Yu Ying, Zeng Ruifeng, Xue Yuezhao, Zhao Xiaoguo
School of Mechanical and Electrical Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
Capital Engineering & Research Incorporation Limited, Beijing 100176, China.
Biomimetics (Basel). 2023 Mar 31;8(2):143. doi: 10.3390/biomimetics8020143.
Medium and heavy plates are important strategic materials, which are widely used in many fields, such as large ships, weapons and armor, large bridges, and super high-rise buildings. However, the traditional control technology cannot meet the high-precision control requirements of the roll gap of the thick plate mill, resulting in errors in the thickness of the medium and heavy plate, thereby reducing the quality of the product. In response to this problem, this paper takes the 5500 mm thick plate production line as the research background, and establishes the model of the rolling mill plate thickness automatic control system, using the Ziegler-Nichol response curve method (Z-N), particle swarm optimization (PSO) algorithm and linear weight particle swarm optimization (LWPSO) algorithm, respectively, optimizes the parameter setting of the PID controller of the system, and uses OPC UA communication technology to realize the online semi-physical simulation of Siemens S7-1500 series PLC (Siemens, Munich, Germany) and MATLAB R2018b (The MathWorks, Natick, Massachusetts, United States). Comparative studies show that when the same roll gap displacement step signal is given, the overshoot of the system response using the LWPSO algorithm is reduced by 14.26% and 10.18% compared with the Z-N algorithm and the PSO algorithm, and the peak time is advanced by 0.31 s and 0.05 s. The stabilization time is reduced by 3.71 s and 4.31 s, which effectively improves the control accuracy and speed of the system and has stronger anti-interference ability. It has certain engineering reference and application value.
中厚板是重要的战略物资,广泛应用于大型船舶、武器装备、大型桥梁和超高层建筑等诸多领域。然而,传统控制技术无法满足中厚板轧机辊缝的高精度控制要求,导致中厚板厚度出现误差,从而降低了产品质量。针对这一问题,本文以5500mm中厚板生产线为研究背景,建立了轧机板厚自动控制系统模型,分别采用齐格勒 - 尼科尔斯响应曲线法(Z - N)、粒子群优化(PSO)算法和线性加权粒子群优化(LWPSO)算法,对系统的PID控制器参数设置进行优化,并利用OPC UA通信技术实现了德国西门子公司S7 - 1500系列PLC(Siemens, Munich, Germany)与美国MathWorks公司MATLAB R2018b(The MathWorks, Natick, Massachusetts, United States)的在线半物理仿真。对比研究表明,在给定相同辊缝位移阶跃信号时,采用LWPSO算法的系统响应超调量相比Z - N算法和PSO算法分别降低了14.26%和10.18%,峰值时间提前了0.31s和0.05s,调节时间缩短了3.71s和4.31s,有效提高了系统的控制精度和速度,且具有更强的抗干扰能力。具有一定的工程参考和应用价值。