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system identification with binary-valued observations under both denial-of-service attacks and data tampering attacks:the optimality of attack strategy

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control Theory and Technology 2022年第1期20卷 127-138页

作者： Jin Guo Xuebin Wang Yanling Zhang Wenchao Xue Yanlong Zhao School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of EducationBeijing100083China Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China

With the development of wireless communication technology,cyber physical systems are applied in various fields such as industrial production and infrastructure,where lots of information exchange brings cyber security threats to the *** the perspective of system identification with binary-valued observations,we study the optimal attack problem when the system is subject to both denial of service attacks and data tampering *** packet loss rate and the data tampering rate caused by the attack is given,and the estimation error is *** the optimal attack strategy to maximize the identification error with the least energy is described as a min–max optimization problem with *** explicit expression of the optimal attack strategy is *** examples are presented to verify the effectiveness of the main conclusions.

关键词： system identification Binary-valued observations Denial-of-service attacks Data tampering attacks

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Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1822-1833页

作者： Wei Xu Chen Zhao Jie Cheng Yin Wang Yiqing Tang Tao Zhang Zhiming Yuan Yisheng Lv Fei-Yue Wang Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Signal&Communication Research Institute China Academy Railway SciencesBeijing 100081China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway *** such cases,train timetables need to be ***,timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization *** paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based ***,the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer,providing the better understanding of overall operation in the high-speed railway ***,a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast *** experiments on various delay scenarios are *** results demonstrate the effectiveness of the proposed method in comparison to other popular methods.

关键词： High-speed railway reinforcement learning train timetable rescheduling Transformer

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A Novel Hybrid Transformer-Based Framework for Solar Irradiance Forecasting under Incomplete Data Scenarios

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IEEE Transactions on Industrial Informatics 2024年第6期20卷 8605-8615页

作者： Zhang, Hanjin Li, Bin Su, Shun-Feng Yang, Wankou Xie, Liping Southeast University School of Economics and Management Nanjing210096 China National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518063 China

Accurate prediction of solar irradiance is crucial for the effective utilization of solar energy. However, in real-world scenarios, complex irradiance patterns and prevalent incomplete data pose challenges to precise forecasting, resulting in additional uncertainties and instability. To address these issues, this study proposes a novel irradiance forecasting model that integrates a Mask-Transformer data imputation module and a prediction module centered around the typical patterns representation mechanism. The Mask-Transformer leverages a mask modeling mechanism to model the context of missing data, facilitating accurate estimation of missing values and reducing noise and uncertainty in the input data. The typical patterns representation mechanism comprises a series decomposition module and a feature fusion module, providing the module with the capability to mitigate nonlinearity and nonstationarity in solar irradiance data. This enhancement leads to improved short-term forecasting performance while maintaining long-term forecasting capabilities. Experimental results on two datasets demonstrate that the proposed model exhibits sufficient robustness and accuracy, making it effective in scenarios with incomplete data. © 2005-2012 IEEE.

关键词： Forecasting

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An Iterative-Based Dead-Time Compensation Method for Integrated Interleaved Boost-LLC Converter

An Iterative-Based Dead-Time Compensation Method for Integra...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Wen, Jin Guan, Jiajia Wu, Zongheng Xu, Wenzhe Chen, Haiyan Jin, Zhaosheng Yang, Lei Chen, Cai Yong, Kang Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China Aecc Aero Engine Control System Institute China Beijing Institute of Precision Mechatronics and Controls China

ISBN: (纸本)9798350316445

This paper proposes an iterative-based dead-time compensation method to help integrated interleaved boost-LLC converter (IIBLLC) converter achieve higher frequency. By adjusting switching frequency and compensating dead time, the converter can operate in quasi-resonant mode and the rectification control signal is synchronized with the primary side. In quasi-resonant mode, smaller current RMS results in lower conduction losses and the advantages of realizing ZCS on the secondary side can be preserved. Finally, a 400 W / 850 kHz IIBLLC prototype with 36 - 60 V input and 12 V output is demonstrated, which achieves a peak efficiency of 96.2%. The experimental results show that the LLC operates in quasi-resonant mode, and the efficiency and power density are improved. © 2023 IEEE.

关键词： dead-time compensation integrated converter LLC resonant converter

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Methane and nitrous oxide emissions from municipal wastewater treatment plants in China:A plant-level and technology-specific study

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Environmental science and Ecotechnology 2024年第4期20卷 123-130页

作者： Haiyan Li Liangfang You He Du Bowen Yu Lu Lu Bo Zheng Qiang Zhang Kebin He Nanqi Ren School of Civil and Environmental Engineering Harbin Institute of TechnologyShenzhen518055China Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and EcologyTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China

Wastewater treatment is an important source of greenhouse gases(GHGs).Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants(MWWTPs)in China.A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of *** we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level ***'s methane(CH_(4))and nitrous oxide(N_(2)O)emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg,respectively,with the uncertainty range of-30%to 37%and-30%to 26%at 95%confidence *** find an emission inequality across cities,with the richest cities emitting two times more CH_(4)and N_(2)O per capita from municipal wastewater treatment than the poorest *** emitted CH_(4)and N_(2)O are dominated by Anaerobic/Anoxic/Oxic-,Sequencing Batch Reactor-,Oxidation Ditch-,and Anoxic/Oxic-based MWWTPs of less than 20 years *** the relatively young age structure of China's MWWTPs,the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation *** emission differences among our estimates,previous studies,and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors,implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.

关键词： Methane Nitrous oxide Emissions Municipal wastewater treatment plants

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Secure-by-Construction Synthesis for control systems

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IEEE Transactions on Automatic control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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A Novel Space Vector Modulation Strategy for Three-Level Simplified Neutral Point Clamped Inverter

A Novel Space Vector Modulation Strategy for Three-Level Sim...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Zhu, Shuangxi Guo, Xinyue Liu, Menghu Chen, Cai Kang, Yong Chen, Haiyan Jin, Zhaosheng Yang, Lei Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan China Aecc Aero Engine Control System Institute China Beijing Institute of Precision Mechatronics and Controls China

ISBN: (纸本)9798350316445

To improve efficiency of the three-level (3-L) simplified neutral point clamped (SNPC) inverter, a novel space vector modulation (SVM) strategy is proposed in this paper. The proposed SVM strategy is characterized by switching all switches in 2-L inverter stage only under zero voltage, thus achieving zero voltage switching (ZVS). Therefore, the switching loss of 2-L inverter stage can be diminished. 3-L SNPC inverter suffers from unbalanced neutral-point voltage (NPV) as conventional multilevel inverters. By using alternative small vectors, the NPV can be balanced as well. The performance of the proposed SVM strategy is analyzed in terms of switching loss and the ability of NPV control. Finally, the feasibility and superiority of the proposed strategy are verified by simulation and experiment. © 2023 IEEE.

关键词： 3-L SNPC inverter NPV balancing space vector modulation ZVS

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Anti-disturbance control for Aerial-Recovery Drogue with Flexible Prescribed Performance

Anti-disturbance Control for Aerial-Recovery Drogue with Fle...

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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Zhu, Junfan Wang, Honglun Wang, Yanxiang Liu, Yiheng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shenyuan Honors College Beihang University Beijing100191 China Beijing Institute of Astronautical System Engineering Beijing100076 China

ISBN: (纸本)9789819622115

The control of towed-cable-drogue system (TCDS) is important to achieving aerial recovery. In this paper, an adaptive prescribed performance control (APPC) based drogue controller is proposed to control drogue’s position while docking. First, the kinematic and dynamic models of controllable TCDS under multiple airflow disturbances are constructed. Second, the impact of command mutations and sudden disturbances may cause sudden increase of position tracking error and traditional PPC may encounter control singularity. To address the fragility of traditional PPC, an adaptive PPC is proposed. Combined with backstepping controller, the position controller is designed. Finally, the simulation results validate the effectiveness of the proposed method in addressing the control challenges of TCDS under command mutations and sudden disturbances. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Backstepping

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NBA-guided heuristic sampling algorithm for multi-robot task planning under temporal logic

NBA-guided heuristic sampling algorithm for multi-robot task...

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第43届中国控制会议

作者： Jiong Luo Yongzhao Hua Shunfu Ding Xiwang Dong Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Institute of Artificial Intelligence Beihang University Institute of Unmanned System Beihang University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Aiming at the task planning problem of multi-robot under linear temporal logic(LTL), this paper proposes an improved sampling planning algorithm based on Nondeterministic Büchi automaton(NBA) guidance. Firstly, this paper defines a kind of LTL task planning problem, which mainly focuses on the meaningful key nodes in the task execution of each robot, and there are many sequential dependencies of task constraints. Then, an improved sampling algorithm framework is proposed,which uses a more efficient way to build a search tree and reduces the number of nodes in the tree. Furthermore, the sampling points are guided by NBA to ensure that sampling is conducive to the advancement of time-series tasks. And considering the task feasible region of each robot, the auction algorithm is introduced to optimize the local matching relationship, which greatly improves the quality of sampling points. Finally, numerical simulation is carried out to solve the LTL task planning problem. The optimality and stability of the algorithm are obviously improved, and the time consumption of this algorithm is obviously better than that of the existing advanced algorithms.

关键词： Multi-robot systems sampling-based planning temporal logic task planning NBA-guided

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Multi-agent Deep Reinforcement Learning Based Multi-objective Charging control for Electric Vehicle Charging Station 7th

Multi-agent Deep Reinforcement Learning Based Multi-objectiv...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Gong, Jiabao Fu, Weiming Kang, Yu Qin, Jiahu Xiao, Feng Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819733279

This paper proposes a multi-agent deep reinforcement learning (MADRL) based algorithm for charging control of multiple electric vehicles (EVs) in an electric vehicle charging station (EVCS) with dynamic operations. By taking the uncertainties of EV users’ behaviors and charging prices into consideration, a Markov game with multiple objectives is first established, where the individual objective of reducing EV charging costs and the collective objective of mitigating charging load fluctuations are both studied. Then, a multi-agent actor-double-critic (MAADC) algorithm with a unified advantage actor-critic framework is proposed, where two advantage functions are designed as the local and global critics, and the integrated actor is employed to balance the learning towards the individual and collective objectives. The simulation results obtained in a delicately built EVCS environment show the effectiveness of MAADC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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