Measurement of apple harvesting behavior applying estimation error reduction method from body-mounted inertial sensor by low pass filter

2019 ◽  
Vol 2019 (0) ◽  
pp. J23111P
Author(s):  
Satomi IMAI ◽  
Taku TAZAWA ◽  
Chikara NAGAI ◽  
Koichi SAGAWA

This paper implements unscented Kalman filter (UKF) for output voltage estimation of RC low pass filter (LPF) and high pass filter (HPF). At first, the state space model has been obtained using Kirchhoff’s current law (KCL). The performance of UKF has been compared with extended Kalman filter (EKF). The simulation results validate the superiority of UKF over EKF as the estimation error is smaller using UKF as compared to the EKF method. As the UKF uses unscented transform (UT) and EKF uses Taylor series expansion for linearization purpose, linearization error is smaller in UKF as compared to EKF method. Also, UKF implementation has the advantage that it does not require Jacobian computation of nonlinear system model.


2017 ◽  
Vol E100.C (10) ◽  
pp. 858-865 ◽  
Author(s):  
Yohei MORISHITA ◽  
Koichi MIZUNO ◽  
Junji SATO ◽  
Koji TAKINAMI ◽  
Kazuaki TAKAHASHI

2016 ◽  
Vol 15 (12) ◽  
pp. 2579-2586
Author(s):  
Adina Racasan ◽  
Calin Munteanu ◽  
Vasile Topa ◽  
Claudia Pacurar ◽  
Claudia Hebedean

Author(s):  
Nanan Chomnak ◽  
Siradanai Srisamranrungrueang ◽  
Natapong Wongprommoon
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document