : 1991-09-01

Modeling Estimation And Control Of Systems With Uncertainty written by G. B. Dimasi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-09-01 with categories.




Decentralized Estimation And Control For Multisensor Systems


Decentralized Estimation And Control For Multisensor Systems
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Author : Arthur G.O. Mutambara
language : en
Publisher: Routledge
Release Date : 2019-05-20

Decentralized Estimation And Control For Multisensor Systems written by Arthur G.O. Mutambara and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-20 with Technology & Engineering categories.


Decentralized Estimation and Control for Multisensor Systems explores the problem of developing scalable, decentralized estimation and control algorithms for linear and nonlinear multisensor systems. Such algorithms have extensive applications in modular robotics and complex or large scale systems, including the Mars Rover, the Mir station, and Space Shuttle Columbia. Most existing algorithms use some form of hierarchical or centralized structure for data gathering and processing. In contrast, in a fully decentralized system, all information is processed locally. A decentralized data fusion system includes a network of sensor nodes - each with its own processing facility, which together do not require any central processing or central communication facility. Only node-to-node communication and local system knowledge are permitted. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results as those in a conventional centralized data fusion system. However, these algorithms are limited, indicating that existing decentralized data fusion algorithms have limited scalability and are wasteful of communications and computation resources. Decentralized Estimation and Control for Multisensor Systems aims to remove current limitations in decentralized data fusion algorithms and to extend the decentralized principle to problems involving local control and actuation. The text discusses: Generalizing the linear Information filter to the problem of estimation for nonlinear systems Developing a decentralized form of the algorithm Solving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant states Reducing computational requirements by using smaller local model sizes Defining internodal communication Developing estima



Advanced Kalman Filtering Least Squares And Modeling


Advanced Kalman Filtering Least Squares And Modeling
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Author : Bruce P. Gibbs
language : en
Publisher: John Wiley & Sons
Release Date : 2011-03-29

Advanced Kalman Filtering Least Squares And Modeling written by Bruce P. Gibbs 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 2011-03-29 with Technology & Engineering categories.


This book is intended primarily as a handbook for engineers who must design practical systems. Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the “best” model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior. A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared. The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems. The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering. Supplemental materials and up-to-date errata are downloadable at http://booksupport.wiley.com.



Probability Combinatorics And Control


Probability Combinatorics And Control
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Author : Andrey Kostogryzov
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-04-15

Probability Combinatorics And Control written by Andrey Kostogryzov and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-15 with Mathematics categories.


Probabilistic and combinatorial techniques are often used for solving advanced problems. This book describes different probabilistic modeling methods and their applications in various areas, such as artificial intelligence, offshore platforms, social networks, and others. It aims to educate how modern probabilistic and combinatorial models may be created to formalize uncertainties; to train how new probabilistic models can be generated for the systems of complex structures; to describe the correct use of the presented models for rational control in systems creation and operation; and to demonstrate analytical possibilities and practical effects for solving different system problems on each life cycle stage.