TY - GEN
T1 - Performance analysis for a gantry crane system (GCS) using prioritybased fitness scheme in binary particle swarm optimization
AU - Jaafar, Hazriq Izzuan
AU - Mohamed, Zaharuddin
AU - Abidin, Amar Faiz Zainal
AU - Md Sani, Zamani
AU - Jamian, Jasrul Jamani
AU - Kassim, Anuar Mohamed
PY - 2014
Y1 - 2014
N2 - This paper presents development of an optimal PID and PD controllers for controlling the nonlinear Gantry Crane System (GCS). A new method of Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is developed to obtain optimal PID and PD parameters. The optimal parameters are tested on the control structure to examine system responses including trolley displacement and payload oscillation. The dynamic model of GCS is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of the system in terms of settling time, steady state error and overshoot. The result not only confirmed the successes of using new method for GCS, but also shows the new method performs more efficiently compared to the continuous PSO. This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the desired position with low payload oscillation.
AB - This paper presents development of an optimal PID and PD controllers for controlling the nonlinear Gantry Crane System (GCS). A new method of Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is developed to obtain optimal PID and PD parameters. The optimal parameters are tested on the control structure to examine system responses including trolley displacement and payload oscillation. The dynamic model of GCS is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of the system in terms of settling time, steady state error and overshoot. The result not only confirmed the successes of using new method for GCS, but also shows the new method performs more efficiently compared to the continuous PSO. This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the desired position with low payload oscillation.
KW - Binary particle swarm optimization
KW - Computational intelligence
KW - Gantry crane system
KW - Lagragian method
KW - PID
UR - https://www.scopus.com/pages/publications/84896861961
U2 - 10.4028/www.scientific.net/AMR.903.285
DO - 10.4028/www.scientific.net/AMR.903.285
M3 - Conference contribution
AN - SCOPUS:84896861961
SN - 9783038350200
T3 - Advanced Materials Research
SP - 285
EP - 290
BT - Manufacturing Engineering
T2 - 1st International Manufacturing Engineering Conference, iMEC 2013
Y2 - 1 July 2013 through 3 July 2013
ER -