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Dynamic soft sensor development based on Gaussian mixture regression for fermentation processes

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Chinese Journal of Chemical Engineering 2017年第1期25卷 116-122页

作者： Congli Mei Yong Su Guohai Liu yuhan ding Zhiling Liao School of Electrical and Information Engineering Jiangsu University Zhenjiang 212013 China

The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation ***,limitations of single regression models,for multiphase/multimode fermentation processes,may result in large prediction errors and complexity of the soft ***,a dynamic soft sensor based on Gaussian mixture regression(GMR) was proposed to overcome the *** structure parameters,the number of Gaussian components and the order of the model,are crucial to the soft sensor *** achieve a simple and effective soft sensor,an iterative strategy was proposed to optimize the two structure parameters *** the aim of comparisons,the proposed dynamic GMR soft sensor and the existing dynamic GPR soft sensor were both investigated to estimate biomass concentration in a Penicillin simulation process and an industrial Erythromycin fermentation *** show that the proposed dynamic GMR soft sensor has higher prediction accuracy and is more suitable for dynamic multiphase/multimode fermentation processes.

关键词： Dynamic modeling Process systems Instrumentation Gaussian mixture regression Fermentation processes

Development of Improved Inverse Compensator for Two-Dimensional Sensor

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Development of Improved Inverse Compensator for Two-Dimensio...

Wholly smoothing cutter orientations for five-axis NC machining based on cutter contact point mesh

第25届中国控制与决策会议

作者： yuhan ding Guohai Liu Xianzhong Dai School of Electrical & Information Engineering Jiangsu University Key Laboratory of Measurement and Control of CSE (School of Automation Southeast University) Ministry of Education Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Jiangsu University

ISBN: (纸本)9781467355339

In this paper, we developed an improved inverse compensator to ameliorate the dynamic performance of the two-dimensional sensor. The main feature of the improved compensator is the use of a special state observer, which is designed on the state-space model the two-dimensional sensor. As the state-space model can fully describe the complex sensor, the obtained compensator will be more effective in compensating the output of the sensor. Besides, the compensator uses an ANN （artificial neural network） to approximate the imprecisely known nonlinear function, which makes it more applicable for compensating real sensors.

关键词： Inverse Compensator State Space Equation Two-Dimensional Sensor

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Science China(Technological Sciences) 2010年第5期53卷 1294-1303页

作者： BI QingZhen,WANG yuhan,ZHU LiMin & ding Han State Key Laboratory of Mechanical System and Vibration,School of Mechanical Engineering,Shanghai Jiaotong University,Shanghai 200240,China 1. State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiaotong University Shanghai 200240 China

Cutting forces with respect to different cutter orientations are analyzed for five-axis NC machining of a ball-end cutter.A measure is then defined to quantify the effects of cutter orientation *** to the measure,a novel model and algorithm are proposed to wholly optimize cutter orientations based on a cutter contact(CC) point *** method has two *** is that the cutter orientation smoothnesses along the feed direction and pick-feed direction are both wholly *** other is that only the accessibility cones of mesh points are required to compute and the computation efficiency is *** advantages are shown by simulating the machining efficiency,the stability of feed velocities and the smoothness of cutting force.A computational example and a cutting experiment are finally given to illustrate the validity of the proposed method.

关键词： five-axis machining tool path accessibility cone cutter orientation

SVM combined Inversion Control Method in Microbial Fermentation

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SVM combined Inversion Control Method in Microbial Fermentat...

Application of Gauss Process Regression Modeling Based on NN-MIV for Marine Enzyme Fermentation Process

第32届中国控制与决策会议

作者： Chengfeng Wang yuhan ding Yi Li School of Electrical and Information Engineering Jiangsu University High-tech Key Laboratory of Agricultural Equipment and Intelligence of Jiangsu Province

Microbial fermentation productive process is a kind of high nonlinear system with *** key variables of these systems are difficult to measure,which influence the control and optimism of these systems *** realize the control of a microbial fermentation,we adopted right inversion method to linearize and decouple the original system and adopted left inversion method to obtain the directly immeasurable *** method combines the left inversion and right inversion to control a system,so it can be called the combined inversion control *** corresponding controller can be called combined inversion *** adopted support vector machine（SVM） together with several differentiators and an integrator to construct the above controller to overcome the problems caused by the severe nonlinear and uncertainty of the microbial fermentation,and an SVM combined inversion controller came into *** simulation results indicate that,the method presented in this paper can well implement the control of such systems as microbial fermentation with directly immeasurable variables.

关键词： Support vector machine combined inversion control microbial fermentation

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Application of Gauss Process Regression Modeling Based on NN...

第30届中国控制与决策会议

作者： Peisuo Yang yuhan ding Guohai Liu Congli Mei Xu Chen Hui Jiang School of Electrical and Information Engineering Jiangsu University

To overcome the problems of variable redundancy, long training time and low prediction accuracy in the soft sensing model for marine enzyme fermentation, a Gauss process regression（GPR） model based on NN-MIV is presented, which is named as GPR-NNMIV soft sensing model. Firstly, the NN-MIV variable selection method, combining neural network（NN） and mean impact value（MIV）, takes into account both the internal contribution rate and the external contribution rate to get the most suitable input variables with the highest contribution rate, and reduces the number of variables and simplifies soft sensing model. Secondly, based on the NN-MIV method, a new Gauss process regression model is proposed, which does not only give out the soft sensing results but also gives the corresponding uncertainty simultaneously. Results show that the proposed GPR-NNMIV soft sensing model has higher accuracy of results and small confidence intervals compared with single Gauss process model.

关键词： NN-MIV Gauss Process Regression Marine Enzyme Soft Sensing

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微生物燃料电池去除水中低含量头孢他啶研究

水处理技术 2021年第4期47卷 40-44页

作者：丁予涵胡翔北京化工大学化学工程学院北京100029

通过构建单室微生物燃料电池(MFC)体系,考察了不同进水头孢他啶(CAZ)含量在1个换水周期内对于MFC产电及去除污染物能力的影响。结果表明,CAZ的加入会显著影响MFC的产电性能,最大功率密度从595.2mW/m^(2)下降至201.3 mW/m^(2)。在进水CA... 详细信息

通过构建单室微生物燃料电池(MFC)体系,考察了不同进水头孢他啶(CAZ)含量在1个换水周期内对于MFC产电及去除污染物能力的影响。结果表明,CAZ的加入会显著影响MFC的产电性能,最大功率密度从595.2mW/m^(2)下降至201.3 mW/m^(2)。在进水CAZ的质量浓度为0.2 mg/L时,微生物具有最强的生物活性,COD、CAZ和氨氮的去除率分别达到92.9%、87.3%及61.8%。阳极微生物相扫描电镜结果显示,投加抗生素后优势菌种从球状菌变成了短杆菌。通过液相色谱-质谱对CAZ可能的降解产物及途径进行了初步推导,初期分解为m/z=535与m/z=79的中间产物,并继续分解为m/z=275、m/z=263以及m/z=102等更小的物质,最终生成H_(2)O及CO_(2)等小分子。

关键词：微生物燃料电池抗生素头孢他啶降解途径

红霉素发酵生化参量的神经网络逆系统软测量方法

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电气传动 2004年第z1期34卷 325-328页

作者：丁煜函戴先中东南大学

为解决红霉素发酵关键生化参量测定中的困难,提出了一种神经网络逆系统测量的方法.基于可测的溶解氧CL,pH值和体积V,通过构造神经网络逆,来得到无法直接测量的菌丝浓度、总糖和化学效价.检验结果表明,应用该方法得到的测量值与实际值比... 详细信息

为解决红霉素发酵关键生化参量测定中的困难,提出了一种神经网络逆系统测量的方法.基于可测的溶解氧CL,pH值和体积V,通过构造神经网络逆,来得到无法直接测量的菌丝浓度、总糖和化学效价.检验结果表明,应用该方法得到的测量值与实际值比较接近,较好地解决了红霉素发酵过程中的关键生化参量的测量问题,为实施优化控制打下了良好的基础.

关键词：测量神经网络红霉素发酵生化参量

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AZ31镁合金化学镀镍镀层分析

稀有金属材料与工程 2018年第8期47卷 2381-2385页

作者：闫鹏游国强丁煜瀚张秀丽童鑫重庆大学重庆400044 国家镁合金材料工程技术研究中心重庆400030

以H_3PO_4+HNO_3酸洗与NH_4HF_2+H_3PO_4活化为前处理工艺,对AZ31镁合金进行化学镀镍研究。应用扫描电子显微镜(SEM)、能谱分析(EDS)、X射线衍射仪(XRD)与X射线光电子能谱分析仪(XPS)等方法对化学镀镍层进行形貌、成分分布、相结构以及... 详细信息

以H_3PO_4+HNO_3酸洗与NH_4HF_2+H_3PO_4活化为前处理工艺,对AZ31镁合金进行化学镀镍研究。应用扫描电子显微镜(SEM)、能谱分析(EDS)、X射线衍射仪(XRD)与X射线光电子能谱分析仪(XPS)等方法对化学镀镍层进行形貌、成分分布、相结构以及元素分析。结果表明:化学镀镍层表面平整光亮,镀层为高磷非晶结构。化学镀镍层表面,镍主要以单质镍(26.75%)、NiO(32.96%)以及Ni(OH)_2(40.29%)形式存在,磷主要以单质磷(20.17%)、PO2-4(17.37%)以及PO_4^(3-)(62.46%)形式存在;化学镀镍层内部,镍基本为金属单质镍,磷主要以单质磷(74.11%)以及PO_4(2-)(25.89%)形式存在。

关键词： AZ31镁合金前处理化学镀镍

一种求解过程动态优化问题的生物地理学习粒子群算法

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化工学报 2017年第8期68卷 3161-3167页

作者：陈旭梅从立徐斌丁煜函刘国海江苏大学电气信息工程学院江苏镇江212013 华东理工大学化工过程先进控制和优化技术教育部重点实验室上海200237 上海工程技术大学机械工程学院上海201620

智能优化算法具有适用性广泛、全局搜索能力强等优点,近年来在动态优化中的应用逐渐增多。通过混合生物地理优化与粒子群优化,提出了生物地理学习粒子群(biogeography-based learning particle swarm optimization,BLPSO)算法,并用于动... 详细信息

智能优化算法具有适用性广泛、全局搜索能力强等优点,近年来在动态优化中的应用逐渐增多。通过混合生物地理优化与粒子群优化,提出了生物地理学习粒子群(biogeography-based learning particle swarm optimization,BLPSO)算法,并用于动态优化问题的求解。BLPSO采用了新型的生物地理学习方式,该方式根据粒子"排名",即粒子的优劣,以维度为单位构造学习粒子,提高了学习的效率。针对动态优化问题,首先通过控制向量参数化将其转化为非线性规划问题,然后采用BLPSO算法进行求解。最后,将BLPSO应用于非可微、多峰、多变量等典型动态优化问题的求解,计算结果表明BLPSO具有较好的搜索精度和收敛速度。

关键词：全局优化动态学算法控制向量参数化生物地理学习粒子群算法