Abstract
This research proposed a high-order disturbance estimation using Kalman filter for precise reaction-torque control. The proposed method is able to realize the reaction torque control system by using the proportional-derivative controller. It is confirmed that the proposed proportional-derivative controller of reaction torque can improve control system performance without enhancing the noise effect. This is because estimated variables by the proposed Kalman filter based high order disturbance/reaction torque observer are utilized in the PD controller. The observer can estimate the disturbance/external torque and its time derivative with lower noise level than the conventional disturbance observers (DOBs) or reaction torque observers (RTOBs). Experimental results validate the proposed method.
Original language | English |
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Title of host publication | 2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 79-84 |
Number of pages | 6 |
ISBN (Electronic) | 9781479984640 |
DOIs | |
Publication status | Published - 2016 Jun 20 |
Event | 14th IEEE International Workshop on Advanced Motion Control, AMC 2016 - Auckland, New Zealand Duration: 2016 Apr 22 → 2016 Apr 24 |
Other
Other | 14th IEEE International Workshop on Advanced Motion Control, AMC 2016 |
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Country | New Zealand |
City | Auckland |
Period | 16/4/22 → 16/4/24 |
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ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
High-order disturbance estimation using Kalman filter for precise reaction-torque control. / Nagatsu, Yuki; Katsura, Seiichiro.
2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 79-84 7496331.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - High-order disturbance estimation using Kalman filter for precise reaction-torque control
AU - Nagatsu, Yuki
AU - Katsura, Seiichiro
PY - 2016/6/20
Y1 - 2016/6/20
N2 - This research proposed a high-order disturbance estimation using Kalman filter for precise reaction-torque control. The proposed method is able to realize the reaction torque control system by using the proportional-derivative controller. It is confirmed that the proposed proportional-derivative controller of reaction torque can improve control system performance without enhancing the noise effect. This is because estimated variables by the proposed Kalman filter based high order disturbance/reaction torque observer are utilized in the PD controller. The observer can estimate the disturbance/external torque and its time derivative with lower noise level than the conventional disturbance observers (DOBs) or reaction torque observers (RTOBs). Experimental results validate the proposed method.
AB - This research proposed a high-order disturbance estimation using Kalman filter for precise reaction-torque control. The proposed method is able to realize the reaction torque control system by using the proportional-derivative controller. It is confirmed that the proposed proportional-derivative controller of reaction torque can improve control system performance without enhancing the noise effect. This is because estimated variables by the proposed Kalman filter based high order disturbance/reaction torque observer are utilized in the PD controller. The observer can estimate the disturbance/external torque and its time derivative with lower noise level than the conventional disturbance observers (DOBs) or reaction torque observers (RTOBs). Experimental results validate the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=84982792263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982792263&partnerID=8YFLogxK
U2 - 10.1109/AMC.2016.7496331
DO - 10.1109/AMC.2016.7496331
M3 - Conference contribution
AN - SCOPUS:84982792263
SP - 79
EP - 84
BT - 2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -