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Author: Guanrong Chen
Publisher:
ISBN:
Category : Approximation theory
Languages : en
Pages : 6
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Book Description
A very simple yet efficient treatment is suggested in this short note as a suboptimal Kalman filtering algorithm for the standard filtering process under the irregular environment where some measurement data information is missing. Convergence analysis for the proposed algorithm is given.
Author: Guanrong Chen
Publisher:
ISBN:
Category : Approximation theory
Languages : en
Pages : 6
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Book Description
A very simple yet efficient treatment is suggested in this short note as a suboptimal Kalman filtering algorithm for the standard filtering process under the irregular environment where some measurement data information is missing. Convergence analysis for the proposed algorithm is given.
Author: Ian R. Petersen
Publisher: Springer Science & Business Media
ISBN: 1461215943
Category : Technology & Engineering
Languages : en
Pages : 206
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Book Description
A significant shortcoming of the state space control theory that emerged in the 1960s was its lack of concern for the issue of robustness. However, in the design of feedback control systems, robustness is a critical issue. These facts led to great activity in the research area of robust control theory. One of the major developments of modern control theory was the Kalman Filter and hence the development of a robust version of the Kalman Filter has become an active area of research. Although the issue of robustness in filtering is not as critical as in feedback control (where there is always the issue of instability to worry about), research on robust filtering and state estimation has remained very active in recent years. However, although numerous books have appeared on the topic of Kalman filtering, this book is one of the first to appear on robust Kalman filtering. Most of the material presented in this book derives from a period of research collaboration between the authors from 1992 to 1994. However, its origins go back earlier than that. The first author (LR. P. ) became in terested in problems of robust filtering through his research collaboration with Dr. Duncan McFarlane. At this time, Dr. McFarlane was employed at the Melbourne Research Laboratories ofBHP Ltd. , a large Australian min erals, resources, and steel processing company.
Author: Guoliang Wei
Publisher: CRC Press
ISBN: 1498760759
Category : Mathematics
Languages : en
Pages : 250
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Book Description
Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for stochastic systems with traditional and emerging engineering-oriented complexities. The book begins with an overview of the relevant background, motivation, and research problems, and then: Discusses the robust stability and stabilization problems for a class of stochastic time-delay interval systems with nonlinear disturbances Investigates the robust stabilization and H∞ control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbances Explores the H∞ state estimator and H∞ output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances, sensor nonlinearities, and Markovian jumping parameters Analyzes the H∞ performance for a general class of nonlinear stochastic systems with time delays, where the addressed systems are described by general stochastic functional differential equations Studies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbances Uses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete information Evaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet losses Examines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delays Considers the H∞ state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delays Addresses the H∞ synchronization control problem for a class of dynamical networks with randomly varying nonlinearities Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities describes novel methodologies that can be applied extensively in lab simulations, field experiments, and real-world engineering practices. Thus, this text provides a valuable reference for researchers and professionals in the signal processing and control engineering communities.
Author: Leon Bess
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 36
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Book Description
Author: Sy-Miin Chow
Publisher:
ISBN:
Category :
Languages : en
Pages : 528
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Book Description
Author: Ran Y. Gazit
Publisher:
ISBN:
Category :
Languages : en
Pages : 206
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Book Description
Author: Naeem Khan
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Kalrnan filter relies heavily on perfect knowledge of sensor readings, used to compute the minimum mean square error estimate of the system state. However in reality, unavailability of output data might occur due to factors including sensor faults and failures, confined memory spaces of buffer registers and congestion of communication channels. Therefore investigations on the effectiveness of Kalman filtering in the case of imperfect data have, since the last decade, been an interesting yet challenging research topic. The prevailed methodology employed in the state estimation for imperfect data is the open loop estimation wherein the measurement update step is skipped during data loss time. This method has several shortcomings such as high divergence rate, not regaining its steady states after the data is resumed, etc. This thesis proposes a novel approach, which is found efficient for both stationary and non- stationary processes, for the above scenario, based on linear prediction schemes. Utilising the concept of linear prediction, the missing data (output signal) is reconstructed through modified linear prediction schemes. This signal is then employed in Kalman filtering at the measure- ment update step. To reduce the computational cost in the large matrix inversions, a modified Levinson-Durbin algorithm is employed. It is shown that the proposed scheme offers promising results in the event of loss of observations and exhibits the general properties of conventional Kalman filters. To demonstrate the effectiveness of the proposed scheme, a rigid body spacecraft case study subject to measurement loss has been considered.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 700
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Book Description
Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 111898496X
Category : Technology & Engineering
Languages : en
Pages : 639
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Book Description
The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
Author: Brian D. O. Anderson
Publisher: Courier Corporation
ISBN: 0486136892
Category : Science
Languages : en
Pages : 370
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Book Description
Graduate-level text extends studies of signal processing, particularly regarding communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; discrete-time Kalman filter; time-invariant filters; more. 1979 edition.
