Optimal State Estimation

Kalman, H Infinity, and Nonlinear Approaches

Author: Dan Simon

Publisher: John Wiley & Sons

ISBN: 0470045337

Category: Technology & Engineering

Page: 552

View: 2067


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.

The 1st International Workshop on the Quality of Geodetic Observation and Monitoring Systems (QuGOMS'11)

Proceedings of the 2011 IAG International Workshop, Munich, Germany April 13–15, 2011

Author: Hansjörg Kutterer,Florian Seitz,Hamza Alkhatib,Michael Schmidt

Publisher: Springer

ISBN: 331910828X

Category: Science

Page: 183

View: 3759


These proceedings contain 25 papers, which are the peer-reviewed versions of presentations made at the 1st International Workshop on the Quality of Geodetic Observation and Monitoring (QuGOMS’11), held 13 April to 15 April 2011 in Garching, Germany. The papers were drawn from five sessions which reflected the following topic areas: (1) Uncertainty Modeling of Geodetic Data, (2) Theoretical Studies on Combination Strategies and Parameter Estimation, (3) Recursive State-Space Filtering, (4) Sensor Networks and Multi Sensor Systems in Engineering Geodesy, (5) Multi-Mission Approaches With View to Physical Processes in the Earth System.

Grid-based Nonlinear Estimation and Its Applications

Author: Bin Jia,Ming Xin

Publisher: CRC Press

ISBN: 1351757415

Category: Mathematics

Page: 252

View: 8701


Grid-based Nonlinear Estimation and its Applications presents new Bayesian nonlinear estimation techniques developed in the last two decades. Grid-based estimation techniques are based on efficient and precise numerical integration rules to improve performance of the traditional Kalman filtering based estimation for nonlinear and uncertainty dynamic systems. The unscented Kalman filter, Gauss-Hermite quadrature filter, cubature Kalman filter, sparse-grid quadrature filter, and many other numerical grid-based filtering techniques have been introduced and compared in this book. Theoretical analysis and numerical simulations are provided to show the relationships and distinct features of different estimation techniques. To assist the exposition of the filtering concept, preliminary mathematical review is provided. In addition, rather than merely considering the single sensor estimation, multiple sensor estimation, including the centralized and decentralized estimation, is included. Different decentralized estimation strategies, including consensus, diffusion, and covariance intersection, are investigated. Diverse engineering applications, such as uncertainty propagation, target tracking, guidance, navigation, and control, are presented to illustrate the performance of different grid-based estimation techniques.

State Estimation for Robotics

Author: Timothy D. Barfoot

Publisher: Cambridge University Press

ISBN: 1107159393

Category: Computers

Page: 350

View: 1741


A modern look at state estimation, targeted at students and practitioners of robotics, with emphasis on three-dimensional applications.

An engineering approach to optimal control and estimation theory

Author: George M. Siouris

Publisher: Wiley-Interscience


Category: Science

Page: 407

View: 1474


A much-awaited guide to real-world problems in modern control and estimation This combined text and reference deals with the design of modern control systems. It is the first book in this rapidly growing field to approach optimal control and optimal estimation from a strictly pragmatic standpoint. Sidestepping the realm of theoretical mathematics, An Engineering Approach to Optimal Control and Estimation Theory offers realistic and workable solutions that can be put to immediate use by electrical and mechanical engineers in aerospace and in many other applications. The author draws on his extensive experience in research and development from industry, government, and academia to present systematic, accessible coverage of all important topics, including: * All basic mathematics needed to apply subsequent information * A historical perspective on the evolution of modern control and estimation theory * All major concepts relevant to the design of modern control systems--from the Kalman filter, to linear regulators, to decentralized Kalman filters * Practical examples useful in applying the principles under discussion * Problems at the end of each chapter * Carefully selected references from the vast number of books published on this subject * Appendixes reviewing matrix algebra that is central to modern control theory, as well as matrix subroutines, useful to both students and practicing engineers Optimal Control and Estimation Theory Optimal control and optimal estimation have seen tremendous growth over the past three decades, owing to major advances in aerospace and other types of engineering. Optimal control and estimation theory is crucial to the design of modern control systems; for instance, navigation, mobile robotics, or automated vehicles and aircraft. It ensures that variables such as temperatures or pressure are kept in check, regardless of the disturbance the system undergoes. Despite the proliferation of books on the subject, most of the material published in this area is highly theoretical, and approaches the subject in a "theorem-proof" fashion, which is more appropriate to mathematics than to an engineering text. As its title suggests, An Engineering Approach to Optimal Control and Estimation Theory provides a practical and accessible guide, focusing on applications and implementation, and answering real-world questions faced by control engineers. In its highly organized overview of all areas, the book examines the design of modern optimal controllers requiring the selection of a performance criterion, demonstrates optimization of linear systems with bounded controls and limited control effort, and considers nonlinearities and their effect on various types of signals. Covering all the basics, the book deals with the evolution of optimal control and estimation theory, and presents the necessary mathematical background needed for this study. It also lists references and problems, and supplies appendixes for those wishing to delve into matrix algebra. Throughout, it offers opportunities for experimentation, while discussing analysis, various filtering methods, and many other pertinent topics. An Engineering Approach to Optimal Control and Estimation Theory is an invaluable, self-contained reference for practicing engineers, a useful text for graduate students and qualified senior undergraduates, and an important resource for anyone interested in the future of modern control technology.

Intelligent Systems and Automation

2nd Mediterranean Conference on Intelligent Systems and Automation (CISA '09)

Author: Lotfi Beji,Samir Otmane,Azgal Abichou

Publisher: American Inst. of Physics


Category: Computers

Page: 408

View: 8638


The aim of CISA’09 is to present the latest research and application results emerging from new research and technological developments of complex systems and intelligent machines acting on known or unknown, virtual or real, environments in an autonomous way or in cooperation with humans. This field requires skills in automation and control, perception of the environment, human-computer interfaces, mechanics and design, simulation, etc. It also aims at encouraging scientific cooperation between North and South and promoting scientific exchanges through a durable event.

Extending H-infinity Control to Nonlinear Systems

Control of Nonlinear Systems to Achieve Performance Objectives

Author: J. William Helton,Matthew R. James

Publisher: SIAM

ISBN: 9780898719840

Category: H [infinity symbol] control

Page: 333

View: 5724


H-infinity control originated from an effort to codify classical control methods, where one shapes frequency response functions for linear systems to meet certain objectives. H-infinity control underwent tremendous development in the 1980s and made considerable strides toward systematizing classical control. This book addresses the next major issue of how this extends to nonlinear systems. At the core of nonlinear control theory lie two partial differential equations (PDEs). One is a first-order evolution equation called the information state equation, which constitutes the dynamics of the controller. One can view this equation as a nonlinear dynamical system. Much of this volume is concerned with basic properties of this system, such as the nature of trajectories, stability, and, most important, how it leads to a general solution of the nonlinear H-infinity control problem.