Optimization Study of Short Stroke Control for Head and Tail of Hot Strip

摘要

For the present situation of traditional short stroke control (SSC) strip head and tail low width precision, some scholars use genetic algorithm (GA) and partlicle swarm optimisation (PSO) to optimise short stroke control model parameters, achieved a certain effect, but both have shortcomings. This article uses a new swarm intelligence optimisation method adaptive particle swarm genetic optimization (APSGO) algorithm to optimize hot strip during rough rolling short stroke control model parameters. The practical application at a domestic hot rolling plant show that short stroke control models after using adaptive particle swarm genetic optimization algorithm can control strip head and tail width and width steady portion within 1. 5 mm, shorten width tolerance length, strip head and tail cut loss tate reduces to less than 2%.