摘要
高棒产线在高速轧制过程中,钢材温度控制的稳定性对最终产品性能具有决定性影响。针对高棒热区温控系统中动态响应慢、扰动影响大、测温精度有限的问题,提出了一种基于卡尔曼滤波、PID控制与粒子群优化(PSO)相结合的优化控制方法。首先,将钢材温度变化过程建模为二阶热惯性系统,并在输出端引入外部扰动与测量噪声,以模拟真实工况;其次,设计卡尔曼滤波器用于噪声滤除与状态估计,提高反馈精度;并在此基础上,通过PSO算法对PID控制器的比例、积分、微分参数进行全局优化,构建闭环控制系统,实现温度精准调节与干扰抑制。通过Simulink仿真验证,该控制结构有效降低了稳态误差与超调量,提高了系统对外部扰动的鲁棒性与响应速度,为高棒产线智能温控系统的优化控制提供了理论支持与工程参考。
The stability of temperature control in the high-speed rolling process of high-speed bar production lines is crucial to the final product quality.To address the issues of slow dynamic response,significant disturbance influence,and limited temperature measurement accuracy in the thermal control system of the high-bar hot zone,this paper proposes an optimized control strategy that integrates Kalman filtering,PID control,and Particle Swarm Optimization(PSO).Firstly,the thermal dynamics of the steel bar are modeled as a second-order thermal inertia system,incorporating external disturbances and measurement noise to simulate actual industrial conditions.Subsequently,a Kalman filter is designed to estimate the system states and mitigate measurement noise,thereby enhancing feedback accuracy.On this basis,PSO is employed to globally optimize the PID controller parameters(K p,K i,K d),aiming to achieve precise temperature regulation and disturbance rejection.Simulation results in Simulink demonstrate that the proposed control strategy effectively reduces steady-state error and overshoot,improves system robustness against external disturbances,and enhances response speed,providing theoretical support and engineering reference for the intelligent temperature control system of high-bar production lines.
作者
孙水孝
SUN Shuixiao(Hongxing Co.,Ltd.,Jiuquan Iron and Steel Co.,Jiayuguan 735100,China)
出处
《重型机械》
2025年第4期85-90,共6页
Heavy Machinery
