Sampling Jitter mitigation in latency-critical state-estimation applications using particle filters

Viktorio Semir El Hakim, Marco Jan Gerrit Bekooij

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    46 Downloads (Pure)

    Abstract

    State estimation algorithms, such as the Kalman filter, are applied for conditioning and sensor fusion in digital control loops. It is desirable that these algorithms can be executed on embedded multiprocessor systems. However this results in large worst-case execution times with a consequence that a large sampling period must selected, which degrades the estimation and control performance. In this paper, we propose a free-running state-estimation approach in which the next sample is taken as soon as the current iteration completes. The approach utilizes the particle filter algorithm to mitigate the effects of sampling jitter, introduced by the variation in the execution times of tasks. As a result of the reduced interval between subsequent sampling moments the estimation accuracy is improved. The delay introduced by the estimator in a control loop is reduced by enabling execution of the prediction step in parallel with other control tasks. We compare simulation results obtained for our approach with a Kalman filter based approach, by estimating the state of a DC motor. These results show that our approach minimizes the estimation error, as a result of sampling jitter, by up to a factor of 10. Additionally we show that the approach does not require precise knowledge of the distribution of the execution times of the tasks.
    Original languageEnglish
    Title of host publication2017 SICE International Symposium on Control Systems
    PublisherIEEE
    Number of pages8
    ISBN (Electronic)978-4-907764-54-8
    ISBN (Print)978-1-5090-5614-9
    Publication statusPublished - 3 Apr 2017
    Event2017 SICE International Symposium on Control Systems - Okayama, Japan
    Duration: 6 Mar 20179 Mar 2017

    Conference

    Conference2017 SICE International Symposium on Control Systems
    Abbreviated titleSICE ISCS 2017
    CountryJapan
    CityOkayama
    Period6/03/179/03/17

    Keywords

    • Sampling jitter, Particle filtering

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  • Cite this

    El Hakim, V. S., & Bekooij, M. J. G. (2017). Sampling Jitter mitigation in latency-critical state-estimation applications using particle filters. In 2017 SICE International Symposium on Control Systems IEEE.