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Active training sample selection and updating strategy for near-infrared model with an industrial application

Chinese Journal of chemical Engineering 2019年第11期27卷 2749-2758页

作者： Kaixun He Kai Wang Yayun Yan College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Training sample selection is widely accepted as an important step in developing a near-infrared(NIR) spectroscopic model. For industrial applications, the initial training dataset is usually selected empirically. This process is time-consuming, and updating the structure of the modeling dataset online is difficult. Considering the static structure of the modeling dataset, the performance of the established NIR model could be degraded in the online process. To cope with this issue, an active training sample selection and updating strategy is proposed in this work. The advantage of the proposed approach is that it can select suitable modeling samples automatically according to the process information. Moreover, it can adjust model coefficients in a timely manner and avoid arbitrary updating effectively. The effectiveness of the proposed method is validated by applying the method to an industrial gasoline blending process.

关键词： Near-infrared spectroscopy chemical processes Process systems Soft sensor Gasoline blending

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Adaptive output consensus for heterogeneous nonlinear multi-agent systems with multi-type input constraints under switching-directed topologies

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control Theory and Technology 2021年第2期19卷 260-272页

作者： Wei Zhang Zhaoxu Yu Shugang Li Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai200237China Department of Information Management Shanghai UniversityShanghai200444China

This study concentrates on solving the output consensus problem for a class of heterogeneous uncertain nonstrict-feedback nonlinear multi-agent systems under switching-directed communication topologies,in which all followers are subjected to multi-type input constraints such as unknown asymmetric saturation,unknown dead-zone and their integration.A unified representation is presented to overcome the difficulties originating from multi-agent input ***,the uncertain system functions in a non-lower triangular form and the interaction terms among agents are dealt with by exploiting the fuzzy logic systems and their special ***,by introducing a nonlinear filter to alleviate the problem of“explosion of complexity”during the backstepping design,a distributed common adaptive control protocol is proposed to ensure that the synchronization errors converge to a small neighborhood of the origin despite the existence of multiple input constraints and arbitrary switching communication *** stability analysis and simulation results are conducted to show the effectiveness and performance of the proposed control methodology.

关键词： Nonlinear multi-agent system Output consensus Fuzzy logic system Input constraint Switching topology

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Enantioselective effects of chiral antibiotics on antibiotic resistance gene dissemination and risk in activated sludge

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Bioresource Technology 2025年

作者： Fang Zhao Zhao Yang Jingjing Wang Mark Bartlam Yingying Wang Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education) Nankai International Advanced Research Institute (Shenzhen Futian) Tianjin Key Laboratory of Environmental Remediation and Pollution Control College of Environmental Science and Engineering Nankai University Tianjin 300350 China State Key Laboratory of Medicinal Chemical Biology College of Life Sciences Nankai International Advanced Research Institute (Shenzhen Futian) Nankai University Tianjin China

Misuse of antibiotics drives the spread of antibiotic resistance genes (ARGs). Although reducing residual antibiotic concentrations can help curb ARG proliferation, the biodegradation and transformation of antibiotic stereoisomers may exacerbate resistance development. However, the impact of antibiotic enantiomers on ARG proliferation remains poorly understood. This study employed metagenomic analysis to investigate the enantiomer-specific selection and resistance risks of chiral antibiotic ofloxacin (OFL) and its ( S )-enantiomer, levofloxacin (LEV), in activated sludge. Results showed that LEV primarily promoted the enrichment of ARGs related to aminoglycoside and mupirocin resistance by selecting for pathogenic bacteria carrying virulence factors under high toxicity stress. OFL-driven ARG proliferation involved more diverse mechanisms, including increased gene mobility, co-selection with heavy metals, broader host range, and elevated pathogenicity. The antibiotic resistome risk index (ARRI) further demonstrated a higher environmental risk under OFL treatment than LEV. These findings offer critical insights into the enantioselective resistance risks posed by chiral antibiotics.

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Event-triggered decentralized predictive control for coupled linear systems 36

Event-triggered decentralized predictive control for coupled...

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第36届中国控制会议

作者： YUAN Fenglin ZOU Yuanyuan NIU Yugang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Key Laboratory of System Control and Information Processing Department of AutomationShanghai Jiao Tong University

ISBN: (纸本)9781538629185

In this paper,we consider the problem of predictive control for a class of coupled linear *** solving a set of local optimization problems with decoupled cost functions and constraints,an event-triggered decentralized predictive control(DPC) scheme is *** event-triggering conditions only involving local information of every subsystem is derived and sufficient conditions of the recursive feasibility and the stability of close-loop control systems are also ***,a numerical example is given.

关键词： Coupled Linear Systems Decentralized Predictive control(DPC) Event-Triggered

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Multimode Process Monitoring Based on the Density-Based Support Vector Data Description

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Journal of Donghua University(English Edition) 2017年第3期34卷 342-348页

作者：郭红杰王帆宋冰侍洪波谭帅 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University ofScience and Technology Shanghai 200237 China

Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the *** solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.

关键词： Eastman Tennessee sparse utilized illustrated kernel Bayesian charts validity false

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Nonlinear adaptive switching control for a class of non-affine nonlinear systems

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Chinese Journal of chemical Engineering 2016年第9期24卷 1243-1251页

作者： Miao Huang Xin Wang Zhenlei Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology School of Optical–Electrical and Computer Engineering University of Shanghai for Science and Technology Center of Electrical & Electronic Technology Shanghai Jiao Tong University

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.

关键词： Non-affine nonlinear systems Nonlinear adaptive switching control Incremental model

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Process Monitoring Based on Independent Component Contribution

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Journal of Donghua University(English Edition) 2017年第3期34卷 349-354页

作者：吕小条宋冰侍洪波谭帅 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University ofScience and Technology Shanghai 200237 China

Independent component analysis( ICA) has been widely applied to the monitoring of non-Gaussian processes. Despite lots of applications,there is no universally accepted criterion to select the dominant independent components( ICs). Moreover, how to determine the number of dominant ICs is still an open question. To further address this issue,a novel process monitoring based on IC contribution( ICC) is proposed from the perspective of information storage. Based on the ICC with each variable,the dominant ICs can be obtained and the number of dominant ICs is determined objectively. To further preserve the process information, the remaining ICs are not useless. As a result,all the ICs are regarded to be divided into dominant and residual subspaces. The monitoring models are established respectively in each subspace, and then Bayesian inference is applied to integrating monitoring results of the two subspaces. Finally, the feasibility and effectiveness of the proposed method are illustrated through a numerical example and the Tennessee Eastman process.

关键词： Independent Eastman Tennessee Bayesian preserve illustrated criterion universally remaining integrating

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Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1326-1334页

作者： Wangli He Zekun Mo Qing-Long Han Feng Qian IEEE Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and TechnologyShanghai 200237China School of Software and Electrical Engineering Swinburne University of TechnologyMelbourne VIC 3122Australia

Cyber attacks pose severe threats on synchronization of multi-agent *** attack,as a typical type of cyber attack,can bypass the surveillance of the attack detection mechanism silently,resulting in a heavy ***,the problem of mean-square bounded synchronization in multi-agent systems subject to deception attacks is investigated in this *** control signals can be replaced with false data from controllerto-actuator channels or the *** success of the attack is measured through a stochastic variable.A distributed impulsive controller using a pinning strategy is redesigned,which ensures that mean-square bounded synchronization is achieved in the presence of deception *** sufficient conditions are derived,in which upper bounds of the synchronization error are ***,two numerical simulations with symmetric and asymmetric network topologies are given to illustrate the theoretical results.

关键词： Deception attacks impulsive control multi-agent systems(MASs) synchronization

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Modeling of oil near-infrared spectroscopy based on similarity and transfer learning algorithm

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Frontiers of chemical Science and Engineering 2019年第3期13卷 599-607页

作者： Yifei Wang Kai Wang Zhao Zhou Wenli Du Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and TechnologyShanghai 200237China School of information science and engineering East China University of Science and TechnologyShanghai 200237China

Near-infrared spectroscopy mainly reflects the frequency-doubled and total-frequency absorption information of hydrogen-containing groups (0 -H, C-H, N-H, S-H) in organic molecules for near-infrared lights with different wavelengths, so it is applicable to testing of most raw materials and products in the field of petrochemicals. However, the modeling process needs to collect a large number of laboratory analysis data. There are many oil sources in China, and oil properties change frequently. Modeling of each raw material is not only unfeasible but also will affect its engineering application efficiency. In order to achieve rapid modeling of near-infrared spectroscopy and based on historical data of different crude oils under different detection conditions, this paper discusses about the feasibility of the application of transfer learning algorithm and makes it possible that transfer learning can assist in rapid modeling using certain historical data under similar distributions under a small quantity of new data. In consideration of the requirement of transfer learning for certain similarity of different datasets, a transfer learning method based on local similarity feature selection is proposed. The simulation verification of spectral data of 13 crude oils measured by three different probe detection methods is performed. The effectiveness and application scope of the transfer modeling method under different similarity conditions are analyzed.

关键词： near-infrared spectroscopy transfer learning similarity modeling

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The multiscale simulation of metal organic chemical vapor deposition growth dynamics of GaInP thin film

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Science China(Physics,Mechanics & Astronomy) 2010年第8期53卷 1481-1490页

作者： HU GuiHua YU Tao Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and TechnologyShanghai 200237China CIMS&Robot Center of Shanghai University Shanghai 200072China

As a Group III–V compound, GaInP is a high-efficiency luminous material. Metal organic chemical vapor deposition (MOCVD) technology is a very efficient way to uniformly grow multi-chip, multilayer and large-area thin film. By combining the computational fluid dynamics (CFD) and the kinetic Monte Carlo (KMC) methods with virtual reality (VR) technology, this paper presents a multiscale simulation of fluid dynamics, thermodynamics, and molecular dynamics to study the growth process of GaInP thin film in a vertical MOCVD reactor. The results of visualization truly and intuitively not only display the distributional properties of the gas’ thermal and flow fields in a MOCVD reactor but also display the process of GaInP thin film growth in a MOCVD reactor. The simulation thus provides us with a fundamental guideline for optimizing GaInP MOCVD growth.

关键词： metal organic chemical vapor deposition computational fluid dynamics kinetic Monte Carlo virtual reality multiscale simulation GaInP thin film growth

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