摘要
本文以辽宁锦州六陆实业股份公司年产3万吨二氧化碳精制回收工程为实例,根据该工程的设计要求和现场的实际情况,以降低项目成本、保证功能为出发点,在参考国内外现今流行的组态软件基础之上,设计开发了针对该化工生产过程的计算机监控系统。该监控系统具有良好的人机界面、简单方便的操作和易扩展性,同时,它也具有较好的可靠性和稳定性,不仪能够直观、形象地反映生产现场的实际工况,而且也为该化工生产过程安全可靠稳定连续的运行提供了有力的支持。
此外,本文也针对生产现场一些工艺参数,特别是温度参数采用常规的PID控制效果不好,并且参数整定麻烦这一问题,给出了一种解决办法。该方法实际上是根据常规PID离散化算式,借鉴了预测控制的思想,利用人工神经网络的非线性逼近能力和学习记忆能力,设计了一种神经网络的PID控制器及其改进的基于输出多步预测的神经网络PID控制器,通过仿真试验证明它们是可行的和有效的,能够较好地解决类似于温度这类响应较慢的对象的控制问题,对非线性、时变对象具有较强的适应性,并且其参数整定简单,方便用于在线实时控制。
The paper discusses a computer monitoring system for a thirty thousand ton CO2 refinedly retrieving project of Jinzhou Liulu Industry joint-stock company. According to the designing requirements and actual surroundings, the author designs a reliable and low cost system based on domestic and international popular configuration software. The monitoring system has not only friendly HMI which is convenient to operate but also good stability and expansibility. It can reflect the real-time situation of the production vividly so that it provides a strong support for the successive running of the chemical production safely and reliably.
In addition, the traditional PID controller for some parameter, specially is temperature parameter, has dissatisfactory results and the parameters are hard to tune. To improve the statues, the author proposes a method to solve the problem effectively. Actually this method use the idea of predictive control for reference and its improved one based on neural network PID controller which applies the non-linearly approaching ability and memorizing ability of neural network to traditional PID discrete equation. The simulation test proves the design's feasibility and validity. It is convenient to use on the real time control of online and better than the traditional one on the aspects of parameter tuning, adaptability of actual production and solve the control problem of slow response plant which is like temperature parameter.
引文
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