The application of the improved particle swarm algorithm in parameter tuning of partition PID

摘要

The improvement of the dynamic performance of target tracking has put forward higher requirements of fast response and accuracy of servo system. To our actual servo system, the intelligent partition PID based on the control target is applied. However, to identify the parameters of partition PID algorithm, PSO has low accuracy and easily falls into local optimum. Therefore, this paper improves the PSO algorithm by introducing the selection, crossover, mutation operations of genetic algorithm into the PSO, and then proposes a fusion particle swarm optimization algorithm called FPSO. The results of standard test functions and the simulation model of servo system show that the FPSO has the advantages of faster optimization speed and parameter tuning effect compared with PSO, which verify the effectiveness of the FPSO algorithm.