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Science China(Information Sciences) 2025年第2期68卷 200-215页

作者： Yunxiang MA Tong ZHOU department of automation Tsinghua University department of automation and bnrist Tsinghua University

This paper investigates the identifiability of structured systems with a matrix fraction description and attacks practical difficulties in estimating parameters under finite frequency responses. The numerator and denominator polynomial matrices depend affinely on system parameters, which can represent a broad range of systems, especially circuits and mechanical systems. Except for assuming that the denominator matrix is invertible, no further assumptions are adopted. A criterion is provided for validating this assumption utilizing graph theories and matroids. A sufficient and necessary criterion for global identifiability based on the rank of a numerical matrix is given and can be recursively verified with each frequency point,which is computationally attractive for large-scale systems. For an identifiable system, an ellipsoid approximation is obtained for the set of parameters whose corresponding system frequency responses deviate within a specific range from those of the system at a specific parameter value. Using this approximation, explicit expressions for absolute and relative sloppiness have been derived, which can be used to quantify the difficulty of identifying system parameters. Comparisons with the well-known Fisher information matrix have also been performed through a mechanical system, revealing significant differences in quantifying parameter estimation hardness.

关键词： identifiability sloppiness structured system matrix fraction graph theory matroid

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Decentralized fault diagnosis of discrete-event systems with unreliable sensors using linear temporal logic

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Science China(Information Sciences) 2025年第1期68卷 322-341页

作者： Weijie DONG Shaoyuan LI Xiang YIN Key Laboratory of System Control and Information Processing Ministry of EducationDepartment of Automation Shanghai Jiao Tong University

In this paper,we investigate a decentralized diagnosis problem of a discrete-evnt system(DES) subject to unreliable sensors,where the sensor observations of local diagnosers may be non-deterministic as a result of possible *** studies on decentralized robust diagnosis can only deal with different types of sensor failures separately,e.g.,all sensors suffer from the same type of sensor failures such as intermittent sensor failures or permanent sensor ***,since sensors of different local diagnosers may face different external environments and have different internal characteristics,sensors corresponding to different local diagnosers may also have their own fault *** this paper,we propose a flexible framework of decentralized diagnosis for DES subject to unreliable sensors such that sensors of different local diagnosers are permitted to have different types of sensor *** this end,we extend the existing decentralized diagnosis framework to the case where there exist common sensors broadcasting their observations to all local *** apply linear temporal logic(LTL) to constrain infinite behaviors of private sensors of local diagnosers and common ***,a new notion of φ-codiagnosability is proposed as the necessary and sufficient condition for the existence of a decentralized diagnoser that works correctly under sensors,satisfying LTL-based sensor ***,we provide an effective approach to verify the φ-codiagnosability.

关键词： discrete event systems decentralized diagnosis codiagnosability automata

Capsaicin(CAP) exerts a protective effect against ethanol-induced oxidative gastric mucosal injury by modulating the chemokine receptor 4 (CCR4)/Src/p47phox signaling pathway both in vitro and in vivo

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Chinese Journal of Natural Medicines 2025年第2期23卷 191-202页

作者： Zhiru Yang Haolin Guo Pengfei Zhang Kairui Liu Junli Ba Xue Bai Shiti Shama Bo Zhang Xiaoning Gao Jun Kang School of Life Sciences Tianjin University School of Traditional Chinese Medicine Beijing University of Chinese Medicine Tianjin Pharmaceutical and Cosmetic Evaluation and Inspection Center Institute for TCM-X MOE Key Laboratory of Bioinformatics Bioinformatics Division BNRist Department of Automation Tsinghua University Institute of Biomedical Research Henan Academy of Sciences

Ethanol(EtOH) is a common trigger for gastric mucosal diseases, and mitigating oxidative stress is essential for attenuating gastric mucosal damage. Capsaicin(CAP) has been identified as a potential agent to counteract oxidative damage in the gastric mucosa; however, its precise mechanism remains unclear. This study demonstrates that CAP alleviates EtOH-induced gastric mucosal injuries through two primary pathways: by suppressing the chemokine receptor 4(CCR4)/Src/p47phox axis, thereby reducing oxidative stress, and by inhibiting the phosphorylation and nuclear translocation of nuclear factor-κB p65(NF-κB) p65, resulting in diminished inflammatory responses. These findings elucidate the mechanistic pathways of CAP and provide a theoretical foundation for its potential therapeutic application in the treatment of gastric mucosal injuries.

关键词： Capsaicin Chemokine signaling Gastric mucosal damage NF-κB p65

General expert consensus on the application of network pharmacology in the research and development of new traditional Chinese medicine drugs

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Chinese Journal of Natural Medicines 2025年第2期23卷 129-142页

作者： Shao Li Wei Xiao Institute of TCM-X/MOE Key Laboratory of Bioinformatics Bioinformatics Division BNRist/Department of Automation Tsinghua University State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Jiangsu Kanion Pharmaceutical Co. Ltd.

The research and development of new traditional Chinese medicine(TCM) drugs have progressively established a novel system founded on the integration of TCM theory, human experience, and clinical trials(termed the “Three Combinations”). However, considering TCM's distinctive features of “syndrome differentiation and treatment” and “multicomponent formulations and complex mechanisms”, current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system. Moreover, significant obstacles persist in gathering human experience data, evaluating clinical efficacy, and controlling the quality of active ingredients, which impede the innovation process in TCM drug development. Network pharmacology, centered on the “network targets” theory, transcends the limitations of the conventional“single target” reductionist research model. It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions. This approach aligns with the holistic perspective of TCM, offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs. It is internationally recognized as a “next-generation drug research model”. To advance the research of new tools, methods, and standards for TCM evaluation and to overcome fundamental, critical, and cutting-edge technical challenges in TCM regulation, this consensus aims to explore the characteristics, progress, challenges, applicable pathways, and specific applications of network pharmacology as a new theory, method, and tool in TCM drug development. The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.

关键词： Expert consensus Network pharmacology Research and development of new traditional Chinese medicine drugs

A Comprehensive Survey of Few-shot Information Networks

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Machine Intelligence Research 2025年第1期22卷 60-78页

作者： Xinxin Zheng Feihu Che Jianhua Tao School of Artificial Intelligence University of Chinese Academy of SciencesBeijing100049China Institute of automation Chinese Academy of SciencesBeijing100190China department of automation Tsinghua UniversityBeijing100084China

Information networks store rich information in the nodes and edges,which benefit many downstream tasks,such as recommender systems and knowledge graph *** networks contain homogeneous information,heterogeneous information and knowledge graphs.A significant number of surveys focus on one of the three parts and summarize the research works,but few surveys conclude and compare the three kinds of information *** addition,in real scenarios,lots of information networks lack sufficient labeled data,so the combination of meta-learning and information networks can bring in extended *** paper concentrates on few-shot information networks and systematically presents recent works to help analyze and follow related works.

关键词： Few-shot learning meta-learning homogeneous information networks heterogeneous information networks knowledge graphs

K-Corruption Intermittent Attacks for Violating the Codiagnosability

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 159-172页

作者： Ruotian Liu Yihui Hu Agostino Marcello Mangini Maria Pia Fanti IEEE the department of Electrical and Information Engineering Polytechnic University of Bari the School of automation Xi'an University of Posts and Telecommunications

In this work, we address the codiagnosability analysis problem of a networked discrete event system under malicious attacks. The considered system is modeled by a labeled Petri net and is monitored by a series of sites, in which each site possesses its own set of sensors, without requiring communication among sites or to any coordinators. A net is said to be codiagnosable with respect to a fault if at least one site could deduce the occurrence of this fault within finite steps. In this context, we focus on a type of malicious attack that is called stealthy intermittent replacement attack. The stealthiness demands that the corrupted observations should be consistent with the system's normal behavior, while the intermittent replacement setting entails that the replaced transition labels must be recovered within a bounded of consecutive corrupted observations(called as K-corruption intermittent attack). Particularly, there exists a coordination between attackers that are separately effected on different sites, which holds the same corrupted observation for each common transition under attacks. From an attacker viewpoint, this work aims to design Kcorruption intermittent attacks for violating the codiagnosability of systems. For this purpose, we propose an attack automaton to analyze K-corruption intermittent attack for each site, and build a new structure called complete attack graph that is used to analyze all the potential attacked paths. Finally, an algorithm is inferred to obtain the K-corruption intermittent attacks, and examples are given to show the proposed attack strategy.

关键词： Codiagnosability decentralized structure discrete event system intermittent attack Petri net

Distributed Nash Equilibrium Seeking with Disturbances of Unknown Frequencies for High-Order Integrators over Jointly Strongly Connected Switching Networks

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Journal of Systems Science & Complexity 2025年第01期 369-389页

作者： HE Xiongnan HUANG Jie department of Mechanical and automation Engineering The Chinese University of Hong Kong

In this paper, the authors study the problem of distributed Nash equilibrium seeking of N-player games with high-order integrator dynamics subject to disturbances generated by an uncertain exosystem. Similar problems have been studied for disturbances with an exactly known *** with the existing results of high-order integrator dynamics, which can only handle sinusoidal disturbances with known frequencies, this paper aims to handle multi-tone disturbances with unknown frequencies by introducing an adaptive control technique to estimate the unknown frequencies. Technically, when the exosystem is known, the disturbance can be dealt with by the Luenburger observer. In contrast, the Luenburger observer cannot deal with an uncertain exosystem. The authors combine the internal model design and some adaptive control technique to solve the proposed problem. Further, the authors also establish the sufficient condition to guarantee the convergence of the estimated unknown frequencies to the actual values of these frequencies. Two examples are given to verify the proposed algorithm.

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Deep reinforcement learning based integrated evasion and impact hierarchical intelligent policy of exo-atmospheric vehicles

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Chinese Journal of Aeronautics 2025年第1期38卷 409-426页

作者： Leliang REN Weilin GUO Yong XIAN Zhenyu LIU Daqiao ZHANG Shaopeng LI Xi’an Research Institute of High Technology Xi’an 710025China China Xi’an Satellite Control Center Xi’an710043China department of automation Tsinghua UniversityBeijing 100084China

Exo-atmospheric vehicles are constrained by limited maneuverability,which leads to the contradiction between evasive maneuver and precision *** address the problem of Integrated Evasion and Impact(IEI)decision under multi-constraint conditions,a hierarchical intelligent decision-making method based on Deep Reinforcement Learning(DRL)was ***,an intelligent decision-making framework of“DRL evasion decision”+“impact prediction guidance decision”was established:it takes the impact point deviation correction ability as the constraint and the maximum miss distance as the objective,and effectively solves the problem of poor decisionmaking effect caused by the large IEI decision ***,to solve the sparse reward problem faced by evasion decision-making,a hierarchical decision-making method consisting of maneuver timing decision and maneuver duration decision was proposed,and the corresponding Markov Decision Process(MDP)was designed.A detailed simulation experiment was designed to analyze the advantages and computational complexity of the proposed *** results show that the proposed model has good performance and low computational resource *** minimum miss distance is 21.3 m under the condition of guaranteeing the impact point accuracy,and the single decision-making time is 4.086 ms on an STM32F407 single-chip microcomputer,which has engineering application value.

关键词： Exo-atmospheric vehicle Integrated evasion and impact Deep reinforcement learning Hierarchical intelligent policy Single-chip microcomputer Miss distance

Value Iteration-Based Distributed Adaptive Dynamic Programming for Multi-Player Differential Game With Incomplete Information

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 436-447页

作者： Yun Zhang Yuqi Wang Yunze Cai the department of automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China the National Key Laboratory of Air-based Information Perception and Fusion

In this paper, a distributed adaptive dynamic programming(ADP) framework based on value iteration is proposed for multi-player differential games. In the game setting,players have no access to the information of others' system parameters or control laws. Each player adopts an on-policy value iteration algorithm as the basic learning framework. To deal with the incomplete information structure, players collect a period of system trajectory data to compensate for the lack of information. The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy. Theoretical analysis shows that by adopting proximal policy searching rules, the approximated policies can converge to a neighborhood of equilibrium policies. The efficacy of our method is illustrated by three examples, which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.

关键词： Distributed adaptive dynamic programming incomplete information multi-player differential game (MPDG) value iteration

Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer