基于ANFIS的轧钢加热炉炉温智能控制的研究

发布时间：2018-07-23 21:05

【摘要】：轧钢加热炉是钢铁生产过程中不可缺少的热工设备,它的功能是按生产节奏均匀加热钢坯,使钢坯表面温度及内部温度分布满足轧制要求。为了有效解决目前加热炉燃烧过程普遍存在的能耗高、氧化烧损严重、钢坯温度波动严重、温度控制精度差等问题,本文提出了加热炉燃烧过程的智能优化控制系统。针对具有双交叉限幅控制的轧钢加热炉系统,本文设计了一种基于自适应神经网络模糊推理系统(ANFIS)的炉温智能控制器,其与一种改进的双交叉限幅控制相结合组成加热炉温度流量串级控制系统,该系统克服了模糊控制规则建立的难点,增强了模糊控制的自适应能力,避免了传统神经网络容易陷入局部极小值的缺点,并在此基础上给出了ANFIS智能控制器具体的设计方法。文中建立了加热炉控制系统的数学模型,并在MATLAB/Simulink平台上进行了仿真实验,仿真结果表明系统具有良好的自适应能力和控制性能。
[Abstract]:Rolling furnace is an indispensable thermal equipment in the process of iron and steel production. Its function is to heat the billet uniformly according to the production rhythm, so that the surface temperature and internal temperature distribution of the billet can meet the rolling requirements. In order to effectively solve the problems of high energy consumption, serious oxidation loss, serious temperature fluctuation of billet and poor precision of temperature control, the intelligent optimal control system for combustion process of reheating furnace is put forward in this paper. In this paper, an intelligent controller of furnace temperature based on adaptive neural network fuzzy inference system (ANFIS) is designed for the reheating furnace system with double cross limiting control. It is combined with an improved double cross limiting control system to form the temperature and flow cascade control system of heating furnace. The system overcomes the difficulty of establishing fuzzy control rules and enhances the adaptive ability of fuzzy control. The shortcoming of traditional neural network is avoided that it is easy to fall into local minima. Based on this, the design method of ANFIS intelligent controller is given. The mathematical model of the heating furnace control system is established in this paper, and the simulation experiment is carried out on MATLAB/Simulink platform. The simulation results show that the system has good adaptive ability and control performance.
【学位授予单位】：辽宁科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TG307

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