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Author : John L. Crassidis
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (11 download)
Download or read book Predictive Filtering for Non-linear Systems written by John L. Crassidis and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peyman Setoodeh
Publisher : John Wiley & Sons
ISBN 13 : 1119078156
Total Pages : 308 pages
Book Rating : 4.1/5 (19 download)
Download or read book Nonlinear Filters written by Peyman Setoodeh and published by John Wiley & Sons. This book was released on 2022-03-04 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: NONLINEAR FILTERS Discover the utility of using deep learning and (deep) reinforcement learning in deriving filtering algorithms with this insightful and powerful new resource Nonlinear Filters: Theory and Applications delivers an insightful view on state and parameter estimation by merging ideas from control theory, statistical signal processing, and machine learning. Taking an algorithmic approach, the book covers both classic and machine learning-based filtering algorithms. Readers of Nonlinear Filters will greatly benefit from the wide spectrum of presented topics including stability, robustness, computability, and algorithmic sufficiency. Readers will also enjoy: Organization that allows the book to act as a stand-alone, self-contained reference A thorough exploration of the notion of observability, nonlinear observers, and the theory of optimal nonlinear filtering that bridges the gap between different science and engineering disciplines A profound account of Bayesian filters including Kalman filter and its variants as well as particle filter A rigorous derivation of the smooth variable structure filter as a predictor-corrector estimator formulated based on a stability theorem, used to confine the estimated states within a neighborhood of their true values A concise tutorial on deep learning and reinforcement learning A detailed presentation of the expectation maximization algorithm and its machine learning-based variants, used for joint state and parameter estimation Guidelines for constructing nonparametric Bayesian models from parametric ones Perfect for researchers, professors, and graduate students in engineering, computer science, applied mathematics, and artificial intelligence, Nonlinear Filters: Theory and Applications will also earn a place in the libraries of those studying or practicing in fields involving pandemic diseases, cybersecurity, information fusion, augmented reality, autonomous driving, urban traffic network, navigation and tracking, robotics, power systems, hybrid technologies, and finance.
Author : Jitendra R. Raol
Publisher : CRC Press
ISBN 13 : 1498745180
Total Pages : 581 pages
Book Rating : 4.4/5 (987 download)
Download or read book Nonlinear Filtering written by Jitendra R. Raol and published by CRC Press. This book was released on 2017-07-12 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Filtering covers linear and nonlinear filtering in a comprehensive manner, with appropriate theoretic and practical development. Aspects of modeling, estimation, recursive filtering, linear filtering, and nonlinear filtering are presented with appropriate and sufficient mathematics. A modeling-control-system approach is used when applicable, and detailed practical applications are presented to elucidate the analysis and filtering concepts. MATLAB routines are included, and examples from a wide range of engineering applications - including aerospace, automated manufacturing, robotics, and advanced control systems - are referenced throughout the text.
Author : National Research Council (U.S.). Committee on Applied and Theoretical Statistics. Panel on Statistics and Oceanography
Publisher : National Academies
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.0/5 (21 download)
Download or read book Statistics and Physical Oceanography written by National Research Council (U.S.). Committee on Applied and Theoretical Statistics. Panel on Statistics and Oceanography and published by National Academies. This book was released on 1993 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Lalo Magni
Publisher : Springer Science & Business Media
ISBN 13 : 3642010938
Total Pages : 562 pages
Book Rating : 4.6/5 (42 download)
Download or read book Nonlinear Model Predictive Control written by Lalo Magni and published by Springer Science & Business Media. This book was released on 2009-05-25 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.
Author : Huiping Li
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (889 download)
Download or read book Filtering and Model Predictive Control of Networked Nonlinear Systems written by Huiping Li and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Networked control systems (NCSs) present many advantages such as easy installation and maintenance, flexible layouts and structures of components, and efficient allocation and distribution of resources. Consequently, they find potential applications in a variety of emerging industrial systems including multi-agent systems, power grids, tele-operations and cyber-physical systems. The study of NCSs with nonlinear dynamics (i.e., nonlinear NCSs) is a very significant yet challenging topic, and it not only widens application areas of NCSs in practice, but also extends the theoretical framework of NCSs with linear dynamics (i.e., linear NCSs). Numerous issues are required to be resolved towards a fully-fledged theory of industrial nonlinear NCS design. In this dissertation, three important problems of nonlinear NCSs are investigated: The robust filtering problem, the robust model predictive control (MPC) problem and the robust distributed MPC problem of large-scale nonlinear systems. In the robust filtering problem of nonlinear NCSs, the nonlinear system model is subject to uncertainties and external disturbances, and the measurements suffer from time delays governed by a Markov process. Utilizing the Lyapunov theory, the algebraic Hamilton-Jacobi inequality (HJI)-based sufficient conditions are established for designing the H_infty nonlinear filter. Moreover, the developed results are specialized for a special type of nonlinear systems, by presenting the HJI in terms of matrix inequalities. For the robust MPC problem of NCSs, three aspects are considered. Firstly, to reduce the computation and communication load, the networked MPC scheme with an efficient transmission and compensation strategy is proposed, for constrained nonlinear NCSs with disturbances and two-channel packet dropouts. A novel Lyapunov function is constructed to ensure the input-to-state practical stability (ISpS) of the closed-loop system. Secondly, to improve robustness, a networked min-max MPC scheme are developed, for constrained nonlinear NCSs subject to external disturbances, input and state constraints, and network-induced constraints. The ISpS of the resulting nonlinear NCS is established by constructing a new Lyapunov function. Finally, to deal with the issue of unavailability of system state, a robust output feedback MPC scheme is designed for constrained linear systems subject to periodical measurement losses and external disturbances. The rigorous feasibility and stability conditions are established.For the robust distributed MPC problem of large-scale nonlinear systems, three steps are taken to conduct the studies. In the first step, the issue of external disturbances is addressed. A robustness constraint is proposed to handle the external disturbances, based on which a novel robust distributed MPC algorithm is designed. The conditions for guaranteeing feasibility and stability are established, respectively. In the second step, the issue of communication delays are dealt with. By designing the waiting mechanism, a distributed MPC scheme is proposed, and the feasibility and stability conditions are established. In the third step, the robust distributed MPC problem for large-scale nonlinear systems subject to control input constraints, communication delays and external disturbances are studied. A dual-mode robust distributed MPC strategy is designed to deal with the communication delays and the external disturbances simultaneously, and the feasibility and the stability conditions are developed, accordingly.
Author : Robert Kalaba
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (833 download)
Download or read book Exact Sequential Filtering, Smoothing and Prediction for Nonlinear Systems written by Robert Kalaba and published by . This book was released on 1985 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Danilo Comminiello
Publisher : Butterworth-Heinemann
ISBN 13 : 0128129778
Total Pages : 390 pages
Book Rating : 4.1/5 (281 download)
Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello and published by Butterworth-Heinemann. This book was released on 2018-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.
Author : Simone Loureiro de Oliveira
Publisher : vdf Hochschulverlag AG
ISBN 13 : 9783728123947
Total Pages : 274 pages
Book Rating : 4.1/5 (239 download)
Download or read book Model Predictive Control for Constrained Nonlinear Systems written by Simone Loureiro de Oliveira and published by vdf Hochschulverlag AG. This book was released on 1996 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Tokunbo Ogunfunmi
Publisher : Springer Science & Business Media
ISBN 13 : 0387686304
Total Pages : 238 pages
Book Rating : 4.3/5 (876 download)
Download or read book Adaptive Nonlinear System Identification written by Tokunbo Ogunfunmi and published by Springer Science & Business Media. This book was released on 2007-09-05 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Author : Hisashi Tanizaki
Publisher : Springer Science & Business Media
ISBN 13 : 3662032236
Total Pages : 264 pages
Book Rating : 4.6/5 (62 download)
Download or read book Nonlinear Filters written by Hisashi Tanizaki and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear and nonnormal filters are introduced and developed. Traditional nonlinear filters such as the extended Kalman filter and the Gaussian sum filter give biased filtering estimates, and therefore several nonlinear and nonnormal filters have been derived from the underlying probability density functions. The density-based nonlinear filters introduced in this book utilize numerical integration, Monte-Carlo integration with importance sampling or rejection sampling and the obtained filtering estimates are asymptotically unbiased and efficient. By Monte-Carlo simulation studies, all the nonlinear filters are compared. Finally, as an empirical application, consumption functions based on the rational expectation model are estimated for the nonlinear filters, where US, UK and Japan economies are compared.
Author : Gopinath Kallianpur
Publisher : CRC Press
ISBN 13 : 9782881246852
Total Pages : 624 pages
Book Rating : 4.2/5 (468 download)
Download or read book White Noise Theory of Prediction, Filtering and Smoothing written by Gopinath Kallianpur and published by CRC Press. This book was released on 1988-01-01 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the author’s own research, this book rigorously and systematically develops the theory of Gaussian white noise measures on Hilbert spaces to provide a comprehensive account of nonlinear filtering theory. Covers Markov processes, cylinder and quasi-cylinder probabilities and conditional expectation as well as predictio0n and smoothing and the varied processes used in filtering. Especially useful for electronic engineers and mathematical statisticians for explaining the systematic use of finely additive white noise theory leading to a more simplified and direct presentation.
Author : Oliver Nelles
Publisher : Springer Science & Business Media
ISBN 13 : 3662043238
Total Pages : 785 pages
Book Rating : 4.6/5 (62 download)
Download or read book Nonlinear System Identification written by Oliver Nelles and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Author : Kumar Pakki Bharani Chandra
Publisher : Springer
ISBN 13 : 3030017974
Total Pages : 197 pages
Book Rating : 4.0/5 (3 download)
Download or read book Nonlinear Filtering written by Kumar Pakki Bharani Chandra and published by Springer. This book was released on 2018-11-20 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods, which help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications, which can be downloaded from the Springer Extra Materials website.
Author : Kumar Pakki Bharani Chan
Publisher :
ISBN 13 : 9783030017989
Total Pages : pages
Book Rating : 4.0/5 (179 download)
Download or read book Nonlinear Filtering written by Kumar Pakki Bharani Chan and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters, etc. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB codes associated with case-study applications can be downloaded from the Springer Extra Materials website.
Author : Reza N. Jazar
Publisher : Springer
ISBN 13 : 3319270559
Total Pages : 428 pages
Book Rating : 4.3/5 (192 download)
Download or read book Nonlinear Approaches in Engineering Applications written by Reza N. Jazar and published by Springer. This book was released on 2016-05-27 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book looks at the broad field of engineering science through the lens of nonlinear approaches. Examples focus on issues in vehicle technology, including vehicle dynamics, vehicle-road interaction, steering, and control for electric and hybrid vehicles. Also included are discussions on train and tram systems, aerial vehicles, robot-human interaction, and contact and scratch analysis at the micro/nanoscale. Chapters are based on invited contributions from world-class experts in the field who advance the future of engineering by discussing the development of more optimal, accurate, efficient, and cost and energy effective systems. This book is appropriate for researchers, students, and practicing engineers who are interested in the applications of nonlinear approaches to solving engineering and science problems.
Author : Lu Cao
Publisher : Academic Press
ISBN 13 : 0128218665
Total Pages : 284 pages
Book Rating : 4.1/5 (282 download)
Download or read book Predictive Filtering for Microsatellite Control System written by Lu Cao and published by Academic Press. This book was released on 2020-11-26 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Filtering for Microsatellite Control Systems introduces technological design, modeling, stability analysis, predictive filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically and almost self-contained description of the many facets of envisaging, designing, implementing or experimentally exploring predictive filtering for spacecraft control systems, along with the adequate designs of integrated modeling, dynamics, state estimation, and signal processing of spacecrafts and nonlinear systems. Unifies existing and emerging concepts concerning predictive filtering theory, state estimation, and signal processing for spacecraft control systems Provides a series of latest results in, including but not limited to, nonlinear filtering, attitude determination, and state estimation towards spacecraft control systems Gives numerical and simulation results in each chapter in order to reflect the engineering practice and demonstrate the main focus of the developed analysis and synthesis approach Covers advanced topics in nonlinear filtering with aerospace application
