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Chinese Automation Congress (CAC)

作者： Yu Shang Cheng-Lin Liu Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

This paper investigates the consensus control problem of first-order nonlinear multi-agent systems (MASs), and a distributed event-triggered consensus protocol is proposed. Different from the traditional event-triggered protocol with zero-order hold, we use the first-order hold to keep the sampling states. In the light of Lyapunov stability criterion, we present a sufficient condition for the agents reaching the asymptotic consensus, and Zeno behavior can be avoided. Finally, the correctness of the proposed control protocol is demonstrated by numerical simulations.

关键词： Protocols Artificial neural networks Multi-agent systems Eigenvalues and eigenfunctions Nonlinear dynamical systems Topology Lyapunov methods

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A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine

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Journal of Central South University 2017年第8期24卷 1779-1788页

作者：孙泽文顾幸生 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education(East China University of Science and Technology)Shanghai 200237China

The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.

关键词： hybrid estimation of distribution algorithm teaching learning based optimization strategy hybrid flow shop unrelated parallel machine scheduling

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Fixed-Time Consensus Tracking of Heterogeneous Multi-agent Systems*

Fixed-Time Consensus Tracking of Heterogeneous Multi-agent S...

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Chinese Automation Congress (CAC)

作者： Cong Wang Cheng-Lin Liu Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

Fixed-time consensus tracking problem of the heterogeneous multi-agent systems comprised of first-order agents and second-order agents with uncertain disturbances is studied in this paper. To solve consensus tracking problem of heterogeneous multi-agent systems, we design a novel distributed fixed-time observer for each follower to estimate leader's states, and the decentralized fixed-time sliding mode controllers which can suppress disturbances to make each follower track the leader's states within fixed-time. By using graph theory and Lyapunov stability theory, fixed-time consensus tracking conditions are presented for our proposed algorithms. Simulation examples show the effectiveness of theoretical results.

关键词： Multi-agent systems Observers Lyapunov methods Delays Topology Graph theory

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An Adaptive Event-Triggered Synchronization Approach for Chaotic Lur’e Systems Subject to Aperiodic Sampled Data

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IEEE Transactions on Circuits and Systems II: Express Briefs 2019年第3期66卷 442-446页

作者： Yueying Wang Hamid Reza Karimi Huaicheng Yan School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China Department of Mechanical Engineering Politecnico di Milano Milan Italy Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai China

This brief deals with the problem of master-slave synchronization for chaotic Lur'e systems with aperiodic sampled data. Specifically, a novel aperiodic adaptive event-triggered communication mechanism is introduced to reduce the transmission load, which covers the previous ones as special cases. By partially resorting to the time-dependent Lyapunov function, a new synchronization criterion is derived, which depends on both the upper and lower bounds of variable sampling interval. Finally, Chua's circuit system is chosen as an illustrative example to show the virtue and effectiveness of the achieved synchronization strategies.

关键词： Synchronization Chaotic communication Master-slave Circuits and systems Extraterrestrial measurements Symmetric matrices Adaptive systems

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An improved UKPK-PSO algorithm inspired from block chain technology for flexible job shop scheduling problem

An improved UKPK-PSO algorithm inspired from block chain tec...

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第三十八届中国控制会议

作者： Lin Yao Yabin Liu Houbao Zhao Haojie Ding Shanghai Polytechnic University Shanghai Lixin University of Accounting and Finance Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

The paper proposes a new encoding method inspired from the block chain technology, by which an operation sequence information and the corresponding machine information is integrated in an operation node and links all operation nodes to form an operation list with pointer technology of C++ program language. Accordingly, the paper designs an individual unit ID for every possible cases. Subsequently, it describes the process of searching the optimal solution of FJSP by implementing an improved UKPK-PSO algorithm, which hybridizes a varied PSO algorithm by getting the best information from K informants and the method of keeping the elitists for next generation in iterations. With the improved algorithm we can more efficiently traverse the solution space. After obtained some better solutions with the improved PSO, we continuously search the optimal solutions by tentatively changing the chosen machines of the dominant operations. Finally, it outputs the optimal solution through some limited iterations again. By analyzing the experiment results for the instances, the paper furtherly proves that the whole algorithm is effective for FJSP.

关键词： Flexible job shop scheduling problems Particle Swarm Optimal Algorithm Block chain Technology Operations Research

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Formation-containment control of second-order multi-agent systems with sampled data and intermittent communication

Formation-containment control of second-order multi-agent sy...

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2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Xia, Mao-Dong Liu, Cheng-Lin Liu, Fei Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

ISBN: (纸本)9781538680698

This paper investigates the formation-containment control of multi-agent systems with agents' dynamics modelled by double integrators. For the agents communicating with each other intermittently, distributed coordination control algorithms are constructed for the leaders and following agents respectively. In our proposed algorithms, each agent's input is driven by continuous-time data, sampled data and zero are proposed. By means of the theories about matrices and algebraic graphs, sufficient conditions are analyzed respectively for the leaders converging to the expected formation asymptotically and the followers reaching the containment region of the leaders asymptotically. Furthermore, the validity of our theoretical results are shown by simulations. © 2018 IEEE.

关键词： Multi agent systems

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Manipulating interfacial charge redistribution in Mn 0.5 Cd 0.5 S/N-rich C 3 N 5 S-scheme heterojunction for high-performance photocatalytic removal of emerging contaminants

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Journal of Materials Science & Technology 2025年

作者： Deyun Ma Qingquan Xue Yanping Liu Fenglan Liang Wenyao Li Tong Liu Chunqiang Zhuang Zaiwang Zhao Shijie Li School of Food and Pharmaceutical Engineering School of life sciences Zhaoqing University Zhaoqing 526061 China Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province Interdisciplinary Research Academy (IRA) Zhejiang Shuren University Hangzhou 310015 China National Engineering Research Center for Marine Aquaculture Zhejiang Ocean University Zhoushan 316022 China School of Materials Science and Engineering Shanghai University of Engineering Science Shanghai 201620 China Key Laboratory of Green Chemical Process Ministry of Education Hubei Key Laboratory of Novel Reactor and Green Chemical Technology School of Chemical Engineering and Pharmacy Wuhan Institute of Technology Wuhan 430205 China Institute of Microstructure and Property of Advanced Materials Beijing University of Technology Beijing 100124 China College of Energy Materials and Chemistry College of Chemistry and Chemical Engineering Inner Mongolia University Hohhot 010070 China

Engineering advanced S-scheme heterojunction photocatalysts represents a prospective strategy for efficient antibiotic-contaminated wastewater decontamination. However, the practical realization of such systems is hindered by difficulties in achieving seamless interfacial integration and precise control over charge-carrier dynamics. Herein, we proposed a shell-core 0D/2D Mn 0.5 Cd 0.5 S/C 3 N 5 S-scheme heterojunction with compact interfacial contact, synthesized by in-situ solvothermal growth of Mn 0.5 Cd 0.5 S nanodots on C 3 N 5 nanosheets. This optimized Mn 0.5 Cd 0.5 S/C 3 N 5 heterojunction performs extraordinary catalytic performance and enables approximately 1.3- and 3.2-fold tetracycline abatement rate greater than that for Mn 0.5 Cd 0.5 S and C 3 N 5 , respectively, which arises from the synergy of efficient spatial photo-carrier separation and well preserved great redox capacity of the heterojunction enabled by the S-scheme mechanism. Mechanistic validation was achieved through systematic characterizations and computational analyses. This study advances the rational design of shell-core S-scheme heterojunctions for photocatalytic antibiotic wastewater treatment.

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Investigation of anisotropic thermophysical properties of highly oriented carbon fiber composites: From one to three dimensions

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Carbon 2025年 243卷

作者： Yanhui Zhang Jie Yang Xiaoyu Zhang Rui Xu Minsu Liu Aoran Fan Yingjun Liu Jianli Wang Xing Zhang Jiangsu Key Laboratory for Design and Manufacturing of Precision Medicine Equipment Department of Mechanical Engineering Southeast University Nanjing 210096 China Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering Mechanics Tsinghua University Beijing 100084 China Monash Suzhou Research Institute Monash University Suzhou 215000 China ARC Research Hub for Smart Process Design and Control School of Chemical and Biological Engineering Monash University Clayton VIC 3800 Australia MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and Engineering Key Laboratory of Adsorption and Separation Materials & Technologies of Zhejiang Province Zhejiang University 38 Zheda Road Hangzhou 310027 China

Highly oriented carbon fiber composites exhibit three-dimensional anisotropic thermophysical properties, making them candidates for thermal management applications. In this study, the thermal properties of highly oriented carbon fiber/epoxy resin (CF/ER) composites and their components were systematically investigated. The T-type probe method was employed to measure the pitch CF, while the 2ω method and the laser-spot-periodic-heating method were combined to characterize the E51-ER film and the composites. The impact of local fiber bending on heat transfer in the composites was also analyzed through finite element simulations. The results show that these composites exhibit high thermal conductivity along the fiber orientation with an anisotropy ratio of about 294. At different temperatures, the thermal conductivity along the fiber orientation is lower than the value predicted by the parallel model, while the conductivity in the other two directions is significantly higher than that predicted by the series model. Simulation results suggest that the bending of certain pitch CF can be a key factor contributing to this discrepancy.

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Multi-objective modeling and optimization for scheduling of cracking furnace systems

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Chinese Journal of chemical Engineering 2017年第8期25卷 992-999页

作者： Peng Jiang Wenli Du Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education School of Information Science and Engineering East China University of Science and Technology

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.

关键词： Cracking furnace systems Feed scheduling Multi-objective mixed integer nonlinear optimization Genetic algorithm

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Facilitating renewable natural gas production for a circular bioeconomy: AI-Driven process visualization and data augmentation on biochar-mediated anaerobic digestion

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chemical Engineering Journal 2025年 516卷

作者： Xiaoman He Jingyuan Guo Xihui Kang Xue Ning Huichao Chen Daolun Liang Chen Deng Zutan Li Dekui Shen Huiyan Zhang Richen Lin Jerry D. Murphy Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and Environment Southeast University Nanjing 211189 China Advanced Biofuels and Bioproducts Process Development Unit Biological Systems and Engineering Division Lawrence Berkeley National Laboratory Emeryville CA 94608 USA School of Engineering and Architecture University College Cork T23XE10 Cork Ireland Research Ireland MaREI Centre for Energy Climate and Marine Environmental Research Institute University College Cork T23XE10 Cork Ireland School of Chemistry and Chemical Engineering Southeast University Nanjing 211189 China School of Engineering Westlake University Hangzhou Zhejiang 310030 China Institute of Advanced Technology Westlake Institute for Advanced Study Hangzhou Zhejiang 310024 China

The conversion of biomass residues into biochar is a promising strategy for enhancing sustainability within the circular bioeconomy, particularly through its role in improving renewable natural gas production. However, engineering biochar with optimal properties remains a complex challenge, as the relationship between preparation conditions, biochar characteristics, and anaerobic digestion (AD) performance is not fully understood. This study presents an AI-derived full-process prediction approach that integrates machine learning and generative models to guide the rational design of biochar, and optimize its use for biomethane production. Three tree-based regression models were employed to predict AD performance, with the eXtreme Gradient Boosting Regression model demonstrating superior accuracy. Feature importance analysis identified key biochar properties, including electrical conductivity, oxygen content, and specific surface area, as critical factors influencing biomethane production. These properties can be fine-tuned by adjusting pyrolysis conditions and selecting suitable biomass sources. A generative adversarial network was further used to explore a broader data space, helping to identify the optimal combination of parameters for maximizing AD efficiency. This novel AI-driven framework facilitates biochar-mediated renewable natural gas production, offering a scalable and sustainable approach for advancing circular bioeconomy.

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