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Indefinite Quadratic Estimation And Control
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Book Synopsis Indefinite-Quadratic Estimation and Control by : Babak Hassibi
Download or read book Indefinite-Quadratic Estimation and Control written by Babak Hassibi and published by SIAM. This book was released on 1999-01-01 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents a unified mathematical framework for a wide range of problems in estimation and control. The authors discuss the two most commonly used methodologies: the stochastic H² approach and the deterministic (worst-case) H [infinity] approach. Despite the fundamental differences in the philosophies of these two approaches, the authors have discovered that, if indefinite metric spaces are considered, they can be treated in the same way and are essentially the same. The benefits and consequences of this unification are pursued in detail, with discussions of how to generalize well-known results from H² theory to H [infinity] setting, as well as new results and insight, the development of new algorithms, and applications to adaptive signal processing. The authors deliberately have placed primary emphasis on estimation problems which enable one to solve all the relevant control problems in detail. They also deal mostly with discrete-time systems, since these are the ones most important in current applications.
Book Synopsis Indefinite-Quadratic Estimation and Control by : Babak Hassibi
Download or read book Indefinite-Quadratic Estimation and Control written by Babak Hassibi and published by SIAM. This book was released on 1999-01-01 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a unified mathematical framework for a wide range of problems in estimation and control.
Book Synopsis Advances in Computer Science, Intelligent Systems and Environment by : David Jin
Download or read book Advances in Computer Science, Intelligent Systems and Environment written by David Jin and published by Springer Science & Business Media. This book was released on 2011-09-15 with total page 733 pages. Available in PDF, EPUB and Kindle. Book excerpt: CSISE2011 is an integrated conference concentrating its focus upon Computer Science,Intelligent System and Environment. In the proceeding, you can learn much more knowledge about Computer Science, Intelligent System and Environment of researchers all around the world. The international conference will provide a forum for engineers, scientist, teachers and all researchers to discuss their latest research achievements and their future research plan. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned field. In order to meet high standard of Springer ́s Advances in Intelligent and Soft Computing ,the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organization had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful. We hope that you can get much more knowledges from our CSISE2011, and we also hope that you can give us good suggestions to improve our work in the future.
Book Synopsis Modeling, Estimation and Optimal Filtration in Signal Processing by : Mohamed Najim
Download or read book Modeling, Estimation and Optimal Filtration in Signal Processing written by Mohamed Najim and published by John Wiley & Sons. This book was released on 2010-01-05 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing. Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed. Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented. Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and their variants.
Book Synopsis Control and Estimation of Systems with Input/Output Delays by : Huanshui Zhang
Download or read book Control and Estimation of Systems with Input/Output Delays written by Huanshui Zhang and published by Springer. This book was released on 2007-09-05 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time delays exist in many engineering systems such as transportation, communication, process engineering and networked control systems. In recent years, time delay systems have attracted recurring interests from research community. Much of the effort has been focused on stability analysis and stabilization of time delay systems using the so-called Lyapunov-Krasovskii functional together with a linear matrix inequality approach, which provides an efficient numerical tool for handling systems with delays in state and/or inputs. Recently, some more interesting and fundamental development for systems with input/output (i/o) delays has been made using time domain or frequency domain approaches. These approaches lead to analytical solutions to time delay problems in terms of Riccati equations or spectral factorizations. This monograph presents simple analytical solutions to control and estimation problems for systems with multiple i/o delays via elementary tools such as projection. We propose a re-organized innovation analysis approach for delay systems and establish a duality between optimal control of systems with multiple input delays and smoothing estimation for delay free systems. These appealing new techniques are applied to solve control and estimation problems for systems with multiple i/o delays and state delays under both the H2 and H-infinity performance criteria.
Book Synopsis Fault Diagnosis for Linear Discrete Time-Varying Systems and Its Applications by : Maiying Zhong
Download or read book Fault Diagnosis for Linear Discrete Time-Varying Systems and Its Applications written by Maiying Zhong and published by Springer Nature. This book was released on 2022-11-01 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on fault diagnosis for linear discrete time-varying (LDTV) systems and its applications in modern engineering processes, with more weighting placed on the development of theory and methodologies. A comprehensive and systematic study on fault diagnosis for LDTV systems is provided, covering H∞-optimization-based fault diagnosis, H∞-filtering-based fault diagnosis, parity space-based fault diagnosis, Krein space technique-aided fault detection and fault estimation, and their typical applications in linear/nonlinear processes such as satellite attitude control systems and INS/GPS systems. This book benefits researchers, engineers, and graduate students in the fields of control engineering, electrical and electronic engineering, instrumentation science, and optoelectronic engineering.
Book Synopsis Optimal State Estimation by : Dan Simon
Download or read book Optimal State Estimation written by Dan Simon and published by John Wiley & Sons. This book was released on 2006-06-19 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.
Book Synopsis Optimal and Robust State Estimation by : Yuriy S. Shmaliy
Download or read book Optimal and Robust State Estimation written by Yuriy S. Shmaliy and published by John Wiley & Sons. This book was released on 2022-07-20 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified and systematic theoretical framework for solving problems related to finite impulse response (FIR) estimate Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches is a comprehensive investigation into batch state estimators and recursive forms. The work begins by introducing the reader to the state estimation approach and provides a brief historical overview. Next, the work discusses the specific properties of finite impulse response (FIR) state estimators. Further chapters give the basics of probability and stochastic processes, discuss the available linear and nonlinear state estimators, deal with optimal FIR filtering, and consider a limited memory batch and recursive algorithms. Other topics covered include solving the q-lag FIR smoothing problem, introducing the receding horizon (RH) FIR state estimation approach, and developing the theory of FIR state estimation under disturbances. The book closes by discussing the theory of FIR state estimation for uncertain systems and providing several applications where the FIR state estimators are used effectively. Key concepts covered in the work include: A holistic overview of the state estimation approach, which arose from the need to know the internal state of a real system, given that the input and output are both known Optimal, optimal unbiased, maximum likelihood, and unbiased and robust finite impulse response (FIR) structures FIR state estimation approach along with the infinite impulse response (IIR) and Kalman approaches Cost functions and the most critical properties of FIR and IIR state estimates Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches was written for professionals in the fields of microwave engineering, system engineering, and robotics who wish to move towards solving finite impulse response (FIR) estimate issues in both theoretical and practical applications. Graduate and senior undergraduate students with coursework dealing with state estimation will also be able to use the book to gain a valuable foundation of knowledge and become more adept in their chosen fields of study.
Book Synopsis State Estimation for Nonlinear Continuous–Discrete Stochastic Systems by : Gennady Yu. Kulikov
Download or read book State Estimation for Nonlinear Continuous–Discrete Stochastic Systems written by Gennady Yu. Kulikov and published by Springer Nature. This book was released on with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Least-Mean-Square Adaptive Filters by : Simon Haykin
Download or read book Least-Mean-Square Adaptive Filters written by Simon Haykin and published by John Wiley & Sons. This book was released on 2003-09-08 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by the original inventor of the technology. Includes contributions by the foremost experts in the field. The only book to cover these topics together.
Book Synopsis Total Least Squares and Errors-in-Variables Modeling by : S. van Huffel
Download or read book Total Least Squares and Errors-in-Variables Modeling written by S. van Huffel and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: In response to a growing interest in Total Least Squares (TLS) and Errors-In-Variables (EIV) modeling by researchers and practitioners, well-known experts from several disciplines were invited to prepare an overview paper and present it at the third international workshop on TLS and EIV modeling held in Leuven, Belgium, August 27-29, 2001. These invited papers, representing two-thirds of the book, together with a selection of other presented contributions yield a complete overview of the main scientific achievements since 1996 in TLS and Errors-In-Variables modeling. In this way, the book nicely completes two earlier books on TLS (SIAM 1991 and 1997). Not only computational issues, but also statistical, numerical, algebraic properties are described, as well as many new generalizations and applications. Being aware of the growing interest in these techniques, it is a strong belief that this book will aid and stimulate users to apply the new techniques and models correctly to their own practical problems.
Book Synopsis Digital Signal Processing Handbook on CD-ROM by : VIJAY MADISETTI
Download or read book Digital Signal Processing Handbook on CD-ROM written by VIJAY MADISETTI and published by CRC Press. This book was released on 1999-02-26 with total page 1725 pages. Available in PDF, EPUB and Kindle. Book excerpt: A best-seller in its print version, this comprehensive CD-ROM reference contains unique, fully searchable coverage of all major topics in digital signal processing (DSP), establishing an invaluable, time-saving resource for the engineering community. Its unique and broad scope includes contributions from all DSP specialties, including: telecommunications, computer engineering, acoustics, seismic data analysis, DSP software and hardware, image and video processing, remote sensing, multimedia applications, medical technology, radar and sonar applications
Book Synopsis Modeling and Control of Economic Systems 2001 by : R. Neck
Download or read book Modeling and Control of Economic Systems 2001 written by R. Neck and published by Elsevier. This book was released on 2003-05-21 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains papers presented at the IFAC symposium on Modeling and control of Economic Systems (SME 2001), which was held at the university of Klagenfurt, Austria. The symposium brought together scientists and users to explore current theoretical developments of modeling techniques for economic systems. It contains a section of plenary, invited and contributed papers presented at the SME 2001 symposium. The papers presented in this volume reflect advances both in methodology and in applications in the area of modeling and control of economic systems.
Book Synopsis Nonlinear Filters by : Sueo Sugimoto
Download or read book Nonlinear Filters written by Sueo Sugimoto and published by Ohmsha, Ltd.. This book was released on 2020-12-10 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a broad range of filter theories, algorithms, and numerical examples. The representative linear and nonlinear filters such as the Kalman filter, the steady-state Kalman filter, the H infinity filter, the extended Kalman filter, the Gaussian sum filter, the statistically linearized Kalman filter, the unscented Kalman filter, the Gaussian filter, the cubature Kalman filter are first visited. Then, the non-Gaussian filters such as the ensemble Kalman filter and the particle filters based on the sequential Bayesian filter and the sequential importance resampling are described, together with their recent advances. Moreover, the information matrix in the nonlinear filtering, the nonlinear smoother based on the Markov Chain Monte Carlo, the continuous-discrete filters, factorized filters, and nonlinear filters based on stochastic approximation method are detailed. 1 Review of the Kalman Filter and Related Filters 2 Information Matrix in Nonlinear Filtering 3 Extended Kalman Filter and Gaussian Sum Filter 4 Statistically Linearized Kalman Filter 5 The Unscented Kalman Filter 6 General Gaussian Filters and Applications 7 The Ensemble Kalman Filter 8 Particle Filter 9 Nonlinear Smoother with Markov Chain Monte Carlo 10 Continuous-Discrete Filters 11 Factorized Filters 12 Nonlinear Filters Based on Stochastic Approximation Method
Book Synopsis Minimax Approaches to Robust Model Predictive Control by : Johan Löfberg
Download or read book Minimax Approaches to Robust Model Predictive Control written by Johan Löfberg and published by Linköping University Electronic Press. This book was released on 2003-04-11 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Controlling a system with control and state constraints is one of the most important problems in control theory, but also one of the most challenging. Another important but just as demanding topic is robustness against uncertainties in a controlled system. One of the most successful approaches, both in theory and practice, to control constrained systems is model predictive control (MPC). The basic idea in MPC is to repeatedly solve optimization problems on-line to find an optimal input to the controlled system. In recent years, much effort has been spent to incorporate the robustness problem into this framework. The main part of the thesis revolves around minimax formulations of MPC for uncertain constrained linear discrete-time systems. A minimax strategy in MPC means that worst-case performance with respect to uncertainties is optimized. Unfortunately, many minimax MPC formulations yield intractable optimization problems with exponential complexity. Minimax algorithms for a number of uncertainty models are derived in the thesis. These include systems with bounded external additive disturbances, systems with uncertain gain, and systems described with linear fractional transformations. The central theme in the different algorithms is semidefinite relaxations. This means that the minimax problems are written as uncertain semidefinite programs, and then conservatively approximated using robust optimization theory. The result is an optimization problem with polynomial complexity. The use of semidefinite relaxations enables a framework that allows extensions of the basic algorithms, such as joint minimax control and estimation, and approx- imation of closed-loop minimax MPC using a convex programming framework. Additional topics include development of an efficient optimization algorithm to solve the resulting semidefinite programs and connections between deterministic minimax MPC and stochastic risk-sensitive control. The remaining part of the thesis is devoted to stability issues in MPC for continuous-time nonlinear unconstrained systems. While stability of MPC for un-constrained linear systems essentially is solved with the linear quadratic controller, no such simple solution exists in the nonlinear case. It is shown how tools from modern nonlinear control theory can be used to synthesize finite horizon MPC controllers with guaranteed stability, and more importantly, how some of the tech- nical assumptions in the literature can be dispensed with by using a slightly more complex controller.
Book Synopsis Principles of Signal Detection and Parameter Estimation by : Bernard C. Levy
Download or read book Principles of Signal Detection and Parameter Estimation written by Bernard C. Levy and published by Springer Science & Business Media. This book was released on 2008-07-07 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and current understanding of signal detection and estimation, including problems and solutions for each chapter. Signal detection plays an important role in fields such as radar, sonar, digital communications, image processing, and failure detection. The book explores both Gaussian detection and detection of Markov chains, presenting a unified treatment of coding and modulation topics. Addresses asymptotic of tests with the theory of large deviations, and robust detection. This text is appropriate for students of Electrical Engineering in graduate courses in Signal Detection and Estimation.
Book Synopsis Computational Science - ICCS 2006 by : Vassil N. Alexandrov
Download or read book Computational Science - ICCS 2006 written by Vassil N. Alexandrov and published by Springer. This book was released on 2006-05-10 with total page 1173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is Volume I of the four-volume set LNCS 3991-3994 constituting the refereed proceedings of the 6th International Conference on Computational Science, ICCS 2006. The 98 revised full papers and 29 revised poster papers of the main track presented together with 500 accepted workshop papers were carefully reviewed and selected for inclusion in the four volumes. The coverage spans the whole range of computational science.