Abdul Wahab, Hamimi Fadziati Binti and Katebi, Reza (2013) Robust adaptive estimators for nonlinear systems. In: Conference on Control and Fault-Tolerant Systems (SysTol), 2013, 2013-10-09 - 2013-10-11.
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This paper is concerned with the development of new adaptive nonlinear estimators which incorporate adaptive estimation techniques for system noise statistics with the robust technique. These include Extended H∞ Filter (EHF), State Dependent H∞ Filter (SDHF) and Unscented H∞ Filter (UHF). The new filters are aimed at compensating the nonlinear dynamics as well as the system modeling errors by adaptively estimating the noise statistics and unknown parameters. For comparison purposes, this adaptive technique has also being applied to the Kalman-based filter which include extended Kalman filter (EKF), state dependent Kalman filter (SDKF) and Unscented Kalman filter (UKF). The performance of the proposed estimators is demonstrated using a two-state Van der Pol oscillator as a simulation example.
|Item type:||Conference or Workshop Item (Paper)|
|Keywords:||fault monitoring, nonlinear, adaptive nonlinear estimators, Kalman-based filter, state dependent Kalman filter, nonlinear systems, Electrical engineering. Electronics Nuclear engineering, Control and Systems Engineering|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering|
|Depositing user:||Pure Administrator|
|Date Deposited:||17 Jun 2014 10:38|
|Last modified:||02 Apr 2017 22:32|