基于改进蚁群优化算法的中高速长网纸机速度链的控制

Speed Chain Control of Medium and High Speed Fourdrinier Paper Machine Based on Improved ACO Algorithm

关键词:  中高速长网纸机  速度链控制  改进蚁群优化算法  PID参数优化

Key Words:medium and high speed fourdrinier paper machine  speed chain control  improved ant colony algorithm  PID parameter optimization

摘要:对中高速长网纸机而言，确保速度链控制满足工艺要求对纸机正常运行有着重要意义。目前，纸机速度链控制多采用常规PID控制，但中高速长网纸机由于自身传动点多、车速快，故对闭环系统的响应速度和控制精度要求高，常规PID参数整定方法难以满足上述控制要求。蚁群优化算法（ACO）是一种适合多目标寻优的全局搜索算法，但传统蚁群算法易陷入局部最优及搜索较慢的问题，对此，本课题将信息素因子（α）和启发式因子（ ）按一定比例关系随迭代进行变化，提出一种改进蚁群优化算法，并将其应用于速度链PID控制器参数整定中。仿真结果表明，与常规PID控制相比，基于改进的蚁群优化算法PID控制系统响应速度更快、超调更小、抗干扰能力更好、鲁棒性更强。应用结果表明，该控制系统可保持纸机各部分速度长期稳定。

Abstract:For medium and high speed fourdrinier paper machine, ensuring the speed chain control to meet the process requirements is of great significance for the normal operation. At present, the paper machine speed chain control mostly adopts conventional PID control. However the medium and high speed fourdrinier paper machine requires higher response speed of the closed-loop system and control precision due to it has multi driving points and high speed, so the conventional PID parameter tuning method is difficult to meet the above control requirements. Ant colony algorithm (ACO) is a kind of suitable for multi-objective optimization of the global search algorithm, in view of the traditional ant colony algorithm is easy to fall into local optimum and slower search problems, this article will change pheromone factor (α) and heuristic factor (β) according to certain ratio relations with iteration, an improved ant colony algorithm was prepared, and applied to the speed chain of PID control parameters setting. Simulation results showed that, compared with conventional PID control, the improved ant colony algorithm based PID control system had higher response speed, smaller overshoot, better anti-interference ability and stronger robustness. Application results showed that the speed of each part of the paper machine was stable for a long period.