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第三十八届中国控制会议

作者： Yupeng Li Xian Du Ximing Sun Anning Dai Jixiang Chen Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of Control Science and Engineering Dalian University of Technology

Multivariable control has become an indispensable factor for advanced aero-engine control. Considering the fact that most multivariable techniques are model-based and the accurate adaptive model of aero-engines is difficult to acquire, a multivariable control scheme based on active disturbance rejection control is proposed. Moreover, aero-engines are subject to all kinds of limits, nonlinear limit functions is put forward and introduced in the aero-engine control system. At first, multivariable control framework based on active disturbance rejection control(ADRC) is achieved, in which tracking differentiator(TD) is designed to provide the fastest tracking of reference input and its derivative subject, linear extended state observer(LESO) is designed to observe the total disturbance. Then, nonlinear state error feedback(NLSEF) is designed to employ a nonlinear feedback combination with higher efficiency. Finally, the limits protections of aero-engine is considered. Results show that the proposed controller can not only decouple both control loops, but also keeps the turbine outlet temperature within prescribed limit bound.

关键词： Active disturbance rejection control(ADRC) aero-engine multivariable control control protection

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Comparative study on the impact of ethane/ethylene/acetylene addition on ignition of fuel-rich n-decane/air flame

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UPB Scientific Bulletin, Series B: Chemistry and Materials science 2020年第4期82卷 185-198页

作者： Huang, Jing Li, Fangsheng Qi, Yunguo College of Environmental and Biological Engineering Fujian Provincial Key Laboratory of Ecology-Toxicological Effects & Control for Emerging Contaminants Putian University PutianFujian China Dept. of Chemical Engineering Qingdao University of Science and Technology QingdaoShandong China Dept. of Chemical Engineering Weifang vocational college WeifangShandong China

The ignition of heavy hydrocarbon at high altitude regions is difficult as the air is very thin so that the fuel/air is ignited under ultimately fuel-rich condition. To simulate and improve the ignition of heavy hydrocarbon (n-decane) at high altitude regions, the effects of ethane/ethylene/acetylene addition on ignition of fuel-rich n-decane/air mixtures are studied and compared numerically in the present study. Our research found that the addition of C2H6 inhibits the ignition when the starting ignition temperature (T0) 0 >1150 K. C2H4 addition affects little on the ignition when T0 = 1000 K and promotes the ignition when T0 >1000 K. The addition of C2H2 promotes the ignition at all considered temperatures. The ignition delay with ethane, ethylene and acetylene additions at various equivalence ratio and different pressure conditions indicate that the order of promoting auto-ignition from intense to weak are C2H2, C2H4 and C2H6. Our findings would be a useful guidance to promote the ignition of real jet at high altitude regions by adding C2H2 to the real jet fuel n-decane. The results also provided a way for the efficient ignition of motor and had great significance in the safe production of oil industry. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Ethylene

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Quantifying the mitigation potential of energy and chemical consumption for a full-scale wastewater treatment plant with deep learning methods

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Applied Energy 2025年 394卷

作者： Yu, Chenyang Huang, Runyao Yu, Jie Zhang, Shike Jin, Sitian Xu, Qianrong Zhang, Jing Ai, Zisheng Mąkinia, Jacek Wang, Hongtao Key Laboratory of Yangtze River Water Environment Ministry of Education State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University Shanghai200092 China Institute of Carbon Neutrality Tongji University Shanghai200092 China Shanghai Institute of Pollution Control and Ecological Security Tongji University Shanghai200092 China College of Surveying and Geo-Informatic Tongji University Shanghai200092 China School for Environment and Sustainability University of Michigan Ann Arbor United States School of Medicine Tongji University Shanghai200092 China Faculty of Civil and Environmental Engineering Gdańsk University of Technology Narutowicza Street 11/12 Gdańsk80-233 Poland

Wastewater treatment plants (WWTPs) play an essential role in urban water system, assisting in realizing urbanization and sustainable development. They consume large amounts of energy and chemicals to remove the wastewater pollutants each year around the world, highlighting an urgent need to explore and discover the energy and chemical saving potential of WWTPs. Recently, deep learning model has attracted increasing attention in various research fields. This study evaluated an Attention optimized bidirectional Gated recurrent unit Long short-term memory (ABGL) model against several benchmark deep learning models. Comparative analysis revealed that while ABGL demonstrates superior performance, the optimal model selection should be carefully evaluated based on data accuracy and computational complexity. Among these models, ABGL showed best accuracy and feasibility for the ability of predicting energy and chemical consumption. The results of the model predictions showed that energy saving and chemical saving of studied WWTP could be as high as 9.21 % and 18.78 %, respectively. Accordingly, the energy intensity of the WWTP should be controlled below 0.28 kWh/m3 and the chemical intensity be controlled below 0.09 kg/m3. Implementation of the deep learning model such as ABGL will assist the decision-makers of WWTPs in optimizing the input efficiency, setting a novel paradigm that guides the smart operations of the whole sector by the state-of-the-art DNN model. © 2025 Elsevier Ltd

关键词： Energy efficiency

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A Game Theoretic Approach for Service Chain Composition in Network Function Virtualization Network

A Game Theoretic Approach for Service Chain Composition in N...

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第三十八届中国控制会议

作者： Shu-Ting Le Yuhu Wu Xi-Ming Sun Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of Control Science and Engineering Dalian University of Technology

Network functions virtualization(NFV) is a network architecture that visualizes entire classes of network node functions into software to create Network Service(NS). In this paper, the service chain composition problem in NFV Network is investigated. We leverage non-cooperative game theory to provide a solution to the above-mentioned problem. The service chain composition is converted to the seeking of the potential function under the game framework. By using semi-tensor product of matrices(STP), the potential function of the formulated game is presented and the service chain composition is achieved. Finally,an example is studied to illustrative the effectiveness of the results.

关键词： Semi-tensor product of matrices game theory congestion games service chain Network function virtualization(NFV) Nash equilibrium

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Green vehicle routing optimization based on dynamic constraint selection co-evolutionary algorithm

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Scientific reports 2025年第1期15卷 17688页

作者： Lu-Jie Zhou Hai-Fei Zhang Jun-Hao Fu School of Automobile and Transportation Tianjin University of Technology and Education Tianjin 300222 China. Nanjing Xiaozhuang University College of information engineering Nanjing China. ***@***. School of Artificial Intelligence and Computer Science Jiangnan University Wuxi 214122 Jiangsu China. Key Laboratory of Advanced Process Control for Light Industry (Jiangnan University) Ministry of Education Wuxi 214122 China.

Aiming at the problems of single solution objective in the existing green vehicle routing optimization process and real-time speed change during vehicle travel, a multi-objective green vehicle routing problem with time window constraints in time-varying conditions(MOGVRPTW-TV) is established, then a co-evolutionary framework-based constrained multi-objective evolutionary algorithm for the solving of the model is proposed. First, to better match the actual logistics distribution, this model considers the impact of time-varying speed and capacitated variation on carbon emissions based on capacitated constraints and time window constraints. Second, a constrained multi-objective evolutionary algorithm based on the co-evolutionary framework was proposed for model solving. The algorithm treats the complete problem model as a complex task and introduces a shift crowding distance calculation that considers both individual distribution and convergence information when solving this complex task, effectively balancing the convergence and diversity of solutions. Then, a dynamic constraint selection strategy is designed for the implementation of the simple task, which only considers the effects of some constraints on the populations, and the two populations exchange information through offspring populations to achieve overall optimization. Simulations are performed on different instances and the results show that the proposed algorithm is effective in avoiding traffic congestion periods, decreasing overall distribution costs, and reducing fuel consumption and carbon emissions of vehicles.

关键词： Co-evolutionary algorithm Dynamic constraint selection Logistics distribution Multi-objective optimization Time-varying property

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Mxene quantum dot insertion-induced electron transfer in CoFe LDH for high-performance zinc-air batteries

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Chemical engineering Journal 2025年 516卷

作者： Qing Sun Kailin Li Tie Shu Ziyang Guo Yongfei Li Yuxin Zhang Liang Li Jiaoyi Ning Peng Zhao Ke Xin Yao State Key Laboratory of Coal Mine Disaster Dynamics and Control School of Chemistry and Chemical Engineering Multi-Scale Porous Materials Center Institute of Advanced Interdisciplinary Studies Chongqing University Chongqing 400044 China College of Material Science and Engineering Chongqing University Chongqing 400044 China State Key Laboratory of Molecular Engineering of Polymers Department of Chemistry Fudan University Shanghai 200433 China School of Materials Science and Engineering Beijing Institute of Technology Beijing 100081 China Department of Sciences and Engineering Sorbonne University Abu Dhabi PO Box 38044 Abu Dhabi United Arab Emirates School of Chemical Engineering Huaqiao University Fujian 361021 China

Cobalt-iron layered double hydroxide (CoFe LDH), a promising air cathode material for rechargeable zinc-air batteries (ZABs), faces significant challenges in practical applications due to its low oxygen evolution reaction (OER) catalytic activity and the ambiguity in identifying its active sites. To address these issues, this study introduces MXene quantum dots (MQDs) into CoFe LDH, fabricating a CoFe LDH/MQD/Co@NF composite with enhanced interfacial electronic coupling. This integration induces electron transfer from CoFe LDH to MQDs, leading to the pre-oxidation of Co ions into higher-valence Co 3+ states, as confirmed by X-ray photoelectron spectroscopy, and optimizing OER intermediate adsorption kinetics. Density functional theory (DFT) calculations reveal cobalt as the primary active site, highlighting its critical role in boosting catalytic activity. The composite exhibits a low OER overpotential of 192 mV at 10 mA cm −2 , a Tafel slope of 36.3 mV dec -2 , a maximum power density of 136.5 mW cm −2 , and a high specific energy of 626 mA h g −1 in ZABs, with exceptional durability over an 85-hour cyclic test. These results demonstrate that MQD incorporation significantly improves OER catalytic activity and enhances ZAB performance, offering a promising strategy for designing high-performance, long-lasting electrocatalysts and advancing electrochemical energy storage technologies.

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A novel D-π-A type NBD-based fluorescent probe for ultrafast and distinguishable detection of Hcy/Cys and its bioimaging application

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Journal of Luminescence 2020年 224卷 117330-117330页

作者： Zhong, Keli Zhou, Shiyi Yan, Xiaomei Hou, Shuhua Li, Xuepeng Tang, Lijun College of Chemistry and Chemical Engineering College of Food Science and Technology Bohai University Food Safety Key Lab of Liaoning Province National & Local Joint Engineering Research Center of Storage Processing and Safety Control Technology for Fresh Agricultural and Aquatic Products Bohai University Jinzhou121013 China College of Laboratory Medicine Dalian Medical University Dalian116044 China

Due to the important physiological role of biothiols, the detection for biothiols is becoming increasingly significant, especially the distinguishing detection of Hcy/Cys. In this paper, a simple long-wavelength dual emission fluorescent probe L was designed and synthesized by two-steps reactions using 4-diethylaminosalicylaldehyde as raw material. Probe L can detect Hcy/Cys in the pH range of 6–9 and the detection limit for Hcy and Cys as low as 2.81 μM and 2.33 μM, while L does not respond to GSH/H2S in THF/PBS (2/8, v/v) solution. Probe L can sense Cys with ultrafast responding within 10 s but can detect Hcy in ~6 min, which Hcy/Cys can be distinguished by the reaction speed. In addition, probe L can individually recognize Hcy with better anti-interference ability and sensitivity and distinguish Hcy from Cys in THF/PBS (2/8, v/v, pH 10). Moreover, probe L has been successfully applied to biological field and imaging Hcy in living cells. © 2020

关键词： Probes

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Nb_2O_5 nanowires in-situ grown on carbon fiber: A high-efficiency material for the photocatalytic reduction of Cr(Ⅵ)

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Journal of Environmental sciences 2018年第4期30卷 358-367页

作者： Yucheng Du Shihao Zhang Jinshu Wang Junshu Wu Hongxing Dai Key Lab of Advanced Functional Materials Ministry of Education College of Materials Science and Engineering Beijing University of Technology Beijing Key Laboratory for Green Catalysis and Separation Key Laboratory of Beijing on Regional Air Pollution Control Laboratory of Catalysis Chemistry and Nanoscience Department of Chemistry and Chemical Engineering College of Environmental and Energy EngineeringBeijing University of Technology

Niobium oxide nanowire-deposited carbon fiber（CF） samples were prepared using a hydrothermal method with amorphous Nb2O5·nH2O as precursor. The physical properties of the samples were characterized by means of numerous techniques, including X-ray diffraction（XRD）, energy-dispersive spectroscopy（EDS）, scanning electron microscopy（SEM）, transmission electron microscopy（TEM）, selected-area electron diffraction（SAED）, UV–visible spectroscopy（UV–vis）, N2 adsorption–desorption, Fourier transform infrared spectroscopy（FT-IR）, and X-ray photoelectron spectroscopy. The efficiency for the removal of Cr（VI） was *** such as pH value and initial Cr（VI） concentration could influence the Cr（VI） removal efficiency or adsorption capacity of the Nb2O5/carbon fiber sample obtained after hydrothermal treatment at 160°C for 14 hr. The maximal Cr（VI） adsorption capacity of the Nb2O5 nanowire/CF sample was 115 mg/g. This Nb2O5/CF sample also showed excellent photocatalytic activity and stability for the reduction of Cr（Ⅵ） under UV-light irradiation： the Cr（VI） removal efficiency reached 99.9% after UV-light irradiation for 1 hr and there was no significant decrease in photocatalytic performance after the use of the sample for 10 repeated cycles. Such excellent Cr（VI） adsorption capacity and photocatalytic performance was related to its high surface area,abundant surface hydroxyl groups, and good UV-light absorption ability.

关键词： Carbon fiber Niobium oxide nanowire Photocatalytic reduction Cr（Ⅵ） removal Adsorption efficiency

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Membrane-based Processes for Sustainable Geothermal Water Reuse and Mining: A Comprehensive Review of Process Integration and Influencing Parameters

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Journal of Environmental Chemical engineering 2025年

作者： Bing Wu Tian Li An Ding Faculty of Civil and Environmental Engineering University of Iceland Hjardarhagi 2-6 IS-107 Reykjavík Iceland State Key Laboratory of Water Pollution Control and Green Resource Recycling Key Laboratory of Yangtze River Water Environment Ministry of Education Key Laboratory of Urban Water Supply Water Saving and Water Environment Governance in the Yangtze River Delta of Ministry of Water Resource College of Environmental Science and Engineering Tongji University 200092 Shanghai PR China School of Environment and Energy Engineering Beijing University of Civil Engineering and Architecture 100044 Beijing China State Key Laboratory of Urban Water Resource and Environment (SKLUWRE) School of Environment Harbin Institute of Technology 73 Huanghe Road Nangang District 150090 Harbin China

Geothermal water has been recognized as a valuable resource for renewable energy generation, freshwater production, and valuable mineral/metal recovery. In recent years, application of membrane-based techniques for desalination of geothermal brine (after energy extraction) for simultaneously producing clean water and concentrating minerals/metals (i.e., pretreatment process for their recovery) has been considered as a promising solution for sustainable geothermal resource management. In this paper, we aimed to provide an overview of the current-reported membrane processes for resource recovery from geothermal fluids. The operating parameters and geothermal water property (temperature and salt contents) that are associated with membrane performance, treated water quality, and energy consumption are discussed. In particular, hybrid membrane processes towards improving membrane system performance, treated water quality or mineral/metal recovery efficiency are illustrated, and their advantages and challenges are highlighted. Towards achieving circular economy in geothermal power plants, the prospects and future research directions relating to membrane technology-based geothermal resource utilization are discussed.

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RFBLS: A robust rough fuzzy broad learning system with local neighborhood structure

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Neurocomputing 2025年 647卷

作者： Yonghe Chu Yanlong Guo Peng Li Weiping Ding Witold Pedrycz Heling Cao School of Artificial Intelligence and Computer Science Nantong University Nantong 226019 China College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Key Laboratory of Grain Information Processing and Control(Henan University of Technology) Ministry of Education Zhengzhou 450001 China Centre for Complexity Science Henan University of Technology Zhengzhou 450001 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2R3 Canada Institute of Systems Engineering Macau University of Science and Technology Macau SAR Taipa 999078 China Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkiye

As an extension of random vector functional link neural network (RVFLNN), the broad learning system (BLS) has gradually been applied in various fields due to its advantages of simple network structure, rapid training, and fast model updating. Despite its remarkable achievements, there are still some difficulties and challenges that restrict its further application in practical tasks. In BLS, all samples equally contribute to constructing the optimal classification boundary. However, when training samples contain noise or outliers, it will result in the obtained classification boundary not being the true optimal classification boundary. In other words, BLS is sensitive to noise points or outliers. To address it, we propose a robust rough fuzzy broad learning system with local neighborhood structure (RFBLS). In RFBLS, fuzzy sets are utilized by associating a membership degree with each sample. This incorporation ensures diverse contributions of different samples during the minimization of the objective function. Samples with noise or outliers are assigned smaller weights, effectively eliminating the influence of noise and outlier samples in the learning process. We employ the rough set theory to explore the influence-decision degree of each conditional attribute on the decision attribute, aiming to eliminate the impact of redundant or interfering features. Subsequently, we comprehensively consider the distance between samples and class centers, as well as the local neighborhood structure relationship between samples. Initially, we calculate the initial membership degree of each sample based on the distance to class centers. Then, utilizing fuzzy K-nearest neighbors, we calculate and rank the membership degrees of K nearest neighbors for each sample. These rankings are then weighted with the initial membership degree, achieving the fusion of relationships and membership degree calculations between samples. Finally, extensive comparative experiments are conducted on var

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