粗煤泥分选系统控制方法及应用研究

发布时间：2018-04-27 11:22

本文选题：粗煤泥分选 + 无模型自适应控制　；参考：《中国矿业大学》2017年硕士论文

【摘要】：干扰床分选机(TBS)是利用沉降原理实现粗煤泥分选的一种新型设备,因其结构简单、控制精确及分选效果优良等特点被广泛应用于粗煤泥分选。TBS干扰床层密度的变化直接影响TBS的分选效果和精煤产品的质量。因此,对TBS干扰床层密度的控制尤为重要。TBS粗煤泥分选系统是一个高度非线性、时变、大滞后、强耦合的不确定系统,难以建立被控对象的精确数学模型,而传统的控制方法在复杂系统的控制速度和控制精度方面也渐显不足。本文研究了无模型自适应控制,在此基础上提出一种基于粒子群优化算法的改进无模型自适应控制方法,并将其应用于TBS粗煤泥分选系统。论文介绍了TBS分选工艺,分析了TBS分选过程的主要影响因素。给出了以西门子S7-200系列PLC为控制核心的系统整体控制方案。在方案设计中,基于MFAC算法的理论基础,对系统的MFAC控制器模块进行开发设计,并从跟踪性能、适应能力和抗干扰能力等方面与传统的PID和模糊PID控制方法进行了仿真对比。针对标准MFAC存在的大滞后问题,设计了抗滞后的MFAC(ADMFAC)控制器,并通过与MFAC的仿真对比,验证了ADMFAC在控制性能上的提升。步长序列k?和权重因子?是MFAC的两个主要可调参数,为了进一步完善ADMFAC的控制性能,本文采用粒子群优化算法(PSO)对ADMFAC的参数进行寻优整定,得到步长序列k?和权重因子?的最优组合值,从而设计出基于粒子群优化算法的抗滞后无模型自适应控制器(PSO-ADMFAC)。基于硬件基础,依据控制策略,搭建TBS粗煤泥分选系统的仿真实验平台。利用STEP7 Micro WIN实现PLC的硬件组态和相关程序编写;在MATLAB中完成控制算法的程序编写;基于Kingview设计上位机监控界面;采用DOPSoft设计触摸屏HMI界面,作为就地监测站;通过OPC技术有效地将组态软件与控制算法进行集成,实现了上位机组态软件与MATLAB之间的数据交换。本文对TBS粗煤泥分选系统的控制方法进行设计和改进,在提高产品质量,减少资源浪费,保护环境等方面具有一定的理论意义和应用价值。
[Abstract]:Interference bed separator (TBS) is a new type of equipment for separating coarse coal slime by means of settlement principle, because of its simple structure. The characteristics of precise control and good separation effect are widely used in coarse coal slime separation. TBS-interference bed density directly affects the separation effect of TBS and the quality of clean coal products. Therefore, it is particularly important to control the density of TBS interference bed. The coarse coal slime sorting system is a highly nonlinear, time-varying, time-varying, time-delay and strong coupling uncertain system. It is difficult to establish an accurate mathematical model of the controlled object. However, the traditional control method is not enough in the control speed and precision of complex system. In this paper, model-free adaptive control is studied, and an improved model-free adaptive control method based on particle swarm optimization algorithm is proposed and applied to TBS coarse slime sorting system. This paper introduces the TBS separation process and analyzes the main influencing factors of the TBS separation process. The overall control scheme based on Siemens S7-200 series PLC is presented. In the scheme design, based on the theoretical basis of MFAC algorithm, the MFAC controller module of the system is developed and designed, and compared with the traditional PID and fuzzy PID control methods from the aspects of tracking performance, adaptability and anti-jamming ability. In order to solve the problem of large lag in standard MFAC, an anti-lag ADMFAC controller is designed, and compared with MFAC, the improvement of control performance of ADMFAC is verified. Step length sequence k? And the weight factor? In order to further improve the control performance of MFAC, the particle swarm optimization (PSO) algorithm is used to optimize the parameters of ADMFAC. And the weight factor? The PSO-ADMFAC controller based on particle swarm optimization algorithm is designed for anti-delay model-free adaptive controller. Based on hardware and control strategy, the simulation experiment platform of TBS coarse coal slime separation system is built. The hardware configuration and related program of PLC are realized by STEP7 Micro WIN, the control algorithm is programmed in MATLAB, the monitor interface of host computer is designed based on Kingview, the HMI interface of touch screen is designed by DOPSoft, and the local monitoring station is designed. The configuration software and control algorithm are effectively integrated by OPC technology, and the data exchange between configuration software and MATLAB is realized. This paper designs and improves the control method of TBS coarse slime separation system, which has certain theoretical significance and application value in improving product quality, reducing waste of resources, protecting environment and so on.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD94;TP273

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