摘要
生物氧化预处理过程中氧化槽pH值是影响细菌活性的关键因素之一,而pH值输出形态分布不符合高斯分布,使传统的均值和方差难以描述输出pH值分布,本文提出一种对矿浆输出pH的概率密度函数(PDF)统计信息控制方法。首先,采用B样条逼近矿浆输出pH值的PDF统计信息;其次,针对权值向量之间的关系,利用动态神经网络(DNN)建立控制输入和权值向量之间的非线性动态模型,基于建立pH的PDF统计信息权值模型,设计滑模变结构控制器,通过构造Lyapunov函数进行稳定性分析;最后,实现输出PDF统计信息对目标PDF统计信息的跟踪。仿真结果验证了所提方法的有效性,为生物氧化预处理过程提供了新方法。
pH value of oxidation tank is one of the key factors affecting activity of bacteria in pretreatment process of biological oxidation.However,the pH value output morphology distribution does not conform to the Gaussian distribution,which makes the traditional mean and variance difficult to describe the output pH value distribution.A control method of probability density function(PDF)statistics information for pH output of pulp is proposed.Firstly,B-spline is used to approximate PDF statisties information of pulp output pH value.Secondly,aiming at the relationship between weight vectors,dynamic neural networks(DNN)is used to establish nonlinear dynamic model between control input and weight vector.Based on the PDF statisties information weight model of pH,the variable structure controller of sliding membrane is designed.Stability analysis is carried out by constructing Lyapunov function.Finally,tracking of output PDF statisties information on target PDF statisties information is realized.Simulation results demonstrate the effectiveness of the proposed method,which provides a new method for biological oxidation pretreatment process.
作者
赵雅儒
高丙朋
ZHAO Yaru;GAO Bingpeng(School of Electrical Engineering,Xinjiang University,Urumqi 830017,China)
出处
《传感器与微系统》
CSCD
北大核心
2024年第8期56-59,63,共5页
Transducer and Microsystem Technologies
基金
新疆维吾尔自治区自然科学基金资助项目(2019D01C079)。
关键词
氧化预处理过程
pH随机分布
B样条模型
概率密度函数统计信息
动态神经网络
滑模控制
oxidation pretreatment process
pH random distribution
B-spline model
probability density function(PDF)statistics information
dynamic neural network(DNN)
sliding mode control