Virtual instrument parameter calibration with particle swarm optimization
Yu Peng, Peng Xiyuan, Shengwei Meng · 2004
In virtual instrument designs and applications, lots of functional parameters can be set through software methods. Currently, most parameter settings methods are lightly linked with the knowledge of instruments and basic principles related to specific applications. However, it is difficult for some end users to deal with those advanced operations. By adopting the particle swarm optimization (PSO) algorithm, the adaptive set and calibration of instrument parameters can be achieved by software with computational intelligence. Experiments and applications showed that the adaptive parameter calibration method based on the PSO can enhance the effectiveness of debugging and maintenance of virtual instrument and test system.