先进控制理论在水厂混凝投药控制中的应用

【作者】 刘军；

【导师】 张航；

【作者基本信息】 中南大学 ， 控制工程， 2008， 硕士

【摘要】 随着我国城市建设的快速发展,对城市供水的质量要求越来越高,水处理过程的自动控制是保证供水质量的关键,而难点主要集中在混凝投药过程的自动控制。目前国内众多水厂采用的混凝投药控制方式主要是基于流动电流的反馈投药控制和基于传统数学模型的前馈反馈投药控制,控制效果都不太理想,存在沉淀池出水浊度波动大,药剂浪费严重等问题,因此本文主要研究基于先进控制理论的混凝投药自动控制问题。主要研究内容如下:(1)针对流动电流仪检测混凝反应的不准确性,利用多传感器信息融合技术,提出了一种新的混凝反应过程检测方法。该方法通过采集影响混凝反应的2个主要因素(源水浊度、源水流量)修正流动电流值,实现混凝反应的准确检测,为投药系统的优化控制打下基础。(2)为提高控制效果,提出了一种用于水处理混凝投药控制的模糊控制器。它能根据混凝投药过程出水浊度的状态,自动选取控制规则集,每种控制规则集能根据修正后的流动电流的偏差和偏差变化率来确定具体的控制规则,以此来适应混凝过程环境状态的变化。(3)为提高控制器的自适应性,提出了一种用于水处理混凝投药控制的模糊神经网络控制模型。它结合模糊控制器对不确定性信息的模糊处理能力和神经网络对样本数据的学习能力,能自适应的处理混凝投药控制的各种复杂情况,为水厂混凝投药控制的自动化提供一条新的途径。更多还原

【Abstract】 With the rapid development of urban construction in our country, the requirement to the quality of urban water supply is increasing. Automatic control of water treatment process is the key of protection of water quality. The most difficult focuses on the auto control of coagulant process. However, either forward and feedback control or classical feedback control is currently used in coagulation dosing in many water treatment factories in our country. But the results of both controls are not very good. There are some questions of chemicals wastage and sediment output water qualities varieties. Therefore, the paper is mainly to research the automatic control in coagulant dosing based on advanced intelligent control theory .The main research achievements are as follows:(1) Aiming at Streaming Current Detector’s low accuracy of measuring coagulation process, an improved detection method using multi-sensor data fusion technology is developed in this paper. The method adopts two main factors that affecting coagulation reaction (influent turbidity and flow) to correct the value of Streaming Current. So it can detect coagulation process accurately, which lays the foundation for optimizing control in dosing process.(2) In order to improve control performance, the paper brings forward a piece of new fuzzy controller used in water treatment drug control. Firstly, controller can automatically chooses rules set basing on different state of effluent turbidity in the process of coagulation dosing. Secondly, according to the streaming current’s deviation and its rate of change, each rules set can give concrete control rule which is suitable to be used in different state of the environment.(3) In order to improve adaptability of controller, this paper introduces a control model of the fuzzy neural network. Combining fuzzy controller’s fuzzy reasoning ability with the neural network’s learning ability, it can adaptively handle all kinds of complex situations in auto control of dosing process. It provides new approaches for the auto control of coagulant dosing in the water factory.更多还原