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Event-triggered-based self-organizing fuzzy neural network control for the municipal solid waste incineration process

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Science China(Technological Sciences) 2023年第4期66卷 1096-1109页

作者： HE HaiJun MENG Xi TANG Jian QIAO JunFei Faculty of Information Technology Beijing University of TechnologyBejing 100124China Beijing Laboratory of Smart Environmental Protection Beijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Bejing 100124China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Bejing 100124China Xi'an Institute of Electromechanical Information Technology Xi'an 710065China

Due to the large uncertainty in the municipal solid waste incineration(MSWI)process,the furnace temperature of the MSWI process is difficult to control and the controller is updated *** improve the accuracy and reduce the number of controller updates,a novel event-triggered control method based correntropy self-organizing TS fuzzy neural network(ETCSTSFNN)is ***,the neurons of the rule layer are grown or pruned adaptively based on activation intensity and control error to meet the dynamic change of the actual operating ***,the performance index is designed based on the correntropy of tracking errors,and the parameters of the controller are adjusted by gradient descent ***,a fixed threshold event-triggered condition is designed to determine whether the current controller is updated or *** stability of the control system is proved based on the Lyapunov stability ***,the furnace temperature control experiments are conducted based on the actual data of a municipal solid waste incineration plant in *** experimental results show that the proposed ET-CSTSFNN controller shows a better control performance,which can reduce the number of the controller update significantly while achieving accurate furnace temperature control compared with other traditional control methods.

关键词： municipal solid waste incineration furnace temperature fuzzy control event-triggered

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Semantic Map Construction via Multi-sensor Fusion 36

Semantic Map Construction via Multi-sensor Fusion

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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Qiu, Houhan Lin, Zhicheng Li, Jun Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781665437127

Semantic SLAM can achieve the acquisition of environmental semantic information and increase the understanding of the environmental content. Therefore, it has received extensive attention from academia and industry. In the most existing work, the visual SLAM and deep learning algorithms are combined, and the point cloud fusion method is used to build maps. It is difficult to be directly applied to robot navigation due to problems of time misalignment of sensor data, mismatched detection ranges, and inconsistent accuracy. In this paper, a method of building a semantic map is proposed by combining lidar, camera, odometer. First, the semantic information and position information of the target object are obtained by the YOLO v3 algorithm through the camera, and the grid map is constructed by using the Gmapping algorithm. Second, the semantic information and position information are merged into the grid semantic map to form a semantic grid map. Finally, the effectiveness and feasibility of this method are verified by these experiments. © 2021 IEEE.

关键词： Cameras

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Research on Data Security Risk Analysis Method of Intelligent and Connected Vehicles Based on Data Asset 24

Research on Data Security Risk Analysis Method of Intelligen...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Wang, Liyong Jin, Long Ji, Haojie Chen, Yupeng He, Peng Wang, Jingyan Fang, Junzhe State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology Univ. Beijing China China Automotive Engineering Research Institute Co. Ltd. Chongqing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

The diversity and complexity of typical scenarios of intelligent and connected vehicles (ICVs) bring serious risks to the data security of vehicles. To avoid the potential data security risks of ICVs effectively, this paper proposes a data risk analysis method for vehicles based on the characteristics of data assets. Considering the similarity between the internet of things (IoT) system and the internet of vehicles system, this method organizes the data assets of the vehicles combined with the layered architecture of the IoT system. The data security risks of vehicles are analyzed from the aspects of threat analysis, vulnerability analysis, and risk quantification. The risk points of vehicles are analyzed, so as to provide model design and verification methods for data security risk analysis of ICVs. © ASCE.

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A Pursuit Strategy for Multi-Agent Pursuit-Evasion Game via Multi-Agent Deep Deterministic Policy Gradient Algorithm

A Pursuit Strategy for Multi-Agent Pursuit-Evasion Game via ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Ye, Jianfeng Wang, Qing Ma, Bei Wu, Yongbao Xue, Lei School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China SEU-Monash Joint Graduate School Southeast University Nanjing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

This paper studies a classical pursuit-evasion problem. The pursuer attempts to capture the faster evader in a bounded area. The velocity of evader is 1.2 times as fast as the pursuers'. All of them have adaptive strategies. We use game theory to model the multi-agent pursuit-evasion game and prove that the game model has Nash equilibrium. Then, we modify the multi-agent deep deterministic policy gradient (MADDPG) algorithm for seeking the Nash equilibrium. The simulation examples are given to illustrate the effectiveness of the designed method. © 2022 IEEE.

关键词： Game theory

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Research on Risk Analysis and Testing Method of the Data in Intelligent and Connected Vehicles 24

Research on Risk Analysis and Testing Method of the Data in ...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Ji, Haojie Wang, Jingyan Wang, Liyong Chen, Yupeng He, Peng Jin, Long Fang, Junzhe State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology Univ. Beijing China China Automotive Engineering Research Institute Co. Ltd. Chongqing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

With the increasing information interaction in intelligent and connected vehicles (ICVs), there are more and more security vulnerabilities in the exploitable data. These vulnerabilities may cause personal privacy leaks, property damage, etc. This paper analyzes the data security risks in the four basic functional areas of ICVs and introduces a novel desensitized data testing framework. This work will provide support for security testing methods for desensitized data in ICVs and provide effective security protection for sensitive personal information in ICVs. © ASCE.

关键词： Information leakage

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DISTRIBUTED REAL-TIME STATE ESTIMATION OF INTEGRATED POWER AND GAS system

DISTRIBUTED REAL-TIME STATE ESTIMATION OF INTEGRATED POWER A...

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CIRED 2022 Shanghai Workshop

作者： Lian, Jie Zhang, Wen Zhao, Qi Zhang, Tingting Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan China

ISBN: (纸本)9781839538391

The integrated power and gas system (IPGS) is drawing a lot of attention owing to its superiority in improving energy efficiency. State estimation plays an important role in monitoring the states of IPGS. Considering the different time constants of the IPGS and privacy issues, this paper proposes a distributed real-time state estimation (D-RTSE) method of IPGS based on a cubature Kalman filter (CKF). First, a difference-based model is established for the gas system to depict its slow dynamic characteristics. Subsequently, an RTSE method based on CKF is developed for the IPGS to deal with the system nonlinearity while integrating both the historical and present measurement information. Then, a distributed scheme is designed for the RTSE of the IPGS to enhance computational efficiency and address privacy issues. The 13-bus power system and the 7-node gas system are integrated as the test system. Test results show that the proposed D-RTSE method can efficiently estimate the accurate states of IPGS. © 2022 IET Conference Proceedings. All rights reserved.

关键词： State estimation

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Informative Path Planning based on Global and Local Active Sensing for Environmental Field Mapping

Informative Path Planning based on Global and Local Active S...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Li, Jiahui Yang, Bingyu Yang, Kaibo Li, Teng School of Control Science and Engineering Shandong University Jinan250061 China School of Statistics Beijing Normal University Zhuhai519085 China Key Laboratory of Machine Intelligence and System Control Ministry of Education of the People's Republic of China Jinan250061 China

ISBN: (纸本)9781665481090

Mobile robots can reconstruct environmental fields through active sensing and autonomous navigation, so as to achieve online environmental monitoring. Active sensing enables determine the target sampling location by exploiting the critical information in the target monitored environments. The key information for active sensing is commonly determined by the objective function based on environmental field statistics. In this paper, a novel global and local informative path planning method based on Gaussian process (GP) and multivariate conditional mutual information (MCMI) is proposed, which can achieve effective and reliable execution of information-based active sensing and path planning. Experimental results demonstrate the performance of the proposed method for robotic mobile sensing and environmental field mapping. © 2024 IEEE.

关键词： Environmental monitoring

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Triggered Mechanism for Strict Feedback systems under Unknown control Directions 14

Triggered Mechanism for Strict Feedback Systems under Unknow...

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14th Asian control Conference, ASCC 2024

作者： Liu, Guilong Wu, Hongda Yang, Yongliang Xie, Wei Zhang, Weidong School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581598

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example. © 2024 Asian control Association.

关键词： Feedback

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Deciphering decadal urban ozone trends from historical records since 1980

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National Science Review 2024年第11期11卷 117-129页

作者： Haolin Wang Xiao Lu Paul I.Palmer Lin Zhang Keding Lu Ke Li Tatsuya Nagashima Ja-Ho Koo Hiroshi Tanimoto Haichao Wang Meng Gao Cheng He Kai Wu Shaojia Fan Yuanhang Zhang School of Atmospheric Sciences Sun Yat-sen University and Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Education Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) School of Geo Sciences University of Edinburgh National Centre for Earth Observation University of Edinburgh Laboratory for Climate and Ocean-Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking University State Key Joint Laboratory of Environmental Simulation and Pollution Control The State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution ControlCollege of Environmental Sciences and Engineering Peking University Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science &Technology National Institute for Environmental Studies Department of Atmospheric Sciences Yonsei University Department of Geography Hong Kong Baptist University Department of Civil and Environmental Engineering University of California

Ozone pollution is a major environmental threat to human health. Timely assessment of ozone trends is crucial for informing environmental policy. Here we show that for the most recent decade（2013–2022） in the northern hemisphere, warm-season（April–September） mean daily 8-h average maximum ozone increases much faster in urban regions with top ozone levels(mainly in the North China Plain, 1.2 ± 1.3 ppbv year-1) than in other, low-ozone regions(0.2 ± 0.9 ppbv year-1). These trends widen the ozone differences across urban regions, and increase extreme pollution levels and health threats from a global perspective. Comparison of historical trends in different urban regions reveals that ozone increases in China during 2013–2022 differ in magnitude and mechanisms to historical periods in other regions since *** reflects a unique chemical environment characterized by exceptionally high nitrogen oxides and aerosol concentrations, where reducing ozone precursor emissions leads to substantial ozone *** increase in China has slowed down in 2018–2022 compared to 2013–2017, driven by ongoing emission reductions, but with ozone-favorable weather conditions. Historical ozone evolution in Japan and South Korea indicates that ozone increases should be suppressed with continuous emission *** temperature and associated wildfires have also reversed ozone decreases in the USA and Europe,with anthropogenic ozone control slowing down in recent decades.

关键词： air quality surface ozone trends

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Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset 41

Diving into Underwater: Segment Anything Model Guided Underw...

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41st International Conference on Machine Learning, ICML 2024

作者： Lian, Shijie Zhang, Ziyi Li, Hua Li, Wenjie Yang, Laurence Tianruo Kwong, Sam Cong, Runmin Hainan University China China Ministry of Education China Huazhong University of Science and Technology China St. Francis Xavier University Canada LIngnan University School of Data Science Hong Kong Shandong University School of Control Science and Engineering China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China

With the breakthrough of large models, Segment Anything Model (SAM) and its extensions have been attempted to apply in diverse tasks of computer vision. Underwater salient instance segmentation is a foundational and vital step for various underwater vision tasks, which often suffer from low segmentation accuracy due to the complex underwater circumstances and the adaptive ability of models. Moreover, the lack of large-scale datasets with pixel-level salient instance annotations has impeded the development of machine learning techniques in this field. To address these issues, we construct the first large-scale underwater salient instance segmentation dataset (USIS10K), which contains 10,632 underwater images with pixel-level annotations in 7 categories from various underwater scenes. Then, we propose an Underwater Salient Instance Segmentation architecture based on Segment Anything Model (USIS-SAM) specifically for the underwater domain. We devise an Underwater Adaptive Visual Transformer (UA-ViT) encoder to incorporate underwater domain visual prompts into the segmentation network. We further design an out-of-the-box underwater Salient Feature Prompter Generator (SFPG) to automatically generate salient prompters instead of explicitly providing foreground points or boxes as prompts in SAM. Comprehensive experimental results show that our USIS-SAM method can achieve superior performance on USIS10K datasets compared to the state-of-the-art methods. Datasets and codes are released on Github. Copyright 2024 by the author(s)

关键词： Pixels

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