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Enhanced adaptive nonlinear extended state observer for pure feedback systems with matched and mismatched disturbances

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Control Theory and Technology 2024年第2期22卷 254-268页

作者： Mahtab Delpasand Mohammad Farrokhi School of Electrical engineering Iran University of Science and TechnologyTehran16846-13114Iran center of excellence for Modelling and Control of Complex systems Iran University of Science and TechnologyTehran16846-13114Iran

In this paper, an enhanced adaptive nonlinear extended state observer (EANESO) for single-input single-output pure feedback systems in the presence of external time-varying disturbances is proposed. In this paper, a nonlinear system with matched and mismatched disturbances is considered. The conventional extended state observer (ESO) can only be applied to systems that are in the form of integral chains. Moreover, this method has limitations in the face of mismatched disturbances. In the presence of time-varying disturbances, the traditional ESOs cannot estimate the disturbances accurately. To overcome this limitation, an EANESO is proposed in this paper. The main idea is to design the nonlinear ESO (NESO) to estimate the states of the system and multiple disturbances simultaneously. The observer gains are considered time-varying and adjusted with adaptation laws to improve the estimation accuracy and overcome the peaking phenomenon. Next, the proposed controller is designed based on output feedback to eliminate the effects of multiple disturbances and stabilize the closed-loop system. Subsequently, the stability analysis of the closed-loop system and convergence of the observer error are discussed. Finally, the proposed method is applied to the inverted pendulum system. The simulated results show good performance of the proposed method as compared with a recently published scheme in the related literature.

关键词： Nonlinear extended state observer Enhanced adaptive extended state observer Adaptation law Multiple-channel disturbances Inverted pendulum system Time-varying gain

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Intelligent ion gels: Design, performance, and applications

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SmartMat 2024年第1期5卷 38-58页

作者： Naiwei Gao Caofeng Pan Beijing Key Laboratory of Micro‐nano Energy and Sensor CAS Center for Excellence in NanoscienceBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijingChina Key Laboratory of Optoelectronic Devices and systems of Ministry of Education Center for Stretchable Electronics and Nano SensorsCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhenChina School of Nanoscience and engineering University of Chinese Academy of SciencesBeijingChina

Intelligent ion gels,which possess highly tunable mechanical,electrical,and stimulus‐responsive properties,have emerged as powerful candidates in the field of artificial intelligence,telemedicine,and health monitoring.To enrich the functionality of ion gels,it is critical to explore the link between the structure and function of ion gels.In this review,we provide an overview of the synthesis path and functional derivatives of ion gels.The conformational relationships of ion gels have been discussed,such as the effect of structure on electrical conductivity as well as sensing properties.From the perspective of stimulus response,the role of ion gels in areas such as bionic haptics,neural devices,artificial muscles,and intelligent displays has also been explored.It is possible that smart ion gels will open up a new horizon in the upcoming smart era,especially after the current challenges are resolved.

关键词： chemical structure intelligent electronics ion gels stimulus‐responsive

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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of systems engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and engineering Northeastern UniversityShenyang 110819China center of Research excellence in Renewable Energy and Power systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization problems.The past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer simulations.Moreover,it is hard to traverse the huge search space within reasonable resource as problem dimension increases.Traditional evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory results.To reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent years.Yet there lacks a thorough review of the state of the art in this specific and important area.This paper provides a comprehensive survey of these evolutionary algorithms for HEPs.We start with a brief introduction to the research status and the basic concepts of HEPs.Then,we present surrogate-assisted evolutionary algorithms for HEPs from four main aspects.We also give comparative results of some representative algorithms and application examples.Finally,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Photoionisation detection of a single Er3+ ion with sub-100-ns time resolution

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National Science Review 2024年第4期11卷 38-45页

作者： Yangbo Zhang Wenda Fan Jiliang Yang Hao Guan Qi Zhang Xi Qin Changkui Duan Gabriele G.de Boo Brett C.Johnson Jeffrey C.Mc Callum Matthew J.Sellars Sven Rogge Chunming Yin Jiangfeng Du CAS Key Laboratory of Microscale Magnetic Resonance and School of Physical Sciences University of Science and Technology of China CAS center for excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei National Laboratory University of Science and Technology of China Centre of excellence for Quantum Computation and Communication Technology School of Physics University of New South Wales Centre of excellence for Quantum Computation and Communication Technology School of Engineering RMIT University Centre of excellence for Quantum Computation and Communication Technology School of Physics University of Melbourne Centre of excellence for Quantum Computation and Communication Technology Research School of Physics and Engineering Australian National University

Efficient detection of single optical centres in solids is essential for quantum information processing, sensing and single-photon generation applications.In this work,we use radio-frequency（RF） reflectometry to electrically detect the photoionisation induced by a single Er3+ion in Si.The high bandwidth and sensitivity of the RF reflectometry provide sub-100-ns time resolution for the photoionisation detection.With this technique,the optically excited state lifetime of a single Er3+ion in a Si nano-transistor is measured for the first time to be 0.49±0.04μs.Our results demonstrate an efficient approach for detecting a charge state change induced by Er excitation and relaxation.This approach could be used for fast readout of other single optical centres in solids and is attractive for large-scale integrated optical quantum systems thanks to the multi-channel RF reflectometry demonstrated with frequency multiplexing techniques.

关键词： single optical centres erbium ions RF reflectometry photoionisation detection

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer Modeling in engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan Ibrahim M.Mehedi Shaikh Abdul Latif Md.Masud Rana Department of Electrical and Computer engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia center of excellence in Intelligent engineering systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry 4.0.Specifically, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of processes.Fault diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel accurately.The experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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Impact Analysis of Microscopic Defect Types on the Macroscopic Crack Propagation in Sintered Silver Nanoparticles

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Computer Modeling in engineering & Sciences 2024年第4期139卷 441-458页

作者： Zhongqing Zhang Bo Wan Guicui Fu Yutai Su Zhaoxi Wu Xiangfen Wang Xu Long School of Reliability and systems engineering Beihang UniversityBeijing100191China School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi’an710072China China Aerospace Components engineering center Beijing100098China

Sintered silver nanoparticles(AgNPs)arewidely used in high-power electronics due to their exceptional properties.However,the material reliability is significantly affected by various microscopic defects.In this work,the three primary micro-defect types at potential stress concentrations in sintered AgNPs are identified,categorized,and quantified.Molecular dynamics(MD)simulations are employed to observe the failure evolution of different microscopic defects.The dominant mechanisms responsible for this evolution are dislocation nucleation and dislocation motion.At the same time,this paper clarifies the quantitative relationship between the tensile strain amount and the failure mechanism transitions of the three defect types by defining key strain points.The impact of defect types on the failure process is also discussed.Furthermore,traction-separation curves extracted from microscopic defect evolutions serve as a bridge to connect the macro-scale model.The validity of the crack propagation model is confirmed through tensile tests.Finally,we thoroughly analyze how micro-defect types influence macro-crack propagation and attempt to find supporting evidence from the MD model.Our findings provide a multi-perspective reference for the reliability analysis of sintered AgNPs.

关键词： Sintered silver nanoparticles defect types microscopic defect evolution macroscopic crack propagation molecular dynamics simulation cohesive zone model

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A near-zero quiescent power breeze wake-up anemometer based on a rolling-bearing triboelectric nanogenerator

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Microsystems & Nanoengineering 2024年第2期10卷 241-249页

作者： Xianpeng Fu Zhichao Jiang Jie Cao Zefang Dong Guoxu Liu Meiling Zhu Chi Zhang CAS center for excellence in Nanoscience Beijing Key Laboratory of Micro-nano Energy and SensorBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing101400China School of Nanoscience and engineering University of Chinese Academy of SciencesBeijing100049China center on Nanoenergy Research Guangxi Colleges and Universities Key Laboratory of Blue Energy and Systems IntegrationSchool of Physical Science&TechnologyGuangxi UniversityNanning530004China Institute of Intelligent Flexible Mechatronics Jiangsu UniversityZhenjiang212013China College of engineering Mathematics and Physical ScienceUniversity of ExeterExeterEX44QFUK

Wind sensors have always played an irreplaceable role in environmental information monitoring and are expected to operate with lower power consumption to extend service lifetime.Here,we propose a breeze wake-up anemometer(B-WA)based on a rolling-bearing triboelectric nanogenerator(RB-TENG)with extremely low static power.The B-WA consists of two RB-TENGs,a self-waking-up module(SWM),a signal processing module(SPM),and a wireless transmission unit.The two RB-TENGs are employed for system activation and wind-speed sensing.Once the ambient wind-speed exceeds 2 m/s,the wake TENG(W-TENG)and the SWM can wake up the system within 0.96 s.At the same time,the SPM starts to calculate the signal frequency from the measured TENG(M-TENG)to monitor the wind speed with a sensitivity of 9.45 Hz/(m/s).After the wind stops,the SWM can switch off the B-WA within 0.52 s to decrease the system energy loss.In quiescent on-duty mode,the operating power of the B-WA is less than 30 nW,which can greatly extend the service lifetime of the B-WA.By integrating triboelectric devices and rolling bearings,this work has realized an ultralow quiescent power and self-waked-up wireless wind-speed monitoring system,which has foreseeable applications in remote weather monitoring,IoT nodes,and so on.

关键词： generator power service

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Microscopic nonlinear optical activities and ultrafast carrier dynamics in layered AgInP_(2)S_(6)

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Photonics Research 2024年第4期12卷 691-700页

作者： ZIXIN WANG NINGNING DONG YU MAO CHENDUAN CHEN XIN CHEN CHANG XU ZHOUYUAN YAN JUN WANG Aerospace Laser Technology and systems Department CAS Key Laboratory of Materials for High-Power LaserShanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China center of Materials Science and Optoelectronics engineering University of Chinese Academy of SciencesBeijing 100049China CAS center for excellence in Ultra-intense Laser Science(CEULS) State Key Laboratory of High Field Laser PhysicsShanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China

Since the emergence of graphene, transition metal dichalcogenides, and black phosphorus, two-dimensional materials have attracted significant attention and have driven the development of fundamental physics and optoelectronic devices. Metal phosphorus trichalcogenides(MPX3), due to their large bandgap of 1.3–3.5 eV, enable the extension of optoelectronic applications to visible and ultraviolet(UV) wavelengths.

关键词： nonlinear ultraviolet phosphorus

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Mechanistic modeling of copper corrosions in data center environments

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Building Simulation 2024年第3期17卷 483-492页

作者： Rui Zhang Jianshun Zhang Roger Schmidt Jeremy L.Gilbert Department of Mechanical and Aerospace engineering College of Engineering and Computer ScienceSyracuse UniversitySyracuseNY13244USA Buildings and Transportation Science Division Oak Ridge National LaboratoryOak RidgeTN37830USA SyracuseCoE-New York center of excellence in Environmental and Energy systems Syracuse University727 E.Washington StreetSyracuseNY13244USA Department of Bioengineering Clemson UniversityClemson-Medical University of South Carolina Bioengineering ProgramCharlestonSC29425USA

Air-side economizers are increasingly used to take advantage of“free-cooling”in data centers with the intent of reducing the carbon footprint of buildings.However,they can introduce outdoor pollutants to indoor environment of data centers and cause corrosion damage to the information technology equipment.To evaluate the reliability of information technology equipment under various thermal and air-pollution conditions,a mechanistic model based on multi-ion transport and chemical reactions was developed.The model was used to predict Cu corrosion caused by Cl_(2)-containing pollutant mixtures.It also accounted for the effects of temperature(25℃and 28℃),relative humidity(50%,75%,and 95%),and synergism.It also identified higher air temperature as a corrosion barrier and higher relative humidity as a corrosion accelerator,which agreed well with the experimental results.The average root mean square error of the prediction was 13.7Å.The model can be used to evaluate the thermal guideline for data centers design and operation when Cl_(2)is present based on pre-established acceptable risk of corrosion in data centers’environment.

关键词： chloride pollutant mixture copper corrosion model data center temperature relative humidity synergistic effect

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Computational and dark-field ghost imaging with ultraviolet light

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Photonics Research 2024年第2期12卷 226-234页

作者： JIAQI SONG BAOLEI LIU YAO WANG CHAOHAO CHEN XUCHEN SHAN XIAOLAN ZHONG LING-AN WU FAN WANG School of Physics Beihang UniversityBeijing 102206China Australian Research Council Centre of excellence for Transformative Meta-Optical systems Department of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT 2600Australia Institute of Physics Chinese Academy of SciencesBeijing 100190China

Ultraviolet(UV)imaging enables a diverse array of applications,such as material composition analysis,biological fluorescence imaging,and detecting defects in semiconductor manufacturing.However,scientific-grade UV cameras with high quantum efficiency are expensive and include complex thermoelectric cooling systems.Here,we demonstrate a UV computational ghost imaging(UV-CGI)method to provide a cost-effective UV imaging and detection strategy.By applying spatial–temporal illumination patterns and using a 325 nm laser source,a singlepixel detector is enough to reconstruct the images of objects.We use UV-CGI to distinguish four UV-sensitive sunscreen areas with different densities on a sample.Furthermore,we demonstrate dark-field UV-CGI in both transmission and reflection schemes.By only collecting the scattered light from objects,we can detect the edges of pure phase objects and small scratches on a compact disc.Our results showcase a feasible low-cost solution for nondestructive UV imaging and detection.By combining it with other imaging techniques,such as hyperspectral imaging or time-resolved imaging,a compact and versatile UV computational imaging platform may be realized for future applications.

关键词： ghost illumination versatile

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