Improved PSO algorithm based parameter optimization for fabric heat-setting machine

Based on the energy consumption model of heat-setting machine, an improved PSO (Particle Swarm Optimization) algorithm is proposed and used to optimize its key parameters. The improved algorithm has made three improvements: firstly, initializing the granule position by using the chaotic sequence; secondly, improving the particles´ search capability by using dynamic weight factor; thirdly, using “Re-screening Method” to avoid particles falling into the local optima. Finally the improved PSO and the standard PSO algorithms are applied in solving the heat-setting energy consumption model at the same time; their comparative simulation results show the improved PSO algorithm has better and faster optimal performances. Besides, the improved PSO algorithm is also used to solve the energy consumption models for four kinds of common fabrics under different heat setting condition separately, whose series results may provide some operation reference for heat setting process engineers and operators.