TY - GEN
T1 - Parameter optimization for NC machine tool based on golden section search driven PSO
AU - Oh, Sehoon
AU - Hori, Yoichi
PY - 2007
Y1 - 2007
N2 - We have proposed a modified PSO[1]; GPSO (Golden-section-search driven Particle Swarm Optimization) which updates only one particle in a generation based on a strategy: golden section search and steepest descent method. It was proved to be effect in various optimization problem. In this paper, first, this GPSO is revised to make clear its effectiveness. Then, the GPSO is utilized to optimize control parameters in NC machine tools. Parameters which are said to be difficult to optimize in a NC machine tool, is chosen and the roles of those parameters are scrutinized. Based on those scrutiny, fitness are defined for parameters. In order to verify optimization performance of the algorithms (GA, PSO, GPSO), a hardware-in-the-loop system with a NC machine tool is set up and on-line optimization experiments are conducted using the system. In experiments, the GPSO shows better optimization performance.
AB - We have proposed a modified PSO[1]; GPSO (Golden-section-search driven Particle Swarm Optimization) which updates only one particle in a generation based on a strategy: golden section search and steepest descent method. It was proved to be effect in various optimization problem. In this paper, first, this GPSO is revised to make clear its effectiveness. Then, the GPSO is utilized to optimize control parameters in NC machine tools. Parameters which are said to be difficult to optimize in a NC machine tool, is chosen and the roles of those parameters are scrutinized. Based on those scrutiny, fitness are defined for parameters. In order to verify optimization performance of the algorithms (GA, PSO, GPSO), a hardware-in-the-loop system with a NC machine tool is set up and on-line optimization experiments are conducted using the system. In experiments, the GPSO shows better optimization performance.
KW - Golden section search
KW - Golden section search driven particle swarm optimization (GPSO)
KW - Hardware-in-the-loop system
KW - Parameter tuning
KW - Precision motion control
KW - Steepest descent method
UR - https://www.scopus.com/pages/publications/50049133726
U2 - 10.1109/ISIE.2007.4375113
DO - 10.1109/ISIE.2007.4375113
M3 - Conference contribution
AN - SCOPUS:50049133726
SN - 1424407559
SN - 9781424407552
T3 - IEEE International Symposium on Industrial Electronics
SP - 3114
EP - 3119
BT - 2007 IEEE International Symposium on Industrial Electronics, ISIE 2007, Proceedings
T2 - 2007 IEEE International Symposium on Industrial Electronics, ISIE 2007
Y2 - 4 June 2007 through 7 June 2007
ER -