Karafan Journal

Karafan Journal

State Estimation of an Aviator Using Fuzzy Mixed Kalman/H-infinity Filter

Document Type : Original Article

Authors
1 Assistant Professor, Department of Mechanical Engineering, Faculty of Mofateh, Hamedan Branch, Technical and Vocational University (TVU), Hamedan, Iran.
2 Assistant Professor, Department of Mechanical Engineering, Faculty of Chamran, Guilan Branch, Technical and Vocational University (TVU), Guilan, Iran.
3 Faculty Member, Department of Mechanical Engineering, Faculty of Imam Khomeini, Behshahr Branch, Technical and Vocational University (TVU), Mazandaran, Iran.
Abstract
One of the most important problems in control engineering is state estimation of a dynamical system based on measured data corrupted by noises. One of the most popular algorithms used for state estimation of a linear discrete time dynamical system is mixed Kalman/H-infinity filter. The performance of this filter is essentially depending on how exact statistics of noise characteristics are available. It is also not guaranteed that the process noise covariance matrix, and the measurement noise covariance matrix remain constant with time in a highly non-stationary noise condition. Thus, it is imperative to continuously tune the mixed Kalman/H-infinity accounting for the changing noise conditions in order to get good filter performance. This paper presents an algorithm of fuzzy based mixed Kalman/H-infinity filter for dynamically tuning the process noise and measurement noise covariance matrices. Fuzzy system in every step of the process using the difference between the actual position and speed of the balloon and the amount of observed data by the observer, an adaptive produce and this factor is used to update covariance matrix values. In this way, the Fuzzy Mixed Kalman/H-infinity filter can be more accurately estimated system state variables and therefore always mean square estimation error is minimized.
Keywords
Subjects

References
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Volume 17, Issue 4 - Serial Number 50
Technical and Engineering
Winter 2021
Pages 61-80

  • Receive Date 01 September 2020
  • Revise Date 09 October 2020
  • Accept Date 15 January 2021