TY - GEN
T1 - The Application of Conjugate Gradient Method to Motion Control of Robotic Manipulators
AU - Sulaiman, Ibrahim M.
AU - Malik, Maulana
AU - Giyarti, Wed
AU - Mamat, Mustafa
AU - Ibrahim, Mohd Asrul Hery
AU - Ahmad, Muhammad Zaini
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Many industrial and engineering problems are transformed into optimization problems and solved using various numerical based methods. One of the frequently used method is the Steepest descent algorithm which converge to the solution in only one iteration, given the current point and provided the quadratic function is positive definite. However, this method is not suitable for large scale functions because of lack of gradient information and high computational cost. This study aims to suggest a new conjugate gradient algorithm for motion control of robotic manipulators and unconstrained optimization models. The convergence result of the new algorithm would be discussed under some suitable conditions. Computational simulations are carried out on the discrete-time kinematics equation of a two-joint planar robot manipulator to illustrates the efficiency of the algorithm. The algorithm was further extended to unconstrained optimization problems in addition to motion control of robotic manipulators. Preliminary results prove that the new algorithm is efficient compared to the existing CG algorithm. The comparisons are made using the set of 50 standard benchmark functions including number of iterations and CPU time.
AB - Many industrial and engineering problems are transformed into optimization problems and solved using various numerical based methods. One of the frequently used method is the Steepest descent algorithm which converge to the solution in only one iteration, given the current point and provided the quadratic function is positive definite. However, this method is not suitable for large scale functions because of lack of gradient information and high computational cost. This study aims to suggest a new conjugate gradient algorithm for motion control of robotic manipulators and unconstrained optimization models. The convergence result of the new algorithm would be discussed under some suitable conditions. Computational simulations are carried out on the discrete-time kinematics equation of a two-joint planar robot manipulator to illustrates the efficiency of the algorithm. The algorithm was further extended to unconstrained optimization problems in addition to motion control of robotic manipulators. Preliminary results prove that the new algorithm is efficient compared to the existing CG algorithm. The comparisons are made using the set of 50 standard benchmark functions including number of iterations and CPU time.
KW - Convergence analysis
KW - Line search techniques
KW - Robotic motion control
KW - Unconstrained optimization
UR - http://www.scopus.com/inward/record.url?scp=85131117628&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-2095-0_37
DO - 10.1007/978-981-19-2095-0_37
M3 - Conference contribution
AN - SCOPUS:85131117628
SN - 9789811920943
T3 - Lecture Notes in Electrical Engineering
SP - 435
EP - 445
BT - Enabling Industry 4.0 through Advances in Mechatronics - Selected Articles from iM3F 2021
A2 - Khairuddin, Ismail Mohd.
A2 - Abdullah, Muhammad Amirul
A2 - Ab. Nasir, Ahmad Fakhri
A2 - Mat Jizat, Jessnor Arif
A2 - Mohd. Razman, Mohd. Azraai
A2 - Abdul Ghani, Ahmad Shahrizan
A2 - Zakaria, Muhammad Aizzat
A2 - Mohd. Isa, Wan Hasbullah
A2 - Abdul Majeed, Anwar P.
PB - Springer Science and Business Media Deutschland GmbH
T2 - Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2021
Y2 - 20 September 2021 through 20 September 2021
ER -