A multiple model-based sliding innovation filter

Mohammad A. AlShabi; S. Andrew Gadsden; Mamdouh El Haj Assad; Bassam Khuwaileh

doi:10.1117/12.2587343

12 April 2021 A multiple model-based sliding innovation filter

Mohammad A. AlShabi, S. Andrew Gadsden, Mamdouh El Haj Assad, Bassam Khuwaileh

Proceedings Volume 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX; 1175608 (2021) https://doi.org/10.1117/12.2587343
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

In this brief work, a novel filtering technique that combines the newly developed sliding innovation filter with a multiple model strategy is proposed. Introduced in 2020, the sliding innovation filter is a relatively new filter used for state and parameter estimation. Based on variable structure techniques, it shares the same principles with sliding mode observers. The filter is robust and stable under system modeling uncertainties. The proposed method multiple model-based sliding innovation filter is tested on an electrohydrostatic actuator (EHA) and the results are discussed.

Conference Presentation

Citation Download Citation

Mohammad A. AlShabi, S. Andrew Gadsden, Mamdouh El Haj Assad, and Bassam Khuwaileh "A multiple model-based sliding innovation filter", Proc. SPIE 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX, 1175608 (12 April 2021); https://doi.org/10.1117/12.2587343

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