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Kalman Filtering With Inequality Constraints For Turbofan Engine Health Estimation
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Book Synopsis Kalman Filtering With Inequality Constraints for Turbofan Engine Health Estimation by :
Download or read book Kalman Filtering With Inequality Constraints for Turbofan Engine Health Estimation written by and published by . This book was released on 2003 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satis- fied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estima- tion accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model con- tains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781723734168 Total Pages :38 pages Book Rating :4.7/5 (341 download)
Book Synopsis Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation by : National Aeronautics and Space Adm Nasa
Download or read book Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-09-15 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satisfied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.Simon, Dan and Simon, Donald L.Glenn Research CenterTURBOFAN ENGINES; AIRCRAFT ENGINES; KALMAN FILTERS; QUADRATIC PROGRAMMING; SYSTEMS HEALTH MONITORING; GAS TURBINE ENGINES; ALGORITHMS; ESTIMATES; INEQUALITIES; SIMULATION
Book Synopsis Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering by :
Download or read book Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering written by and published by . This book was released on 2003 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781724120250 Total Pages :28 pages Book Rating :4.1/5 (22 download)
Book Synopsis Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering by : National Aeronautics and Space Adm Nasa
Download or read book Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2018-09-28 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering. Simon, Dan and Simon, Donald L. Glenn Research Center NASA/TM-2003-212528, ARL-TR-2956, GT2003-38584, E-14090, NAS 1.15:212528...
Author :National Aeronautics and Space Administration (NASA) Publisher :Createspace Independent Publishing Platform ISBN 13 :9781721590476 Total Pages :28 pages Book Rating :4.5/5 (94 download)
Book Synopsis Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering by : National Aeronautics and Space Administration (NASA)
Download or read book Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-06-20 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering. Simon, Dan and Simon, Donald L. Glenn Research Center NASA/TM-2003-212528, ARL-TR-2956, GT2003-38584, E-14090, NAS 1.15:212528
Author :National Aeronautics and Space Administration (NASA) Publisher :Createspace Independent Publishing Platform ISBN 13 :9781720451761 Total Pages :28 pages Book Rating :4.4/5 (517 download)
Book Synopsis Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation by : National Aeronautics and Space Administration (NASA)
Download or read book Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-05-29 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).Simon, Dan and Simon, Donald L.Glenn Research CenterTURBOFAN ENGINES; PROBABILITY THEORY; KALMAN FILTERS; AIRCRAFT ENGINES; FLIGHT SAFETY; INEQUALITIES; SIMULATION
Book Synopsis Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation by : National Aeronaut Administration (Nasa)
Download or read book Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation written by National Aeronaut Administration (Nasa) and published by . This book was released on 2020-08-05 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health. Simon, Dan and Simon, Donald L. Glenn Research Center NASA/TM-2005-213962, ARL-MR-621, E-15278 TURBOFAN ENGINES; KALMAN FILTERS; ESTIMATES; HEURISTIC METHODS; RISK; SIMULATION; INEQUALITIES
Book Synopsis Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation by : Nasa Technical Reports Server (Ntrs)
Download or read book Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation written by Nasa Technical Reports Server (Ntrs) and published by BiblioGov. This book was released on 2013-07 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.
Book Synopsis Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation by : Nasa Technical Reports Server (Ntrs)
Download or read book Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation written by Nasa Technical Reports Server (Ntrs) and published by BiblioGov. This book was released on 2013-07 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters.
Book Synopsis Kalman Filtering With Inequity Constraints For Turbofan Engine Health Estimation... NASA/TM-2003-212111... National Aeronautics And Space Administration by : United States. National Aeronautics and Space Administration
Download or read book Kalman Filtering With Inequity Constraints For Turbofan Engine Health Estimation... NASA/TM-2003-212111... National Aeronautics And Space Administration written by United States. National Aeronautics and Space Administration and published by . This book was released on 2003* with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation by : Dan Simon
Download or read book Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation written by Dan Simon and published by . This book was released on 2005 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filters by : Ginalber Luiz Serra
Download or read book Kalman Filters written by Ginalber Luiz Serra and published by BoD – Books on Demand. This book was released on 2018-02-21 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent issues on theory and practice of Kalman filters, with a comprehensive treatment of a selected number of concepts, techniques, and advanced applications. From an interdisciplinary point of view, the contents from each chapter bring together an international scientific community to discuss the state of the art on Kalman filter-based methodologies for adaptive/distributed filtering, optimal estimation, dynamic prediction, nonstationarity, robot navigation, global navigation satellite systems, moving object tracking, optical communication systems, and active power filters, among others. The theoretical and methodological foundations combined with extensive experimental explanation make this book a reference suitable for students, practicing engineers, and researchers in sciences and engineering.
Book Synopsis Restricted Kalman Filtering by : Adrian Pizzinga
Download or read book Restricted Kalman Filtering written by Adrian Pizzinga and published by Springer Science & Business Media. This book was released on 2012-07-25 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter, aiming to make the book self-contained and to give a quick reference to the reader (notation and terminology). The prerequisites would be a contact with time series analysis in the level of Hamilton (1994) or Brockwell & Davis (2002) and also with linear state models and the Kalman filter – each of these books has a chapter entirely dedicated to the subject. The book is intended for graduate students, researchers and practitioners in statistics (specifically: time series analysis and econometrics).
Book Synopsis A Proposed Kalman Filter Algorithm for Estimation of Unmeasured Output Variables for an F100 Turbofan Engine by : Gurbux S. Alag
Download or read book A Proposed Kalman Filter Algorithm for Estimation of Unmeasured Output Variables for an F100 Turbofan Engine written by Gurbux S. Alag and published by . This book was released on 1990 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filtering by : Charles K. Chui
Download or read book Kalman Filtering written by Charles K. Chui and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition to making a number of minor corrections and updat ing the references, we have expanded the section on "real-time system identification" in Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al gorithms, they can also be applied to time-domain filtering, and it is hoped that splines and wavelets can be incorporated with Kalman filtering in the near future. College Station and Houston Charles K. Chui September 1990 Guanrong Chen Preface to the First Edition Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more use ful even for very complicated real-time applications.
Book Synopsis International Conference on Mechanism Science and Control Engineering (MSCE 2014) by :
Download or read book International Conference on Mechanism Science and Control Engineering (MSCE 2014) written by and published by DEStech Publications, Inc. This book was released on 2014-09-02 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of MSCE 2014 is to provide a platform for researchers, engineers, and academicians, as well as industrial professionals, to present their research results and development activities in mechanism science and control engineering. It provides opportunities for the delegates to exchange new ideas and application experiences, to establish business or research relations and to find global partners for future collaboration. MSCE2014 is conducted to all the researchers, engineers, industrial professionals and academicians, who are broadly welcomed to present their latest research results, academic developments or theory practice. Topics of interest include but are not limited to Mechanism theory and Application, Mechanical control and Automation Engineering, Mechanical Dynamics, Materials Processing and Control, Instruments and Vibration Control. It is of great pleasure to see the delegates exchanging ideas and establishing sound relationships on the conference.
Book Synopsis A Proposed Kalman Filter Algorithm for Estimation of Unmeasured Output Variables for an F100 Turbofan Engine by : Gurbux S. Alag
Download or read book A Proposed Kalman Filter Algorithm for Estimation of Unmeasured Output Variables for an F100 Turbofan Engine written by Gurbux S. Alag and published by . This book was released on 1990 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
