PSO-based Parameter Tuning for a Two- Degree-of-Freedom IMC Scheme and Its Application to Paper Basis Weight Control

摘要

Basis weight is an important indicator for evaluating paper quality and a major factor directly affecting the economic benefits of enterprises.Focusing on the large time-delay,time-varying,and nonlinear characteristics of a basis weight control system,a two-degree-of-freedom(TDF)internal model control(IMC)method based on a particle swarm optimization(PSO)algorithm was proposed.The method took the integral of time multiplied by the absolute error(ITAE)as the objective function,and the PSO algorithm was used to optimize the time constant of the tuning IMC filter.The simulation results for the control system under the proposed TDF-IMC method based on the PSO algorithm demonstrate good set-point tracking performance,strong anti-interference capabilities,and good robustness properties.The application results revealed that the basis weight fluctuation range of the paper was±2 g/m2,which significantly improved both the control quality and the product quality.