Adaptive High-Gain observer for joint state and parameter estimation: A comparison to Extended and Unscented Kalman filter

نویسندگان

  • Mauro H. Riva
  • Matthias Dagen
  • Tobias Ortmaier
چکیده

An adaptive High-Gain observer (AHG) as well as an Extended (EKF) and Unscented Kalman filter (UKF) are implemented for joint state and parameter estimation of a novel multi-axial electromagnetically actuated punch. These observers are compared in terms of convergence and response time to erroneous parameter and state initialization, as well as parameter modifications during operation. The AHG is further analyzed proposing an adaptive gain, which reduces the observer’s high sensibility with respect to noise. Simulation results show that AHG is more suitable compared to state-of-the-art EKF and UKF.

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تاریخ انتشار 2014