Research on leachate pressure control system based on single neuron predictive control

Wenchen Wang, Huanli Liu, Zhenmin Wu, Junming Ye, Haipeng Zeng, Qinjun Li
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引用次数: 1

Abstract

∗Landfill leachate is a kind of highly concentrated waste water produced in landfill sites. The composition of landfill leachate is complicated due to the variety of garbage types, so it is necessary to treat the landfill leachate separately. In this paper, on the basis of fully understanding the technological process and system structure of landfill leachate treatment plant, the treatment process of landfill leachate is analyzed, and the control requirements and difficulties of the whole treatment process are analyzed. After analysis, a single neuron predictive control system is adopted to achieve accurate control of OCRO inlet pressure. Firstly, the OCRO inlet pressure is analyzed and the control block diagram of the closed loop is established. Through the historical data of the county’s landfill leachate treatment station, Simulink toolbox in MATLAB software was used to simulate the controlled object, and the transfer function of the controlled object was obtained. Then on the basis of the conventional PID control algorithm and the combination of neural network design single neuron PID intelligent control algorithm. Through MATLAB simulation, the results show that the controller based on the single neuron PID control algorithm has a slight overshoot and poor adaptive ability. Then, the single neuron PID is combined with the Smith controller to eliminate the big delay problem in the single neuron PID control process and improve the adaptive ability of the controller.
基于单神经元预测控制的渗滤液压力控制系统研究
*垃圾渗滤液是垃圾填埋场产生的一种高浓度废水。由于垃圾种类繁多,垃圾渗滤液成分复杂,有必要对垃圾渗滤液进行分类处理。本文在充分了解垃圾渗滤液处理厂工艺流程和系统结构的基础上,对垃圾渗滤液的处理工艺进行了分析,对整个处理过程的控制要求和难点进行了分析。经过分析,采用单神经元预测控制系统实现对OCRO入口压力的精确控制。首先对OCRO入口压力进行了分析,建立了闭环控制框图。通过该县垃圾渗滤液处理站的历史数据,利用MATLAB软件中的Simulink工具箱对被控对象进行仿真,得到被控对象的传递函数。然后在传统PID控制算法的基础上与神经网络相结合,设计出单神经元PID智能控制算法。通过MATLAB仿真,结果表明基于单神经元PID控制算法的控制器存在轻微超调和较差的自适应能力。然后,将单神经元PID与Smith控制器相结合,消除了单神经元PID控制过程中的大延迟问题,提高了控制器的自适应能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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