DO we need a fundamental change in our professional culture and knowledge foundation for control and automation?If so,what are necessary and critical steps we must take to ensure such a change would take place effecti...
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DO we need a fundamental change in our professional culture and knowledge foundation for control and automation?If so,what are necessary and critical steps we must take to ensure such a change would take place effectively and efficiently,or more general,smoothly and sustainably?
Air pollution is one of the most challenging environmental issues in the *** has achieved remarkable success in improving air quality in last decade as a result of aggressive air pollution control ***,the average fine...
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Air pollution is one of the most challenging environmental issues in the *** has achieved remarkable success in improving air quality in last decade as a result of aggressive air pollution control ***,the average fine particulate matter(PM2.5)concentration in China is still about six times of the World Health Organization(WHO)Global Air Quality Guidelines(AQG)and causing significant human health *** emission reductions of multiple air pollutants are required for China to achieve the *** we identify the major challenges in future air quality improvement and propose corresponding control *** main challenges include the persistently high health risk attributed to PM2.5 pollution,the excessively loose air quality standards,and coordinated control of air pollution,greenhouse gases(GHGs)emissions and emerging *** further improve air quality and protect human health,a health-oriented air pollution control strategy shall be implemented by tightening the air quality standards as well as optimizing emission reduction pathways based on the health risks of various *** the meantime,an“oneatmosphere”concept shall be adopted to strengthen the synergistic control of air pollutants and GHGs and the control of non-combustion sources and emerging pollutants shall be enhanced.
In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence ***,there is,currently,near...
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In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence ***,there is,currently,nearly no standard technical framework for objective and quantitative intelligence *** this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation *** this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment *** results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.
Dear Editor,Modeling is the first and essential step for control and automation,and large models,from current Chat GPT or large language models(LLMs)to future large knowledge models of knowledge automation,would be th...
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Dear Editor,Modeling is the first and essential step for control and automation,and large models,from current Chat GPT or large language models(LLMs)to future large knowledge models of knowledge automation,would be the foundation model and infrastructure intelligence for coming intelligent industries and smart societies.
作者:
Wei, QinglaiLi, HongyangLi, TaoWang, Fei-YueChinese Acad Sci
Inst Automation State Key Lab Management & Control Complex Syst Beijing Peoples R China Chinese Acad Sci
Inst Automation State Key Lab Management & Control Complex Syst Beijing Peoples R China Chinese Acad Sci
Inst Automation State Key Lab Management & Control Complex Syst Beijing Peoples R China Chinese Acad Sci
Inst Automation State Key Lab Management & Control Complex Syst Beijing Peoples R China
This article presents a novel data-based fault-tolerant control method for multicontroller linear systems via distributed policy iteration. The traditional fault-tolerant control methods based on policy iteration may ...
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This article presents a novel data-based fault-tolerant control method for multicontroller linear systems via distributed policy iteration. The traditional fault-tolerant control methods based on policy iteration may cause a huge-computational burden under the situation of high-dimension control laws. In order to solve this problem, a novel distributed policy iteration method is presented, where only one iterative control law is updated in each iteration, to realize the fault-tolerant control of multicontroller linear systems. The main contributions can be highlighted as follows: 1) a novel data-based distributed policy iteration method is presented to reduce the computational burden;2) the fault-tolerant control method is presented via designing fault compensators;and 3) the developed data-based method only requires the partial system information. First, the model-based fault-tolerant control via distributed policy iteration and fault compensation is provided. Based on the model-based method, a data-based fault-tolerant control method is presented. Finally, numerical experiments are given to show the performance of the presented method.
The lockdown policy deals a severe blow to the economy and greatly reduces the nitrogen oxides(NOx)emission in China when the coronavirus 2019 spreads widely in early *** we use satellite observations from Tropospheri...
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The lockdown policy deals a severe blow to the economy and greatly reduces the nitrogen oxides(NOx)emission in China when the coronavirus 2019 spreads widely in early *** we use satellite observations from Tropospheric Monitoring Instrument to study the year-round variation of the nitrogen dioxide(NO_(2))tropospheric vertical column density(TVCD)in *** NO_(2)TVCD reveals a sharp drop,followed by small fluctuations and then a strong rebound when compared to *** the end of 2020,the annual average NO_(2)TVCD declines by only 3.4%in Chinamainland,much less than the reduction of 24.1%in the lockdown *** the basis of quantitative analysis,we find the rebound of NO_(2)TVCD is mainly caused by the rapid recovery of economy especially in the fourth quarter,when contribution of industry and power plant on NO_(2)TVCD continues to *** revenge bounce of NO_(2)indicates the emission reduction of NOx in lockdown period is basically offset by the recovery of economy,revealing the fact that China’s economic development and NOx emissions are still not *** efforts are still required to stimulate low-pollution development.
In order to comprehensively evaluate the environmental impact of multi-media mercury pollution under differentiated emission control strategies in China,a literature review and case studies were carried *** human expo...
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In order to comprehensively evaluate the environmental impact of multi-media mercury pollution under differentiated emission control strategies in China,a literature review and case studies were carried *** human exposure to methylmercury was assessed through the dietary intake of residents in areas surrounding a typical coal-fired power plant and a zinc(Zn)smelter,located either on acid soil with paddy growth in southern China,or on alkaline soil with wheat growth in northern *** with knowledge on speciated mercury in flue gas and the fate of mercury in the wastewater or solid waste of the typical emitters applying different air pollution control devices,a simplified model was developed by estimating the incremental daily intake of methylmercury from both local and global *** indicated that air pollution control for coal-fired power plants and Zn smelters can greatly reduce health risks from mercury pollution,mainly through a reduction in global methylmercury exposure,but could unfortunately induce local methylmercury exposure by transferring more mercury from flue gas to wastewater or solid waste,then contaminating surrounding soil,and thus increasing dietary intake via ***,tightening air emission control is conducive to reducing the comprehensive health risk,while the environmental equity between local and global pollution control should be fully *** in the south tends to have higher bioconcentration factors than wheat in the north,implying the great importance of strengthening local pollution control in the south,especially for Zn smelters with higher contribution to local pollution.
Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties ...
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Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced ***, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.
Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O3and PM2.5and the emissions of their ***,the challenge is that precursor reduction does no...
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Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O3and PM2.5and the emissions of their ***,the challenge is that precursor reduction does not necessarily lead to decreases in the concentrations of O3and PM2.5,which are formed by multiple precursors under complex physical and chemical processes;this calls for the development of advanced model technologies to provide accurate predictions of the nonlinear responses of air quality to *** from the traditional sensitivity analysis and source apportionment methods,the reduced form models(RFMs)based on chemical transport models(CTMs)are able to quantify air quality responses to emissions more accurately and efficiently with lower computational *** we review recent approaches used in RFMs and compare their structures,advantages and disadvantages,performance and *** general,RFMs are classified into three types including(1)sensitivity-based models,(2)models with simplified chemistry and physical processes,and(3)statistical models,with considerable differences in principles,characteristics and application *** prediction of nonlinear responses by RFMs enables more in-depth analysis,not only in terms of real-time prediction of concentrations and quantification of human exposure,health impacts and economic damage,but also in optimizing control ***,data assimilation and emission inventory inversion based on the nonlinear response of concentrations to emissions can also be greatly beneficial to air pollution control *** future studies,improvement in the performance of CTMs is exceedingly crucial to obtain a more reliable baseline for the prediction of air quality *** of models to determine the air quality response to emissions under varying meteorological conditions is also necessary in the context of future climate changes,which pose great challenges to the qua
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