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IEEE Conference on Decision and control

作者： Chencheng Xu Chengcheng Zhao Zhiguo Shi Jiming Chen College of Information Science and Electronic Engineering Zhejiang University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province and Interdisciplinary Motion Dynamics Emulation Platform Zhejiang University Hangzhou China

Compared to safe obstacle avoidance in the position space, ensuring the safety of the attitude system in today's aerial vehicle operations is more challenging due to the non-Euclidean nature of the attitude space and the underactuated nature of the system. To address this issue, we first propose the geometric exponential barrier condition (GEBC) to produce barrier certificates on the manifold, by which attitude safety requirements can be encoded globally into the verification problems of attitude control systems. Then, we use exponential coordinates to characterize GEBCs, which makes them describable in terms of quantifier-free real arithmetic logic (QF-NRA) and efficiently solvable by current satisfiability modulo theories (SMT) solvers. A performance criterion is further discussed where we propose an effective algorithm to construct safe operational regions with different controllers, which can help with nominal controller selection and tuning. Finally, we demonstrate our approach in a quadrotor system and analyze the safe performance of two PD controllers on the proposed safe operation criterion.

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A Collaborative Robot Torque Prediction Method Based on CNN-TCN Model

A Collaborative Robot Torque Prediction Method Based on CNN-...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Lina Tong Decheng Cui Chen Wang Liang Peng School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems (SKLMCCS) Institute of Automation Chinese Academy of Science Beijing China

The traditional dynamical models show lower accuracy when predicting joint movement, and should be compensated. This paper proposed a model combined with the convolutional network(CNN) and temporal convolutional network(TCN) to compensate for the joint torque prediction values that are calculated from the sensing information. The experiments on the Cooperative Universal Robotic Assistant 6 DoF(CURA6) open dataset, including multi-load and multi-velocity, showed the prediction error can be reduced by 20% compared to other network models. Since there are many kinds of joint movement information, the input data form of the deep learning model should be improved. Thus, the kinetic linearization model is proposed to modify the input of sensing data. According to the different motion types of the CURA6 dataset, comparative experiments were taken, and the mean absolute error was less than 6.8%.

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Self-Enhanced Oxidation of Fluoroquinolone Antibiotics by Cuii/Peroxymonosulfate: Copper Coordination Mechanism with Antibiotics

SSRN

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SSRN 2024年

作者： Zhao, Qing Chen, Long Wang, Zhiqiang Zhou, Lei Gong, Xueqing Xiu, Guangli Shanghai Environmental Protection Key Laboratory for Environmental Standard and Risk Management of Chemical Pollutants School of Resources & Environmental Engineering East China University of Science and Technology Shanghai200237 China State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes School of Resources & Environmental Engineering East China University of Science and Technology Shanghai200237 China State Key Laboratory of Green Chemical Engineering and Industrial Catalysis Centre for Computational Chemistry Research Institute of Industrial Catalysis School of Chemistry and Molecular Engineering East China University of Science and Technology Shanghai200237 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

Trace copper ions are commonly found in different water bodies. They can effectively promote the degradation of various pollutants by peroxymonosulfate (PMS). However, the underlying mechanism of copper's action has not yet been clarified. Fluoroquinolone antibiotics (FQs), which are commonly used in humans and animals, often coexisting with copper metal in environmental waters, especially in aquaculture and medical wastewater. The presence of CuII under neutral conditions is found to significantly enhance the degradation efficiency of FQs by PMS. The coordination of CuII with FQs plays a crucial role in this process. Taking pefloxacin (PE), one typical FQs as an example, the structure of the copper complexes was determined using UV-visible spectroscopy, fluorescence spectroscopy, and DFT calculations as [Cu (PE) (H2O)4]2+. Comprehensive quenching experiments and electron paramagnetic resonance (EPR) test indicated that high-valence copper was responsible for the accelerated degradation. The combined results, including PMS decay and DFT calculations, indicated that CuII is initially reduced to CuI at a relatively slow rate and then rapidly oxidized to CuIII in the presence of PMS. The results highlight the valence transition of CuII/CuI/CuIII experienced during PMS activation, and the crucial role of contaminant-metal coordination in the valence transformation of copper. © 2024, The Authors. All rights reserved.

关键词： Copper compounds

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Self-Enhanced Oxidation of Fluoroquinolone Antibiotics by Cuii/Peroxymonosulfate: Copper Coordination Mechanism with Antibiotics

SSRN

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SSRN 2024年

作者： Zhao, Qing Chen, Long Wang, Zhiqiang Gong, Xueqing Zhou, Lei Xiu, Guangli Shanghai Environmental Protection Key Laboratory for environmental standard and risk management of chemical pollutants School of Resources & Environmental Engineering East China University of Science and Technology Shanghai200237 China State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes School of Resources & Environmental Engineering East China University of Science and Technology Shanghai200237 China State Key Laboratory of Green Chemical Engineering and Industrial Catalysis Centre for Computational Chemistry Research Institute of Industrial Catalysis School of Chemistry and Molecular Engineering East China University of Science and Technology Shanghai200237 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

关键词： Copper compounds

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No tillage increases soil microarthropod(Acari and Collembola)abundance at the global scale

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Soil Ecology Letters 2024年第2期6卷 5-19页

作者： Yulin Liu Lihong Song Donghui Wu Zihan Ai Qian Xu Xin Sun Liang Chang State Key Laboratory of Black Soil Conservation and Utilization Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun130102China University of Chinese Academy of Sciences Beijing100049China College of Agriculture Guizhou UniversityGuiyang550025China Key Laboratory of Urban Environment and Health Ningbo Observation and Research StationFujian Key Laboratory of Watershed EcologyInstitute of Urban EnvironmentChinese Academy of SciencesXiamen361021China Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control CAS Haixi Industrial Technology Innovation Center in BeilunNingbo315830China

Conservation tillage increases soil microarthropod abundance at the global *** effect of conservative tillage on microarthropods is soil *** positive effect of conservation tillage is particularly evident in nutrient-poor soil *** temperate humid regions,however,this positive effect of conservation tillage is *** effect of conservative tillage on microarthropods varies with fauna group and climate regions.

关键词： no tillage soil microarthropod Acari Collembola meta-analysis

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Data-Driven Based Fault Prognosis for industrial systems:A Concise Overview

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 330-345页

作者： Kai Zhong Min Han Bing Han Faculty of Electronic Information and Electrical Engineering Dalian University of TechnologyDalian 116024China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of TechnologyDalian 116024China State Key Laboratory of Navigation and Safety Technology Shanghai Ship and Shipping Research InstituteShanghai 200135China

Fault prognosis is mainly referred to the estimation of the operating time before a failure occurs,which is vital for ensuring the stability,safety and long lifetime of degrading industrial *** to the results of fault prognosis,the maintenance strategy for underlying industrial systems can realize the conversion from passive maintenance to active *** the increased complexity and the improved automation level of industrial systems,fault prognosis techniques have become more and more ***,the datadriven based prognosis approaches,which tend to find the hidden fault factors and determine the specific fault occurrence time of the system by analysing historical or real-time measurement data,gain great attention from different industrial *** this context,the major task of this paper is to present a systematic overview of data-driven fault prognosis for industrial ***,the characteristics of different prognosis methods are revealed with the data-based ones being ***,based on the different data characteristics that exist in industrial systems,the corresponding fault prognosis methodologies are illustrated,with emphasis on analyses and comparisons of different prognosis ***,we reveal the current research trends and look forward to the future challenges in this *** review is expected to serve as a tutorial and source of references for fault prognosis researchers.

关键词： Data-driven fault prognosis feature extraction industrial systems

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Risk-Aware Objective-Based Forecasting in Inertia Management

arXiv

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arXiv 2023年

作者： Zhang, Haipeng Li, Ran Chen, Yan Chu, Zhongda Sun, Mingyang Teng, Fei The Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai Non-Carbon Energy Conversion Utilization Institute Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Zhejiang University Hangzhou310027 China The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom

-The objective-based forecasting considers the asymmetric and non-linear impacts of forecasting errors on decision objectives, thus improving the effectiveness of its downstream decision-making process. However, existing objective-based forecasting methods are risk-neutral and not suitable for tasks like power system inertia management and unit commitment, of which decision-makers are usually biased toward risk aversion in practice. To tackle this problem, this paper proposes a generic risk-aware objective-based forecasting method. It enables decision-makers to customize their forecasting with different risk preferences. The equivalence between the proposed method and optimization under uncertainty (stochastic/robust optimization) is established for the first time. Case studies are carried out on a Great Britain 2030 power system with system operational data from National Grid. The results show that the proposed model with deterministic optimization can approximate the performance of stochastic programming or robust optimization at only a fraction of their computational cost. © 2023, CC BY.

关键词： Forecasting

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Distributed Cooperative Search Method for Multi-Uav with Unstable Communications

SSRN

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SSRN 2023年

作者： Zhang, Huaqing Ma, Hongbin Mersha, Bemnet Wondimagegnehu Zhang, Xiaofei Jin, Ying School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Beijing100081 China School of Vehicle and Mobility Tsinghua University Beijing100084 China

In search-attack and search-rescue tasks performed by multi-UAV, cooperative search plays an important part. The majority of approaches in use today assume that the UAV swarm's communication network is complete. However, these links are susceptible to environmental changes or adversary interference. Aiming at cooperative search in search-attack and search-rescue tasks, we propose a distributed cooperative search method for multi-UAV with unstable communications (DCS-UC), which is developed based on ant colony optimization (ACO). In this method, three algorithms are presented to enable the UAV swarm to conduct online cooperative search efficiently and safely. Firstly, an algorithm of pheromone matrix consensus update used in ACO is designed under switching and connected topology graphs, which can make the pheromone matrix maintained by each UAV achieve consensus, so that the cooperative efficiency of the UAV swarm is improved. Then, a position consensus update algorithm is presented where the position vector, including the positions of all the UAVs in each UAV, can achieve consensus under switching and connected topology graphs. Finally, to tackle the collision avoidance of all the UAVs, an algorithm of collision avoidance between UAVs is designed by using the obtained consistent positions of all the UAVs, which can make the UAV swarm conduct cooperative search safely. Extensive physical simulation results carried out in Gazebo verify the advantages of our multi-UAV cooperative search method. © 2023, The Authors. All rights reserved.

关键词： Ant colony optimization

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Discrete-time Linear Tracking control Based on Parallel System Theory

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Gao, Junjie Chen, Mingliang Wei, Qinglai The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment China Nuclear Power Engineering Co. Ltd Guangdong Shenzhen518172 China

Inspired by parallel system theory, a novel parallel tracking controller is presented for discrete-time linear systems in this paper. The core point is to model the time derivative of system control, which makes the control system and the control law completely equivalent in mathematical form. First, the architecture of discrete-time linear parallel tracking control is introduced. Then, in the sight of the reachability of control systems, the pole assignment theorems are given. The merits of this presented method comparing with traditional feedback control are analyzed. Eventually, the efficiency of this method is proved through numerical results. © 2024 Gao, J., Chen, M. & Wei, Q.

关键词： Discrete time control systems

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Parallel cognition:hybrid intelligence for human-machine interaction and management

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Frontiers of Information technology & Electronic Engineering 2022年第12期23卷 1765-1779页

作者： Peijun YE Xiao WANG Wenbo ZHENG Qinglai WEI Fei-Yue WANG State Key Laboratory for Management and Control of Complea Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China QingdaoAcademy of Intelligent Industries Qingdao 266109China School of Software Engineering Xi'an Jiaotong UniversityXi'an 710049China Macao Institute of System Engineering Macao University of Science and TechnologyMacao 999078China

As an interdisciplinary research approach,traditional cognitive science adopts mainly the experiment,induction,modeling,and validation *** models are sometimes not applicable in cyber-physical-socialsystems (CPSSs),where the large number of human users involves severe heterogeneity and *** reduce the decision-making conflicts between people and machines in human-centered systems,we propose a new research paradigm called parallel cognition that uses the system of intelligent techniques to investigate cognitive activities and functionals in three stages:descriptive cognition based on artificial cognitive systems (ACSs),predictive cognition with computational deliberation experiments,and prescriptive cognition via parallel behavioral *** make iteration of these stages constantly on-line,a hybrid learning method based on both a psychological model and user behavioral data is further proposed to adaptively learn an individual’s cognitive *** experiments on two representative scenarios,urban travel behavioral prescription and cognitive visual reasoning,indicate that our parallel cognition learning is effective and feasible for human behavioral prescription,and can thus facilitate human-machine cooperation in both complex engineering and social systems.

关键词： Cognitive learning Artificial intelligence Behavioral prescription

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