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Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

Chinese Journal of Chemical Engineering 2024年第3期67卷 182-194页

作者： Shan Liu Wenqi Zhong Li Sun Xi Chen Rafal Madonski School of Energy and Environment Key Laboratory of Energy Thermal Conversion and Control of Ministry of EducationSoutheast UniversityNanjing 210096China faculty of automatic control Electronics and Computer ScienceSilesian University of TechnologyGliwise 44-100Poland

Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal.The desulphurization control system,however,is subjected to complex reaction mechanisms and severe disturbances,which make for it difficult to achieve certain practically relevant control goals including emission and economic performances as well as system robustness.To address these challenges,a new robust control scheme based on uncertainty and disturbance estimator(UDE)and model predictive control(MPC)is proposed in this paper.The UDE is used to estimate and dynamically compensate acting disturbances,whereas MPC is deployed for optimal feedback regulation of the resultant dynamics.By viewing the system nonlinearities and unknown dynamics as disturbances,the proposed control framework allows to locally treat the considered nonlinear plant as a linear one.The obtained simulation results confirm that the utilization of UDE makes the tracking error negligibly small,even in the presence of unmodeled dynamics.In the conducted comparison study,the introduced control scheme outperforms both the standard MPC and PID(proportional-integral-derivative)control strategies in terms of transient performance and robustness.Furthermore,the results reveal that a lowpass-filter time constant has a significant effect on the robustness and the convergence range of the tracking error.

关键词： Desulphurization system Disturbance rejection Model predictive control Uncertainty and disturbance estimator Nonlinear system

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Determining an optimal control strategy for anthropogenic VOC emissions in China based on source emissions and reactivity

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Journal of Environmental Sciences 2024年第2期136卷 248-260页

作者： Ruipeng Wang Xiaoqi Wang Shuiyuan Cheng Jiaxian Zhu Xinyu Zhang Long Cheng Kai Wang Key Laboratory of Beijing on Regional Air Pollution control Faculty of Environment and LifeBeijing University of TechnologyBeijing 100124China

An evidence-based control strategy for emission reduction of VOC sources can effectively solve the regional PM2.5and O3compound pollution in China.We estimated the anthropogenic VOC emission inventory in China in 2018 and established a source profile database containing 129 sources based on localized detection and the latest research results.Then,the distribution of the ozone formation potential(OFP)and secondary organic aerosol formation potential(SOAFP)for emission sources was analyzed.Moreover,priority control routes for VOC emission sources were proposed for different periods.Anthropogenic VOC emissions in China reached 27,211.8 Gg in 2018,and small passenger cars,industrial protective coatings,biomass burning,heavy trucks,printing,asphalt paving,oil storage and transportation,coking,and oil refining were the main contributors.Industrial protective coatings,small passenger cars,and biomass burning all contributed significantly to OFP and SOAFP.Priority in emission reduction control should be given to industrial protective coatings,small passenger cars,heavy trucks,coking,printing,asphalt paving,chemical fibers,and basic organic chemical sources over the medium and long term in China.In addition,the priority control route for VOC emission sources should be adjusted according to the variations in VOC emission characteristics and regional differences,so as to obtain the maximum environmental benefits.

关键词： Volatile organic compounds Anthropogenic emission inventory Reactivity Emission projection Priority control route

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Strong Subgame Consistency of the Core in Stochastic Network Formation Games

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Journal of the Operations Research Society of China 2024年第1期12卷 189-213页

作者： Ping Sun Elena Parilina faculty of Applied Mathematics and control Processes Saint Petersburg State UniversitySaint Petersburg199034Russia

We consider a model of network formation as a stochastic game with random duration proposed initially in Sun and Parilina(Autom Remote control 82(6):1065–1082,2021).In the model,the leader first suggests a joint project to other players,i.e.,the network connecting them.Second,the players are allowed to form fresh links with each other updating the initially proposed network.The stage payoff of any player is defined depending on the network structure.There are two types of randomness in the network formation process:(i)links may fail to be formed with different probabilities although players intend to establish them,(ii)the game process may terminate at any stage or transit to the next stage with a certain probability distribution.Finally,a network is formed as a result of players’decisions and realization of random variables.The cooperative version of the stochastic game is investigated.In particular,we examine the properties of subgame consistency as well as strong subgame consistency of the core.We provide a payment mechanism or regularization of the core elements to sustain its subgame consistency and avoid the player’s deviations from the cooperative trajectory.In addition,the distribution procedure of the core elements is regularized in case there are negative payments to achieve only nonnegative payments to the players at any stage.The sufficient condition of a strongly subgame consistent core is also obtained.We illustrate our theoretical results with a numerical example.

关键词： Stochastic game Network formation Core Strong subgame consistency

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Convective drying of wood chips:Accelerating coupled DEM-CFD simulations with parametrized reduced single particle models

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Particuology 2024年第1期84卷 158-167页

作者： Lucas Reineking Jonas Fischer Ali Mjalled Enric Illana Siegmar Wirtz Viktor Scherer Martin Monnigmann automatic control and System Theory Ruhr-Universität-BochumUniversitätstraße 150Bochum44801Germany Energy Plant Technology Ruhr-Universität-BochumUniversitätstraße 150Bochum44801Germany

The simulation of industry-scale reactive bulks is challenging due to the complex interaction between fluid and particles.The particles in the bulk and their interaction with the fluid flow can be described by combined Discrete Element Method-Computational Fluid Dynamics(DEM-CFD)models.However,the computational cost of the Finite Volume(FV)methods deployed in these models can become prohibi-tively expensive,especially for high inner-particle resolution.Single particle Reduced Models(RMs)can be used to achieve both fast and accurate descriptions of the processes in each particle.As an example of bulk systems comprising heat and mass transfer,we compared FV and RM simulations for the drying of wood chips in a bulk reactor.A manifold-based nonlinear interpolation was applied to resolve changing boundary conditions for the RM.Our simulations showed that RMs provide accurate values for the thermodynamic state variables of the particles.Furthermore,the time required for the bulk simulation was reduced by 67%with the RMs.It is evident that simulations with high inner-particle resolution can be accelerated by RMs if manifold-based nonlinear interpolation is used to address changing boundary conditions.

关键词： Reduced model Reactive bulk Discrete element method Manifold-based interpolation Drying of porous mediaDEM-CFD

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Real-time UAV path planning based on LSTM network

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Journal of Systems Engineering and Electronics 2024年第2期35卷 374-385页

作者： ZHANG Jiandong GUO Yukun ZHENG Lihui YANG Qiming SHI Guoqing WU Yong School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China The Flight automatic control Research Institute of AVIC Xi’an 710065China Military Representative Office of Marine Wuhan Bureau in Luoyang Area Luoyang 471000China

To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle(UAV)real-time path planning problem,a real-time UAV path planning algorithm based on long shortterm memory(RPP-LSTM)network is proposed,which combines the memory characteristics of recurrent neural network(RNN)and the deep reinforcement learning algorithm.LSTM networks are used in this algorithm as Q-value networks for the deep Q network(DQN)algorithm,which makes the decision of the Q-value network has some memory.Thanks to LSTM network,the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment.Besides,the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning,so that the UAV can more reasonably perform path planning.Simulation verification shows that compared with the traditional feed-forward neural network(FNN)based UAV autonomous path planning algorithm,the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.

关键词： deep Q network path planning neural network unmanned aerial vehicle(UAV) long short-term memory(LSTM)

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LFM Radar Source Passive Localization Algorithm Based on Range Migration

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Journal of Beijing Institute of Technology 2024年第2期33卷 130-140页

作者： Dandan Li Deyi Wang Hao Huan Beijing Key Laboratory of Fractional Signals and Systems School of Information and ElectronicsBeijing Institute of TechnologyBeijing 100081China Beijing Aerospace automatic control Institute Beijing 100854China

Traditional single-satellite passive localization algorithms are influenced by frequency and angle measurement accuracies,resulting in error estimation of emitter position on the order of kilometers.Subsequently,a single-satellite localization algorithm based on passive synthetic aper-ture(PSA)was introduced,enabling high-precision positioning.However,its estimation of azimuth and range distance is considerably affected by the residual frequency offset(RFO)of uncoopera-tive system transceivers.Furthermore,it requires data containing a satellite flying over the radia-tion source for RFO search.After estimating the RFO,an accurate estimation of azimuth and range distance can be carried out,which is difficult to achieve in practical situations.An LFM radar source passive localization algorithm based on range migration is proposed to address the dif-ficulty in estimating frequency offset.The algorithm first provides a rough estimate of the pulse repetition time(PRT).It processes intercepted signals through range compression,range interpola-tion,and polynomial fitting to obtain range migration observations.Subsequently,it uses the changing information of range migration and an accurate PRT to formulate a system of nonlinear equations,obtaining the emitter position and a more accurate PRT through a two-step localization algorithm.Frequency offset only induces a fixed offset in range migration,which does not affect the changing information.This algorithm can also achieve high-precision localization in squint scenar-ios.Finally,the effectiveness of this algorithm is verified through simulations.

关键词： passive localization range migration residual frequency offset

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A new scheme of PM_(2.5)and O_(3) control strategies with the integration of SOM,GA and WRF-CAMx

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Journal of Environmental Sciences 2024年第4期138卷 249-265页

作者： Wenjiao Duan Xiaoqi Wang Shuiyuan Cheng Ruipeng Wang Key Laboratory of Beijing on Regional Air Pollution control Faculty of Environment and LifeBeijing University of TechnologyBeijing 100124China

Previous air pollution control strategies didn’t pay enough attention to regional collaboration and the spatial response sensitivities,resulting in limited control effects in China.This study proposed an effective PM_(2.5)and O_(3) control strategy scheme with the integration of Self-Organizing Map(SOM),Genetic Algorithm(GA)and WRF-CAMx,emphasizing regional collaborative control and the strengthening of control in sensitive areas.This scheme embodies the idea of hierarchical management and spatial-temporally differentiated management,with SOM identifying the collaborative subregions,GA providing the optimized subregion-level priority of precursor emission reductions,and WRF-CAMx providing response sensitivities for grid-level priority of precursor emission reductions.With Beijing-Tianjin-Hebei and the surrounding area(BTHSA,“2+26”cities)as the case study area,the optimized strategy required that regions along Taihang Mountains strengthen the emission reductions of all precursors in PM_(2.5)-dominant seasons,and strengthen VOCs reductions but moderate NOx reductions in O_(3)-dominant season.The spatiotemporally differentiated control strategy,without additional emission reduction burdens than the 14th Five-Year Plan proposed,reduced the average annual PM_(2.5)and MDA8 O_(3) concentrations in 28 cities by 3.2%-8.2% and 3.9%-9.7% respectively in comparison with non-differential control strategies,with the most prominent optimization effects occurring in the heavily polluted seasons(6.9%-18.0%for PM_(2.5)and 3.3%-14.2% for MDA8 O_(3),respectively).This study proposed an effective scheme for the collaborative control of PM_(2.5)and O_(3) in BTHSA,and shows important methodological implications for other regions suffering from similar air quality problems.

关键词： PM_(2.5)and O_(3)control SOM GA WRF-CAMx Bionic algorithm Machine learning

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Hierarchically Distributed Optimization with a Flexible and Complexity-Reducing Algorithm

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Journal of Systems Science & Complexity 2024年

作者： LIANG Shu ZHANG Lei WEI Yiheng LIU Yemo 1.Department of control Science and Engineering, Tongji University 2.Shanghai Research Institute for Intelligent Autonomous Systems 3.School of Mathematics, Southeast University 4.Beijing Aerospace automatic control Institute Department of control Science and Engineering Tongji University Shanghai Research Institute for Intelligent Autonomous Systems School of Mathematics Southeast University Beijing Aerospace automatic control Institute

In this paper, the authors consider distributed convex optimization over hierarchical networks. The authors exploit the hierarchical architecture to design specialized distributed algorithms so that the complexity can be reduced compared with that of non-hierarchically distributed algorithms.To this end, the authors use local agents to process local functions in the same manner as other distributed algorithms that take advantage of multiple agents' computing resources. Moreover, the authors use pseudocenters to directly integrate lower-level agents' computation results in each iteration step and then share the outcomes through the higher-level network formed by pseudocenters. The authors prove that the complexity of the proposed algorithm exponentially decreases with respect to the total number of pseudocenters. To support the proposed decomposition-composition method for agents and pseudocenters, the authors develop a class of operators. These operators are generalizations of the widely-used subgradient based operator and the proximal operator and can be used in distributed convex optimization. Additionally, these operators are closed with respect to the addition and composition operations; thus, they are suitable to guide hierarchically distributed design and analysis. Furthermore,these operators make the algorithm flexible since agents with different local functions can adopt suitable operators to simplify their calculations. Finally, numerical examples also illustrate the effectiveness of the method.

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All laser direct writing process for temperature sensor based on graphene and silver

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Frontiers of Optoelectronics 2024年第1期17卷 45-55页

作者： Qi Li Ruijie Bai Lianbo Guo Yang Gao Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power EngineeringEast China University of Science and TechnologyShanghai 200237China North automatic control Technology Institute Taiyuan 030006China Wuhan National Laboratory for Optoelectronics Huazhong University of Science&TechnologyWuhan 430074China

A highly sensitive temperature sensing array is prepared by all laser direct writing(LDW)method,using laser induced silver(LIS)as electrodes and laser induced graphene(LIG)as temperature sensing layer.A finite element analysis(FEA)photothermal model incorporating a phase transition mechanism is developed to investigate the relationship between laser parameters and LIG properties,providing guidance for laser processing parameters selection with laser power of 1–5 W and laser scanning speed(greater than 50 mm/s).The deviation of simulation and experimental data for widths and thickness of LIG are less than 5%and 9%,respectively.The electrical properties and temperature responsiveness of LIG are also studied.By changing the laser process parameters,the thickness of the LIG ablation grooves can be in the range of 30–120μm and the resistivity of LIG can be regulated within the range of 0.031–67.2Ω・m.The percentage temperature coefficient of resistance(TCR)is calculated as−0.58%/°C.Furthermore,the FEA photothermal model is studied through experiments and simulations data regarding LIS,and the average deviation between experiment and simulation is less than 5%.The LIS sensing samples have a thickness of about 14μm,an electrical resistivity of 0.0001–100Ω・m is insensitive to temperature and pressure stimuli.Moreover,for a LIS-LIG based temperature sensing array,a correction factor is introduced to compensate for the LIG temperature sensing being disturbed by pressure stimuli,the temperature measurement difference is decreased from 11.2 to 2.6°C,indicating good accuracy for temperature measurement.

关键词： Laser direct writing Temperature sensor Finite element analysis Laser induced graphene Laser induced silver

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Wireless Power Supply Based on MNG-MNZ Metamaterial for Cardiac Pacemakers

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CES Transactions on Electrical Machines and Systems 2024年第1期8卷 103-112页

作者： Weihua Chen Jingtao Jia Xiaoheng Yan Yuhang Song Jiayi Li faculty of Electrical and control Engineering Liaoning Technical UniversityNo.188Longwan South StreetXingchengHuludao 125105China CES

To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative(MNG) and mu-nearzero(MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted.Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%,19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81%and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm,respectively. The maximum SAR acquired by SAR simulation under human body environment was-7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85℃,and the safety requirements of human bodies were met.

关键词： Cardiac pacemaker MNG metamaterial MNZ metamaterial Wireless power supply system

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