TY - GEN
T1 - Sensorless position control for a single DOF system
AU - Sharida, Ali
AU - Zidan, Obada
AU - Salamn, Majdi
AU - Hashlamon, Iyad
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/8
Y1 - 2018/6/8
N2 - This paper proposes a new method for sensorless position control for a mass which is connected with a servo motor through an elastic element, the system was assumed to have unknown parameter, so recursive least square (RLS) method was used to estimate these parameters depending on the reflected torque on the motor's shaft. Kalman filter (KF) is also used as an observer to estimate the position of the mass, depending on system dynamics and the measured states (angular displacement for motor's shaft and the armature current). Finally, PID controller was used to control the position of the mass depending on the estimated state (mass position). This method is very useful in applications that contain unmeasured states with unknown parameters. The system was implemented experimentally, and driven using Arduino Uno and L298, the current through the motor was measured using ACS712 module.
AB - This paper proposes a new method for sensorless position control for a mass which is connected with a servo motor through an elastic element, the system was assumed to have unknown parameter, so recursive least square (RLS) method was used to estimate these parameters depending on the reflected torque on the motor's shaft. Kalman filter (KF) is also used as an observer to estimate the position of the mass, depending on system dynamics and the measured states (angular displacement for motor's shaft and the armature current). Finally, PID controller was used to control the position of the mass depending on the estimated state (mass position). This method is very useful in applications that contain unmeasured states with unknown parameters. The system was implemented experimentally, and driven using Arduino Uno and L298, the current through the motor was measured using ACS712 module.
KW - elastic joints estimation
KW - Kalman filter
KW - parameters estimation
KW - state estimation
KW - state observation
UR - https://www.scopus.com/pages/publications/85049977891
U2 - 10.1109/ICASET.2018.8376937
DO - 10.1109/ICASET.2018.8376937
M3 - Conference contribution
AN - SCOPUS:85049977891
T3 - 2018 Advances in Science and Engineering Technology International Conferences, ASET 2018
SP - 1
EP - 6
BT - 2018 Advances in Science and Engineering Technology International Conferences, ASET 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Advances in Science and Engineering Technology International Conferences, ASET 2018
Y2 - 6 February 2018 through 5 April 2018
ER -