TY - GEN
T1 - Identification of lonely barycentric parameters of parallel kinematics mechanism with rank-deficient observation matrix
AU - Rosyid, Abdur
AU - El-Khasawneh, Bashar
AU - Alazzam, Anas
N1 - Funding Information:
ACKNOWLEDGMENT This research was partially supported University Internal Research Fund.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/2
Y1 - 2018/4/2
N2 - In parameter identification of dynamic system presented as linear system, the observation matrix is commonly rank-deficient. The widely used approach is transforming the system to new, full-rank system and accordingly estimating the dynamic parameters as linear combinations. The treatment becomes relatively more difficult when dealing with parallel kinematics mechanism due to lengthy expression of their inverse dynamics and hence difficulty to transform it to dynamic identification model manually. This paper presents a new approach which does not require such transformation and is able to present the estimates as lonely parameters. This is conducted by iteratively minimizing the residual instead of solving the estimates by using linear least squares technique. The transformation from the inverse dynamics model to the dynamic identification model is accomplished by symbolic computation.
AB - In parameter identification of dynamic system presented as linear system, the observation matrix is commonly rank-deficient. The widely used approach is transforming the system to new, full-rank system and accordingly estimating the dynamic parameters as linear combinations. The treatment becomes relatively more difficult when dealing with parallel kinematics mechanism due to lengthy expression of their inverse dynamics and hence difficulty to transform it to dynamic identification model manually. This paper presents a new approach which does not require such transformation and is able to present the estimates as lonely parameters. This is conducted by iteratively minimizing the residual instead of solving the estimates by using linear least squares technique. The transformation from the inverse dynamics model to the dynamic identification model is accomplished by symbolic computation.
KW - Barycentric parameters
KW - Dynamic parameter identification
KW - Parallel kinematics
KW - Rank-deficient observation matrix
UR - http://www.scopus.com/inward/record.url?scp=85051021274&partnerID=8YFLogxK
U2 - 10.1109/ISMA.2018.8330120
DO - 10.1109/ISMA.2018.8330120
M3 - Conference contribution
AN - SCOPUS:85051021274
T3 - 11th International Symposium on Mechatronics and its Applications, ISMA 2018
SP - 1
EP - 6
BT - 11th International Symposium on Mechatronics and its Applications, ISMA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Symposium on Mechatronics and its Applications, ISMA 2018
Y2 - 4 March 2018 through 6 March 2018
ER -