Identification of Non-Linear Dynamic systems applying Unscented H-Infinity Adaptive Filtering approach-Reference-Cited by-同舟云学术

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Identification of Non-Linear Dynamic systems applying Unscented H-Infinity Adaptive Filtering approach

Published:2022-11-11 Issue: Volume: Page:
ISSN:
Container-title:2022 2nd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON)
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Author:

Parija Sebamai¹,Dash P. K.²,Bisoi Ranjeeta²

Affiliation:

1. Siksha O Anusandhan Deemed to be University,Department of ECE,Bhubaneswar,Odisha,India

2. Siksha O Anusandhan Deemed to be University,Multidisciplinary Research Cell,Bhubaneswar,Odisha,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10009904/10009934/10010210.pdf?arnumber=10010210

Reference22 articles.

1. A simplified functional link net architecture for dynamic system identification with a UKF algorithm

2. Identification of non-linear dynamic systems using smooth variable structure filter

3. Nonlinear system identification based on Takagi-Sugeno fuzzy modeling and unscented Kalman filter

4. Wiener model-based system identification using moth flame optimised Kalman filter algorithm

5. Optimal Volterra-based nonlinear system identification using arithmetic optimization algorithm assisted with Kalman filter

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