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Event-triggered consensus for linear continuous-time multi-agent systems based on a predictor

Information Sciences 2018年 459卷 278-289页

作者： Jian Sun Qiuling Yang Xiaoyu Liu Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 PR China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 PR China China North Industrial Group Corporation Limited China Ordnance Industry Navigation and Control Technology Institute Beijing 100089 PR China

In this paper, the problem of an event-triggered consensus for a linear continuous-time multi-agent system is investigated. A new event-triggered consensus protocol based on a predictor is proposed to achieve consensus while not requiring continuous communication among agents. The predictor utilizes an artificial closed-loop system to predict the future state of each agent. With the proposed consensus protocol, each agent only needs to monitor its own states to determine its event-triggered instants. When an event of an agent is triggered, the agent immediately updates its consensus protocol and sends its state information to its neighbors. When an agent receives state information from its neighbors, the agent immediately updates its consensus protocol and predictor. A necessary and sufficient condition that solves the consensus problem is derived. Moreover, it is proved that Zeno behaviors are excluded. Finally, some numerical examples are given to illustrate that, with the proposed protocol, a multi-agent system can achieve consensus while greatly reducing event-triggered times.

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Robust Disturbance-Rejection for a Class of Nonlinear systems

Robust Disturbance-Rejection for a Class of Nonlinear System...

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第37届中国控制会议

作者： Pan Yu Kang-Zhi Liu Min Wu Jinhua She Department of Electrical and Electronic Engineering Chiba University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Information Science and Engineering Central South University School of Automation China University of Geosciences School of Engineering Tokyo University of Technology

This paper presents a robust disturbance-rejection method for a system with a time-variant nonlinearity and a disturbance. The nonlinear dynamics which satisfies Lipschitz condition is unknown. The disturbance is also unknown but *** advantage of stable inversion, an improved EID(IEID) is utilized to deal with the total effect of the nonlinearity and disturbance. To reduce the conservativeness of system design, a feedback control gain is obtained in prior to the control gains of the observer and the IEID estimator. Then a Lyapunov functional considering the information of the nonlinearity is constructed and based on that, a linear-matrix-inequality(LMI)-based stability condition is derived to acquire the gains of the observer and the IEID estimator. Two tuning parameters are introduced in the LMI to enable the adjustment of disturbance-rejection performance. Finally, simulations for a flight control system show that the developed method has good robustness. Comparisons with disturbance-observer-based control(DOBC), composite DOBC and H control, and conventional EID-based control methods demonstrate the effectiveness of the developed method and its advantages over others.

关键词： Disturbance-rejection improved equivalent-input-disturbance（EID） linear matrix inequality（LMI） nonlinear system robustness

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Foundation models and intelligent decision-making: Progress, challenges, and perspectives

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Innovation 2025年第6期6卷 100948页

作者： Huang, Jincai Xu, Yongjun Wang, Qi Wang, Qi [Cheems] Liang, Xingxing Wang, Fei Zhang, Zhao Wei, Wei Zhang, Boxuan Huang, Libo Chang, Jingru Ma, Liantao Ma, Ting Liang, Yuxuan Zhang, Jie Guo, Jian Jiang, Xuhui Fan, Xinxin An, Zhulin Li, Tingting Li, Xuefei Shao, Zezhi Qian, Tangwen Sun, Tao Diao, Boyu Yang, Chuanguang Yu, Chenqing Wu, Yiqing Li, Mengxian Zhang, Haifeng Zeng, Yongcheng Zhang, Zhicheng Zhu, Zhengqiu Lv, Yiqin Li, Aming Chen, Xu An, Bo Xiao, Wei Bai, Chenguang Mao, Yuxing Yin, Zhigang Gui, Sheng Su, Wentao Zhu, Yinghao Gao, Junyi He, Xinyu Li, Yizhou Jin, Guangyin Ao, Xiang Zhai, Xuehao Tan, Haoran Yun, Lijun Shi, Hongquan Li, Jun Fan, Changjun Huang, Kuihua Harrison, Ewen Leung, Victor C.M. Qiu, Sihang Dong, Yanjie Zheng, Xiaolong Wang, Gang Zheng, Yu Wang, Yuanzhuo Guo, Jiafeng Wang, Lizhe Cheng, Xueqi Wang, Yaonan Yang, Shanlin Fu, Mengyin Fei, Aiguo Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China Huazhong University of Science and Technology Wuhan430074 China School of Automation Beijing Institute of Technology Beijing100081 China School of Information Science and Engineering Dalian Polytechnic University Dalian116034 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing100081 China Guangzhou511453 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China IDEA Research International Digital Economy Academy Shenzhen518057 China Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Science National University of Defense Technology Changsha410073 China Center for Systems and Control College of Engineering Peking University Beijing100871 China Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China College of Systems Engineering National University of Defense Technology Changsha410073 China Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore School of Electrical Engineering Chongqing University Chongqing400044 China Department of Mathematics The University of Hong Kong Hong Kong SAR999077 China School of Food Science and Technology Dalian Polytechnic University Dalian116034 China Centre for Medical Informatics University of Edinburgh EdinburghEH16 4UX United Kingdom Department of Stomatology Peking Union Medical College Hospital Chinese Academ

intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM's evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems. © 2025 The Authors

关键词： Reinforcement learning

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A NSGA-Ⅱ based Peak Load Shifting Optimization Method for Customers with Distributed Generators Considering Time-of-use Price

A NSGA-Ⅱ based Peak Load Shifting Optimization Method for C...

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第37届中国控制会议

作者： Hao Zhou Min Ding Bo Hu Qingyi Wang Zhili Tan Danyun li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute Co. LTD.

With the extensive use of distributed generation, the traditional demand response analysis cannot meet the current *** paper proposes a NSGA-II based peak load shifting optimization method for customers with distributed generators considering time-of-use price. Firstly, a fuzzy classification method divides the daily power into three time segments,peak hours, flat hours and valley hours. Secondly, on the basis of the time-of-use price, a peak load shifting optimization model is built with constraints and the objectives of minimizing the peak load, maximizing the valley load, and minimizing the peakvalley difference. Then, a NSGA-II based optimization method solves the optimal model and obtains the optimal electricity prices of different time segments to shift the peak load and the valley load. Finally, the simulation results shows the effectiveness of the proposed method.

关键词： Distributed Generation Demand Respond Time-of-use Price Multi-objective Genetic Algorithm

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Trapezoidal Pythagorean Fuzzy Linguistic Bonferroni Mean Operator based on the Preference Relation: A Case Study for Targeted Poverty Alleviation

Trapezoidal Pythagorean Fuzzy Linguistic Bonferroni Mean Ope...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Yue Xiao Sidong Xian School of Automation Chongqing University of Posts and Telecommunications Chongqing P. R. China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing P. R. China

ISBN: (纸本)9781538680988;9781538680971

The 19th session of national congress of the communist party of China reaffirmed its determination to win the fight against poverty. Therefore, it is of great importance to determine how to help people in different poverty-stricken areas. Bonferroni mean (BM), which can capture interrelationship among the individual arguments. And the intuitionistic preference relation is a powerful mean to express decision makers' information of intuitionistic preference over criteria in the process of decision making. Hence, in this paper, we present weighted trapezoidal Pythagorean fuzzy linguistic preference relation (TrPFLPR), afterwards, we propose the BM into trapezoidal Pythagorean fuzzy linguistic preference environment, present the trapezoidal Pythagorean fuzzy linguistic Bonferroni mean (TrPFLBM) operator and the weight TrPFLBM operator. In conclusion, a numerical instance about targeted poverty alleviation selection is given to demonstrate the method's effectiveness.

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Stable walking of quadruped robot on unknown rough terrain

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Journal of Beijing Institute of Technology 2016年第4期25卷 463-472页

作者：何玉东王军政柯贤锋汪首坤 Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Quadruped robot is considered to be the most practical locomotion machine to negotiate uneven terrain, and shows superb stability during static walking. To improve the ability to go over rough terrain, this paper is focused on the stable walking and balance control of quadruped robots. 24 kinds of walking gaits are analyzed in order to derive the most stable and smoothest walking gait. Considering the inefficiency to model a terrain by its specified appearance, a uniform terrain model is established and by means of kinematic analysis, a method to adjust the body posture and center of gravity （COG） height is presented. Simulations demonstrate the effectiveness of the proposed meth- od and the improvement of the adaptation of quadruped robots on rough terrain.

关键词： quadruped robot unknown rough terrain walking gait body posture body center ofgravity （COG）

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Analysis of security in cyber-physical systems

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Science China. Technological Sciences 2017年第12期60卷 1975-1977页

作者： Chen Jie Zhang Fan Sun Jian School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

In recent years, cyber-physical systems (CPSs) have received much attention from both the academic world and the industrial world, which refer to a deep integration and coordination of physical and computational resources [1,2]. Typical examples of CPSs can be found in smart grids, smart transportation systems, industrial control systems, water supply systems, and so on. Furthermore, many military systems are also CPSs. The key characteristic of CPSs is the integration of computing, control and communication. The increased interconnection between the cyber and physical spaces make CPSs vulnerable to various malicious attacks. A well-known example of an attack of CPSs is the Stuxnet which infected the control system of nuclear-fuel centrifuges of Bushehr nuclear power plant in Iran. Stuxnet makes people beware of the grave consequences of a cyber-attack on a CPS. Since many national critical infrastructures are applications of CPS, ensuring security and safety of such systems is of great importance.

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Finite-time Switching Synchronization of Four Real Chaotic systems with Combination Mode

Finite-time Switching Synchronization of Four Real Chaotic S...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Weiqi Qin Yanfeng Wang Tianze Li Ming Guo Xiangyong Chen Xinru Tong Affiliated Hospital of Shandong Medical College Linyi P. R. China School of Engineering Huzhou University Huzhou P. R. China School of Automation and Electrical Engineering Linyi University Key Laboratory of Complex systems and Intelligent Computing in Universities of Shandong Linyi University Linyi P. R. China College of Mathematics and Systems Science Xinjiang University Urumqi P. R. China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

This paper mainly studies the problem of finite-time switching synchronization for four real chaotic systems with combination mode. Firstly, we analyze multi-switching synchronization behavior in signal switching transmission, and the definition of finite-time combination synchronization is given by choosing the preset switching rules. And then, a novel finite time controller is designed to realize fast synchronization, and the sufficient conditions are given. Finally, numerical examples verify the effectiveness of the proposed control scheme.

关键词： Synchronization Switching systems Chaotic communication control system synthesis

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A threshold segmentation method for non-uniform illumination image based on brightness equalization

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IOP Conference Series: Materials Science and Engineering 2019年第5期569卷

作者： Hui Guo Peng Chen Shun Huang Cong Hu Lijun Zhang School of Automation China University of Geosciences Wuhan 430074 China Hubei key laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan 430074 China

In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, an image threshold segmentation method is proposed for non-uniform illumination images. First, the brightness of different regions in the image is compensated to make the brightness background of the whole image consistent. Second, the gradation histogram of the processed image is obtained and simulated into Gaussian distribution curve, then the inflection points of the curve are calculated. Finally, the two inflection points are set as thresholds to segment the image after brightness equalization. This method eliminates the influence of non-uniform illumination to a certain extent and gets a better segmentation effect. Experiments were carried out on images containing several different types of non-uniform illumination. The results demonstrate that the proposed method outperforms the compared enhancement algorithms in threshold segmentation.

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Adaptive robust controller for electric cylinder with fast parameter estimation based on modified lugre model

Adaptive robust controller for electric cylinder with fast p...

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第36届中国控制会议

作者： Duo yang Li Jun Zheng Wang Ren Jian Hao Shou Kun Wang Wei Shen Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

In this paper,the adaptive robust control（ARC） algorithm is proposed for tracking control of the electric cylinder *** to the analysis of the working principle of the electric cylinder servo system,the model of the system is established on the modified Lugre friction model,and single observer is designed for calculating friction as *** the ARC controller and adaptive law are designed for on-line parameters estimation,frictional compensation and the suppression external *** the Lyapunov approach,the stability of this system can be obtained in this *** simulation result shows that ARC can suppresses external disturbances effectively and realize real-time online parameter estimation.

关键词： adaptive robust control Lugre model parameter estimation

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