Robust adaptive estimators for nonlinear systems

Hamimi Fadziati Binti Abdul Wahab, Reza Katebi

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

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.

Conference

ConferenceConference on Control and Fault-Tolerant Systems (SysTol), 2013
CountryFrance
CityNice
Period9/10/1311/10/13

Fingerprint

Kalman filters
Nonlinear systems
Statistics
Extended Kalman filters

Keywords

  • fault monitoring
  • nonlinear
  • adaptive nonlinear estimators
  • Kalman-based filter
  • state dependent Kalman filter
  • nonlinear systems

Cite this

Abdul Wahab, H. F. B., & Katebi, R. (2013). Robust adaptive estimators for nonlinear systems. 67-72 . Paper presented at Conference on Control and Fault-Tolerant Systems (SysTol), 2013 , Nice, France. https://doi.org/10.1109/SysTol.2013.6693823
Abdul Wahab, Hamimi Fadziati Binti ; Katebi, Reza. / Robust adaptive estimators for nonlinear systems. Paper presented at Conference on Control and Fault-Tolerant Systems (SysTol), 2013 , Nice, France.6 p.
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Abdul Wahab, HFB & Katebi, R 2013, 'Robust adaptive estimators for nonlinear systems' Paper presented at Conference on Control and Fault-Tolerant Systems (SysTol), 2013 , Nice, France, 9/10/13 - 11/10/13, pp. 67-72 . https://doi.org/10.1109/SysTol.2013.6693823

Robust adaptive estimators for nonlinear systems. / Abdul Wahab, Hamimi Fadziati Binti; Katebi, Reza.

2013. 67-72 Paper presented at Conference on Control and Fault-Tolerant Systems (SysTol), 2013 , Nice, France.

Research output: Contribution to conferencePaper

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T1 - Robust adaptive estimators for nonlinear systems

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N2 - 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.

AB - 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.

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KW - state dependent Kalman filter

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Abdul Wahab HFB, Katebi R. Robust adaptive estimators for nonlinear systems. 2013. Paper presented at Conference on Control and Fault-Tolerant Systems (SysTol), 2013 , Nice, France. https://doi.org/10.1109/SysTol.2013.6693823