An adaptive three-stage information filter of simultaneous state and unknown disturbance estimation in linear time-varying systems
An adaptive three-stage information filter is proposed to estimate unknown disturbances in discrete linear time-varying systems. By modeling unknown dynamic faults and observation abnormalities as parameter changes, the proposed filter is designed as three detachable filters, including the main info...
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| Veröffentlicht in: | GPS solutions 2023, Vol.27 (1), p.27, Article 27 |
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| creator | He, Kaifei Liu, Huimin |
| description | An adaptive three-stage information filter is proposed to estimate unknown disturbances in discrete linear time-varying systems. By modeling unknown dynamic faults and observation abnormalities as parameter changes, the proposed filter is designed as three detachable filters, including the main information filter and two compensation filters. A rule for detecting the unknown dynamic and observation disturbances is presented based on a generalized likelihood ratio test. Under the classical uniform complete observability–controllability conditions and a persistent excitation condition, the exponential stability of the adaptive three-stage information filter is rigorously analyzed. The numerical examples are presented to illustrate the performance of the proposed algorithm. The results show that the proposed filter is a better trade-off between algorithm simplicity and efficiency; after the dynamic and observation disturbances change, the disturbance compensation converges after a transient. |
| doi_str_mv | 10.1007/s10291-022-01350-z |
| format | Article |
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The results show that the proposed filter is a better trade-off between algorithm simplicity and efficiency; after the dynamic and observation disturbances change, the disturbance compensation converges after a transient.</description><identifier>ISSN: 1080-5370</identifier><identifier>EISSN: 1521-1886</identifier><identifier>DOI: 10.1007/s10291-022-01350-z</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Abnormalities ; Adaptation ; Adaptive systems ; Algorithms ; Atmospheric Sciences ; Automotive Engineering ; Bias ; Compensation ; Design ; Disturbances ; Earth and Environmental Science ; Earth Sciences ; Electrical Engineering ; Estimates ; Fault diagnosis ; Fault lines ; Filters ; Geophysics/Geodesy ; Laboratories ; Likelihood ratio ; Observability (systems) ; Original Article ; Parameter estimation ; Space Exploration and Astronautics ; Space Sciences (including Extraterrestrial Physics ; Stability analysis ; Stochastic models ; Time varying control systems</subject><ispartof>GPS solutions, 2023, Vol.27 (1), p.27, Article 27</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. 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The results show that the proposed filter is a better trade-off between algorithm simplicity and efficiency; after the dynamic and observation disturbances change, the disturbance compensation converges after a transient.</description><subject>Abnormalities</subject><subject>Adaptation</subject><subject>Adaptive systems</subject><subject>Algorithms</subject><subject>Atmospheric Sciences</subject><subject>Automotive Engineering</subject><subject>Bias</subject><subject>Compensation</subject><subject>Design</subject><subject>Disturbances</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Electrical Engineering</subject><subject>Estimates</subject><subject>Fault diagnosis</subject><subject>Fault lines</subject><subject>Filters</subject><subject>Geophysics/Geodesy</subject><subject>Laboratories</subject><subject>Likelihood ratio</subject><subject>Observability (systems)</subject><subject>Original Article</subject><subject>Parameter estimation</subject><subject>Space Exploration and Astronautics</subject><subject>Space Sciences (including Extraterrestrial Physics</subject><subject>Stability analysis</subject><subject>Stochastic models</subject><subject>Time varying control systems</subject><issn>1080-5370</issn><issn>1521-1886</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kE1LAzEQhhdRsFb_gKeA5-jko7vZYyl-QcGLnkN2d1JT22xNspV69JcbbcGbpxmG531n5i2KSwbXDKC6iQx4zShwToGJCdDPo2LEJpxRplR5nHtQQCeigtPiLMYlAIe6lqPia-qJ6cwmuS2S9BoQaUxmgcR524e1Sa73xLpVwkB6S6JbD6tkPPZDJBlMSIzvyODffP_hSediGkJjfIsEY3IHvfNk5TyaQPII6daEnfMLEncx4TqeFyfWrCJeHOq4eLm7fZ490PnT_eNsOqetYHWiqBpZCtYoJhV0HW9QQWO71pRQWawaLlsUQtWc2bJltehk3YKREqBUtbKNGBdXe99N6N-HfJ5e9kPweaXmlYRKTqqyyhTfU23oYwxo9SbkP8JOM9A_Wet91jpnrX-z1p9ZJPaimGG_wPBn_Y_qG2enhac</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>He, Kaifei</creator><creator>Liu, Huimin</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>2023</creationdate><title>An adaptive three-stage information filter of simultaneous state and unknown disturbance estimation in linear time-varying systems</title><author>He, Kaifei ; 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By modeling unknown dynamic faults and observation abnormalities as parameter changes, the proposed filter is designed as three detachable filters, including the main information filter and two compensation filters. A rule for detecting the unknown dynamic and observation disturbances is presented based on a generalized likelihood ratio test. Under the classical uniform complete observability–controllability conditions and a persistent excitation condition, the exponential stability of the adaptive three-stage information filter is rigorously analyzed. The numerical examples are presented to illustrate the performance of the proposed algorithm. 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| ispartof | GPS solutions, 2023, Vol.27 (1), p.27, Article 27 |
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| subjects | Abnormalities Adaptation Adaptive systems Algorithms Atmospheric Sciences Automotive Engineering Bias Compensation Design Disturbances Earth and Environmental Science Earth Sciences Electrical Engineering Estimates Fault diagnosis Fault lines Filters Geophysics/Geodesy Laboratories Likelihood ratio Observability (systems) Original Article Parameter estimation Space Exploration and Astronautics Space Sciences (including Extraterrestrial Physics Stability analysis Stochastic models Time varying control systems |
| title | An adaptive three-stage information filter of simultaneous state and unknown disturbance estimation in linear time-varying systems |
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