Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays
The optimal Kalman filtering problem is investigated for a class of discrete state delay stochastic systems with randomly multiple sensor delays. The phenomenon of measurement delay occurs in a random way and the delay rate for each sensor is described by a Bernoulli distributed random variable with...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/716716 |
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| _version_ | 1849304716695044096 |
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| author | Dongyan Chen Long Xu |
| author_facet | Dongyan Chen Long Xu |
| author_sort | Dongyan Chen |
| collection | DOAJ |
| description | The optimal Kalman filtering problem is investigated for a class of discrete state delay stochastic systems with randomly multiple sensor delays. The phenomenon of measurement delay occurs in a random way and the delay rate for each sensor is described by a Bernoulli distributed random variable with known conditional probability. Based on the innovative analysis approach and recursive projection formula, a new linear optimal filter is designed such that, for the state delay and randomly multiple sensor delays with different delay rates, the filtering error is minimized in the sense of mean square and the filter gain is designed by solving the recursive matrix equation. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed filtering scheme. |
| format | Article |
| id | doaj-art-3ac4db07b32e42cda7e6c133bff9a868 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-3ac4db07b32e42cda7e6c133bff9a8682025-08-20T03:55:40ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/716716716716Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor DelaysDongyan Chen0Long Xu1Department of Applied Mathematics, Harbin University of Science and Technology, Harbin 150080, ChinaDepartment of Applied Mathematics, Harbin University of Science and Technology, Harbin 150080, ChinaThe optimal Kalman filtering problem is investigated for a class of discrete state delay stochastic systems with randomly multiple sensor delays. The phenomenon of measurement delay occurs in a random way and the delay rate for each sensor is described by a Bernoulli distributed random variable with known conditional probability. Based on the innovative analysis approach and recursive projection formula, a new linear optimal filter is designed such that, for the state delay and randomly multiple sensor delays with different delay rates, the filtering error is minimized in the sense of mean square and the filter gain is designed by solving the recursive matrix equation. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed filtering scheme.http://dx.doi.org/10.1155/2014/716716 |
| spellingShingle | Dongyan Chen Long Xu Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays Abstract and Applied Analysis |
| title | Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays |
| title_full | Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays |
| title_fullStr | Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays |
| title_full_unstemmed | Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays |
| title_short | Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays |
| title_sort | optimal kalman filtering for a class of state delay systems with randomly multiple sensor delays |
| url | http://dx.doi.org/10.1155/2014/716716 |
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