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ANN Approach for State Estimation of Hybrid Systems and Its Experimental Validation
Joint Authors
Vellayikot, Shijoh
Vaidyan, M. V.
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-05
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
A novel artificial neural network based state estimator has been proposed to ensure the robustness in the state estimation of autonomous switching hybrid systems under various uncertainties.
Taking the autonomous switching three-tank system as benchmark hybrid model working under various additive and multiplicative uncertainties such as process noise, measurement error, process–model parameter variation, initial state mismatch, and hand valve faults, real-time performance evaluation by the comparison of it with other state estimators such as extended Kalman filter and unscented Kalman Filter was carried out.
The experimental results reported with the proposed approach show considerable improvement in the robustness in performance under the considered uncertainties.
American Psychological Association (APA)
Vellayikot, Shijoh& Vaidyan, M. V.. 2015. ANN Approach for State Estimation of Hybrid Systems and Its Experimental Validation. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073672
Modern Language Association (MLA)
Vellayikot, Shijoh& Vaidyan, M. V.. ANN Approach for State Estimation of Hybrid Systems and Its Experimental Validation. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1073672
American Medical Association (AMA)
Vellayikot, Shijoh& Vaidyan, M. V.. ANN Approach for State Estimation of Hybrid Systems and Its Experimental Validation. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073672
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073672