TY - GEN
T1 - Position control system based on inertia measurement unit sensor fusion with Kalman filter
AU - Ishikawa, Takahiro
AU - Nozaki, Takahiro
AU - Murakami, Toshiyuki
N1 - Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2016/6/20
Y1 - 2016/6/20
N2 - This paper proposes position control system based on measurements of an inertia measurement unit (IMU) sensor (composed of a gyro sensor and an acceleration sensor) attached on the tip position of a 2-link planar manipulator. To estimate joint angle from only one IMU sensor, velocity applied to end effector is required. However, it is difficult to measure accurate velocity from integration of measurements of the acceleration sensor due to noise, offset and drift error. Therefore, Kalman filter and sensor fusion with acceleration sensor and gyro sensor are introduced to estimate the velocity with high accuracy. In addition to that, Disturbance observer (DOB) is used in the position control system, and the estimated angular velocity information is utilized in DOB. To confirm the performance of proposed control system, 3 types of simulation of position control are conducted. Kalman filter can reduce the noise effect and position control is achieved by proposed control system.
AB - This paper proposes position control system based on measurements of an inertia measurement unit (IMU) sensor (composed of a gyro sensor and an acceleration sensor) attached on the tip position of a 2-link planar manipulator. To estimate joint angle from only one IMU sensor, velocity applied to end effector is required. However, it is difficult to measure accurate velocity from integration of measurements of the acceleration sensor due to noise, offset and drift error. Therefore, Kalman filter and sensor fusion with acceleration sensor and gyro sensor are introduced to estimate the velocity with high accuracy. In addition to that, Disturbance observer (DOB) is used in the position control system, and the estimated angular velocity information is utilized in DOB. To confirm the performance of proposed control system, 3 types of simulation of position control are conducted. Kalman filter can reduce the noise effect and position control is achieved by proposed control system.
UR - http://www.scopus.com/inward/record.url?scp=84980431388&partnerID=8YFLogxK
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U2 - 10.1109/AMC.2016.7496343
DO - 10.1109/AMC.2016.7496343
M3 - Conference contribution
AN - SCOPUS:84980431388
T3 - 2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016
SP - 153
EP - 159
BT - 2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Workshop on Advanced Motion Control, AMC 2016
Y2 - 22 April 2016 through 24 April 2016
ER -