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A Multi-Condition Sequential Network Ensemble for Industrial Energy Storage Prediction Considering the Condition Switching Characteristics

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 369-380页

作者： Tianyu Wang Fan Zhou Yangjie Wu Jun Zhao Wei Wang IEEE the School of Control Science and Engineering Dalian University of Technology the School of Information Science and Engineering Dalian Polytechnic University

As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system scheduling. Considering that the continuous switching of the pressure and valve status(mechanism knowledge) would bring about multiple working conditions of the equipment, a multi-condition time sequential network ensembled method is proposed. In order to especially consider the time dependence of different conditions, a centralwise condition sequential network is developed, where the network branches are specially designed based on the condition switching sequences. A branch combination transfer learning strategy is developed to tackle the sample imbalance problem of different condition data. Since the condition or status data are real-time information that cannot be recognized during the prediction process, a pre-trained and ensemble learning approach is further proposed to fuse the outputs of the multi-condition networks and realize a transient-state involved prediction. The performance of the proposed method is validated on practical energy data coming from a domestic steel plant, comparing with the state-of-the-art algorithms. The results show that the proposed method can maintain a high prediction accuracy under different condition switching cases, which would provide effective guidance for the optimal scheduling of the industrial energy systems.

关键词： Ensemble learning industrial energy prediction multi-working condition structural deep network transfer learning

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Event-triggered leader-follower bipartite consensus control for nonlinear multi-agent systems under DoS attacks

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science China(Information sciences) 2025年第3期68卷 286-301页

作者： Wei SU Chaoxu MU Song ZHU Ben NIU Changyin SUN School of Control Science and Engineering Tianjin University School of Mathematics China University of Mining and Technology School of Control Science and Engineering Dalian University of Technology School of Automation Southeast University

Aiming at the consensus control problem of nonlinear multi-agent systems(MASs) under directed topology, a leader-follower bipartite consensus control strategy is proposed. This strategy takes into account the potential for denial-of-service(DoS) attacks and completely unknown system dynamics. Specifically, the bipartite consensus dynamics describes the cooperation and competition relationship between followers and the leader, that is, the follower chooses to move in accordance with or opposite to the leader according to its trajectory. In order to optimize the communication bandwidth and mitigate the impact of DoS attacks, the proposed consensus control scheme integrates the DoS attack detection mechanism and event-triggered mechanism. In addition, neural networks(NNs) are used to solve the nonlinear problem, and a speed function is designed to achieve the desired tracking performance, ensuring that all agents' tracking errors converge to a predefined set in a finite time. With the help of backstepping, graph theory, and Lyapunov stability theory, sufficient conditions for achieving bipartite consensus without Zeno behavior are established. Finally, the accuracy and feasibility of the theoretical analysis are verified by simulation cases.

关键词： multi-agent systems neural networks bipartite consensus event-trigger denial-of-service attack

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Physically informed hierarchical learning based soft sensing for aero-engine health management unit

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Chinese Journal of Aeronautics 2025年第3期38卷 374-385页

作者： Aina WANG Pan QIN Yunbo YUAN Guang ZHAO Ximing SUN School of Control Science and Engineering Dalian University of TechnologyDalian 116024China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian 116024China School of Energy and Power Engineering Dalian University of TechnologyDalian 116024China

Partial Differential Equations(PDEs)are model candidates of soft sensing for aero-engine health management *** existing Physics-Informed Neural Networks(PINNs)have made ***,unmeasurable aero-engine driving sources lead to unknown PDE driving terms,which weaken PINNs *** this end,Physically Informed Hierarchical Learning followed by Recurrent-Prediction Term(PIHL-RPT)is ***,PIHL is proposed for learning nonhomogeneous PDE solutions,in which two networks NetU and NetG are *** is for learning solutions satisfying PDEs;NetG is for learning driving terms to regularize NetU ***,we propose a hierarchical learning strategy to optimize and couple NetU and NetG,which are integrated into a data-physics-hybrid loss ***,we prove PIHL-RPT can iteratively generate a series of networks converging to a function,which can approximate a solution to well-posed ***,RPT is proposed for prediction improvement of PIHL,in which network NetU-RP is constructed to compensate for information loss caused by data sampling and driving sources’***,artificial datasets and practical vibration process datasets from our wear experiment platform are used to verify the feasibility and effectiveness of PIHL-RPT based soft ***,comparisons with relevant methods,discussions,and PIHL-RPT based health monitoring example are given.

关键词： Hierarchical learning strategy Monitoring:Partial differen tial equations with unmeasurable driving terms Physically informed hierarchical learning followed by recurrent-prediction term Soft sensing

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Event-Triggered Trajectory Tracking control for Unmanned Surface Vessels With Prescribed Performance Using Barrier Lyapunov Functions

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IEEE Transactions on Fuzzy Systems 2025年第5期33卷 1466-1474页

作者： Du, Xian Yuan, Xu Yang, Bin Zhao, Xudong Dalian University of Technology School of Control Science and Engineering Dalian116024 China

This paper investigates the event-triggered trajectory tracking control for unmanned surface vessels with prescribed performance subjected to asymmetric time-varying state constraints. In order to realize the prescribed-time control task, a performance function is introduced and the fuzzy logic systems are adopted to estimate the unknown nonlinearities of the USVs model. Subsequently, a flexible event-triggered mechanism is designed to minimize the wastage of communication resource, taking into account the continuous updating of the actual control input. A practical virtual control signal is devised and used for backstepping design. On this basis, an event-triggered adaptive fuzzy trajectory tracking control algorithm with prescribed performance is developed by combining the defined performance function and the barrier Lyapunov function approach, which not only solves the asymmetric time-varying state constraints of the USVs, but also ensures that the USVs achieve the predetermined tracking performance, meanwhile, all the closed-loop signals can be maintained bounded. Finally, the simulation results are performed to demonstrate the feasibility of the developed control scheme. © 1993-2012 IEEE.

关键词： Lyapunov functions

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Incomplete data modeling based on alternate update of clustering and autoencoder for missing value imputation

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Neural Computing and Applications 2025年第3期37卷 1523-1540页

作者： Lai, Xiaochen Zhang, Zheng Zhang, Liyong Lu, Wei Li, ZhuoHan School of Software Dalian University of Technology Dalian116600 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

Missing values exist widely in real-world datasets, which restrict the performance of data mining. In this paper, we propose a joint optimization framework to mine attribute associations and category structures in incomplete datasets, aiming to impute missing values with a full understanding of the data structure. Considering the differences in attribute correlations among different sample categories, we partition incomplete data into fuzzy subsets by fuzzy clustering. Within each subset, a tracking-removed autoencoder is constructed as a submodel to fit the regression relationships among attributes. Due to the mutual influence between fuzzy clustering and regression modeling, we further propose a missing value variable-based training scheme to iteratively optimize these two processes. Our proposed framework offers the advantage of decomposing the complex imputation task into simpler sub-tasks by fuzzy clustering where the attribute associations are more explicit. Moreover, the proposed training scheme activates the complementary nature of clustering and regression processes to reduce imputation errors. The experimental results on artificial and real datasets illustrate the effectiveness of our proposed framework. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Fuzzy clustering

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Springback Behavior and Biocompatibility inβ-Type Ti-Mo-O Alloys

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Acta Metallurgica Sinica(English Letters) 2025年第2期38卷 313-326页

作者： Cheng Ren Xiaohua Min Sujie Zhang Weiqiang Wang School of Materials Science and Engineering Dalian University of TechnologyDalian 116024China

Ti-Mo-O alloys were used to analyze the effect of Mo and O contents on the mechanical compatibility and *** bending modulus,bending yield strength and springback ratio of the alloys were evaluated by using three-point bending tests and bending load-unloading *** biocompatibility was investigated by the adhesion,proliferation and the alkaline phosphatase(ALP)activity of mouse osteoblast-like cells(MC3T3-E1).The results showed that the bending modulus and bending yield strength first were increased and then decreased with the increase in Mo content,while the springback ratio exhibited an opposite trend to the bending *** the increase in O content,the bending modulus remained almost constant,while the bending yield strength was *** springback ratio exhibited a similar trend to the bending yield *** in vitro biological experiments showed that the Ti-Mo-O alloys had excellent biocompatibility due to the formed stable oxide films on their *** the increase in O and Mo contents,the TiO_(2)-MoO_(2)oxide film became *** with mechanical compatibility and biocompatibility,the Ti-15Mo-0.2O and Ti-15Mo-0.3O alloys were more suitable for the biomedical application of spinal fixation device.

关键词： β-type titanium alloys Bending modulus Bending yield strength Springback Biocompatibility

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A novel Co-free high-entropy alloy with excellent antimicrobial and mechanical properties

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Rare Metals 2025年第1期44卷 581-590页

作者： Wen-Yu Li Ming-Liang Wang Xiao-Di Wang Tong-Min Wang Ting-Ju Li Yi-Ping Lu Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China

Microbiologically influenced corrosion and bacterial infection lead to serious losses to human production and *** alloys with inherent antibacterial properties is a vital way to solve the above ***,the widely used Cu-containing stainless steels show insufficient antimicrobial properties and relatively low yield strengths,which further limit their application in extreme service *** on the design concept of high-entropy alloys(HEAs),a novel low-cost Co-free CrFeNi_(0.5)Cu_(0.3)HEA with an optimal combination of antibacterial and mechanical properties was designed and *** alloy comprises triple-phase structures,including FeNi-rich face-centered cubic(FCC1),Cu-rich FCC2 and FeCr-rich body-centered cubic(BCC).The antibacterial rate of this HEA is up to 99.99%against Escherichia coli,which is far superior to that of classic 304 Cu-bearing stainless steel(304-Cu SS)and the most reported antibacterial *** addition,the HEA exhibits excellent mechanical properties with a tensile strength of 1032 MPa and yield strength of 842 MPa,far surpassing the corresponding values of 304-Cu SS(i.e.,528 MPa and 210 MPa,respectively).These findings provide new insights for the development of low-cost and high-performance antibacterial alloys.

关键词： High-entropy alloy Microstructure Antibacterial property Mechanical property

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A bio-inspired broadband absorption metamaterial:Driven by dual-structure synergistically induced current vortices

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材料科学技术（英文版） 2025年第3期206卷 193-201页

作者： Yuping Duan Chenyang Xia Wei Chen Hanxiao Jia Meng Wang Yupeng Shi Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116085China

The performance breakthroughs of some stealth materials have benefited from incorporating biomimetic concepts,and the design ideas of wave-absorbing metamaterials have been greatly ***-ever,stealth materials developed based on a single biological structure still have limitations regarding overall performance and design ***,a dual-structure element combination model with a butterfly-wing porous structure and moth-eye raised structure arranged in an orderly manner is *** iron and polyurethane are mixed as wave absorbents,and the model is utilized to make a biomimetic metamaterial(CSMA),which has an absorption rate of more than 90％at 6.07-18 GHz,achieving broadband effective *** has been verified that the two biostructures designed after an ordered arrangement show synergistic effects in the combined model,and the cooperation between the structures induces the formation of current vector vortices,which are able to induce microwave losses to broaden the effective absorbing ***,the model has the combined application perfor-mance of polarization insensitivity,strong stability of oblique incidence,and low bistatic *** a thought based on the combination of multiple components provides an effective strategy for the design of broadband-absorbing metamaterials.

关键词： Bionic metamaterials Broadband stealth Current vector vortex Environmental adaptation

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Sodium alginate/carbon nanotube energy harvesting fibers:Axial functional group gradient and moist-electric performance

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材料科学技术（英文版） 2025年第5期208卷 67-77页

作者： Rui Zhang Jinxue Li Yu Yin Yonghao Chen Qifeng Huang Ping Tang Hai Wang Yuezhen Bin Department of Polymer Science and Engineering School of Chemical EngineeringDalian University of TechnologyDalian 116024China

Moist-electric generation,a green and environmentally friendly energy harvesting technology,is undoubt-edly one of the effective methods to alleviate energy shortages and environmental ***,the lack of fiber-like moist-electric generators(MEGs)that combine continuous power generation and high electrical output performance has constrained the development of moist-electric in the fields of flexi-ble wearable and self-power *** this work,sodium alginate(SA)/multi-walled carbon nanotubes(MWCNT)fibers with axial heterogeneous(axi-he)of oxygen-containing functional groups(Ocfgs)are prepared through a mold forming method in assistance with the coagulation *** interaction be-tween axi-he MEG and moisture is investigated by analyzing the electrical signal changes of dried MEG under moisture *** maximum output voltage and current of axi-he MEG can reach 0.35 V and 1.92 pA under the stimulation of *** on the regulation of Ocfgs,axi-he MEG has a con-tinuous high moist-electric performance and environmental *** maximum output power density(Pmo)of axi-he MEG with a length of only 2 cm can reach 27.37 pW cm-2 at RH=90％,which exceeds most of the MEGs reported in ***,a continuous output voltage of 0.33-0.37 V for more than 15 h can be obtained from this axi-he ***,the axi-he MEG from Ocfg distribution design and mold forming method provides a new way of clean energy generation using moisture from the ambient environment,exhibiting enormous potential in energy supply for Internet of Things(loT)devices.

关键词： Sodium alginate Multi-walled carbon nanotube Moist-electric Axial heterogeneous Fiber

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Achieving excellent mechanical properties in Mg-5Bi-3Al alloy via ultra-fine grain and high-density precipitates

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Journal of Magnesium and Alloys 2025年第2期13卷 810-822页

作者： Hongrui Li Chong Wang Yukang An Enyu Guo Shuyan Shi Fengyun Yu Zongning Chen Huijun Kang Tongmin Wang Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Ningbo Institute of Dalian University of Technology Ningbo 315000China

The development of low-cost,high-performance Mg alloys is crucial to the industrial applications of large-scale production of Mg *** this work,extruded Mg-5Bi-3Al alloy with excellent mechanical properties is successfully prepared by modifying the extrusion temperatures(240℃and 300℃).The extruded alloy obtained ultra-high strength(yield strength=380 MPa,ultimate tensile strength=418 MPa)and excellent plasticity(elongation=10.2%)at the extrusion temperature of 240℃,the main contributing factors are primarily attributed to the synergistic effect of ultrafine recrystallized grain size(~0.5µm)and high density of Mg_(3)Bi_(2)*** faults within the sub-micron Mg_(3)Bi_(2)phase are observed in the E240 alloy,confirming the plastic deformation capability of Mg_(3)Bi_(2)*** effects of extrusion temperature on the microstructure,mechanical properties,and work-hardening behavior of the extruded Mg-5Bi-3Al alloys at room temperature are systematically *** results suggest that decreasing the extrusion temperature can refine recrystallized grain size and Mg_(3)Bi_(2)phase size,and the quantity of Mg_(3)Bi_(2)phase is increased,while increasing the extrusion temperature can improve the degree of recrystallization and weaken *** work hardening rate is increased with the increased extrusion temperature,mainly due to the coarsening of grains and precipitates,and the weakening of *** work provides an experimental basis for preparing high-performance wrought Mg-5Bi-3Al alloys.

关键词： Mg-Bi-Al alloy Extrusion temperature Dynamic precipitation Mechanical property Work-hardening behavior

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