TY - GEN
T1 - Achieving Precision of a PID-Controlled Nonlinear Mechanism Through a High-Fidelity Simulation
AU - Ghorab, Bassem
AU - Rosyid, Abdur
AU - El-Khasawneh, Bashar
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This work involved finding optimal PID gains for a nonlinear coupled mechanism. A parallel mechanism was presented as an example of such a mechanism. An accurate simulation that corresponds to the physical system was created, and friction parameters were identified through an optimization using a genetic algorithm. Subsequently, another optimization was performed to find optimal PID gains. Remarkable error reductions of 81% and 92% were observed in the experiments after implementing the optimal PID gains on the physical system, without any fine-tuning.
AB - This work involved finding optimal PID gains for a nonlinear coupled mechanism. A parallel mechanism was presented as an example of such a mechanism. An accurate simulation that corresponds to the physical system was created, and friction parameters were identified through an optimization using a genetic algorithm. Subsequently, another optimization was performed to find optimal PID gains. Remarkable error reductions of 81% and 92% were observed in the experiments after implementing the optimal PID gains on the physical system, without any fine-tuning.
UR - http://www.scopus.com/inward/record.url?scp=85217405362&partnerID=8YFLogxK
U2 - 10.1109/ICARCV63323.2024.10821675
DO - 10.1109/ICARCV63323.2024.10821675
M3 - Conference contribution
AN - SCOPUS:85217405362
T3 - 2024 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
SP - 1172
EP - 1177
BT - 2024 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
Y2 - 12 December 2024 through 15 December 2024
ER -