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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1410-1423页

作者： Xiangmin Tan Chunyan Hu Guanzhen Cao qinglai wei wei Li Bo Han Institute of Engineering Thermophysics Chinese Academy of SciencesBeijing 100190 School of Aeronautics and Astronautics University of Chinese Academy of SciencesBeijing 100049China Institute of Automation Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China IEEE

In this paper,fixed-time consensus tracking for mul-tiagent systems(MASs)with dynamics in the form of strict feed-back affine nonlinearity is addressed.A fixed-time antidistur-bance consensus tracking protocol is proposed,which consists of a distributed fixed-time observer,a fixed-time disturbance observer,a nonsmooth antidisturbance backstepping controller,and the fixed-time stability analysis is conducted by using the Lyapunov theory correspondingly.This paper includes three main improvements.First,a distributed fixed-time observer is developed for each follower to obtain an estimate of the leader’s output by utilizing the topology of the communication network.Second,a fixed-time disturbance observer is given to estimate the lumped disturbances for feedforward compensation.Finally,a nonsmooth antidisturbance backstepping tracking controller with feedforward compensation for lumped disturbances is designed.In order to mitigate the“explosion of complexity”in the tradi-tional backstepping approach,we have implemented a modified nonsmooth command filter to enhance the performance of the closed-loop system.The simulation results show that the pro-posed method is effective.

关键词： Antidisturbance backstepping consensus tracking fixed-time stability multiagent system(MASs) strict feedback affine nonlinear systems.

Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal Control

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1702-1704页

作者： Jingwei Lu Lefei Li qinglai wei Fei-Yue Wang IEEE the Department of Industrial Engineering Tsinghua UniversityBeijing 100084China The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

关键词： Deep letter enable

A new optimal adaptive backstepping control approach for nonlinear systems under deception attacks via reinforcement learning

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Journal of Automation and Intelligence

Journal of Automation and Intelligence 2024年第1期3卷 34-39页

作者： Wendi Chen qinglai wei Institute of Systems Engineering Macao University of Science and TechnologyAvenida WeiLong Taipa999078Macao Special Administrative Region of China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences95 Zhongguancun East Road100190BeijingChina

In this paper,a new optimal adaptive backstepping control approach for nonlinear systems under deception attacks via reinforcement learning is presented in this paper.The existence of nonlinear terms in the studied system makes it very difficult to design the optimal controller using traditional methods.To achieve optimal control,RL algorithm based on critic–actor architecture is considered for the nonlinear system.Due to the significant security risks of network transmission,the system is vulnerable to deception attacks,which can make all the system state unavailable.By using the attacked states to design coordinate transformation,the harm brought by unknown deception attacks has been overcome.The presented control strategy can ensure that all signals in the closed-loop system are semi-globally ultimately bounded.Finally,the simulation experiment is shown to prove the effectiveness of the strategy.

关键词： Nonlinear systems Reinforcement learning Optimal control Backstepping method

Optimal synchronization control formulti-agent systems with input saturation:a nonzero-sum game

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Frontiers of Information Technology & Electronic Engineering 2022年第7期23卷 1010-1019页

作者： Hongyang LI qinglai wei School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

This paper presents a novel optimal synchronization control method for multi-agent systems with input saturation.The multi-agent game theory is introduced to transform the optimal synchronization control problem into a multi-agent nonzero-sum game.Then,the Nash equilibrium can be achieved by solving the coupled Hamilton–Jacobi–Bellman(HJB)equations with nonquadratic input energy terms.A novel off-policy reinforcement learning method is presented to obtain the Nash equilibrium solution without the system models,and the critic neural networks(NNs)and actor NNs are introduced to implement the presented method.Theoretical analysis is provided,which shows that the iterative control laws converge to the Nash equilibrium.Simulation results show the good performance of the presented method.

关键词： Optimal synchronization control Multi-agent systems Nonzero-sum game Adaptive dynamic programming Input saturation Off-policy reinforcement learning Policy iteration

Detrital Zircon of Devonian Sandstones in ChangningMenglian Suture Zone, Yunnan, SW China: Implications for the Early Evolution of Paleo-Tethys

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Journal of Earth Science 2024年第3期35卷 786-796页

作者： Zhengqin Gan qinglai Feng Yuehua wei Guichun Liu Xiaomei Nie Tianyu Zhao State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430078China School of Earth Sciences China University of GeosciencesWuhan 430074China

The Changning-Menglian suture zone is a critical tectonic belt pivotal to the evolution of the Paleo-Tethys.The Wenquan Formation,characterized as turbidite deposited on the western side of the Changning-Menglian suture zone as well as the eastern edge of the Baoshan Block.Analysis of detrital zircons from the Wenquan Formation reveals two significant age peaks approximately at 440 and 980 Ma,with additional age populations around 600,780,and 2500 Ma.The major age peak at about 440 Ma is come from the andesitic-dominant volcanic arc within the Lancang Block and the western Simao Block,corroborated by the presence of andesite fragments in thin section studies.Meanwhile,the zircons that form the secondary age peak at~980 Ma and other older age groups probably originate from the Baoshan Block.Deposited on the western side of the Paleo-Tethyan ophiolites,the Wenquan Formation received detrital materials from the continental margin on the opposite side.Thus,the main Paleo-Tethyan Ocean basin was not sufficiently broad enough to cut off the transference of detrital materials.It was a relatively narrow basin in the Early Devonian.

关键词： Changning-Menglian suture zone sandstone zircon Paleo-Tethys Devonian tectonics.

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 paradigm.Such models are sometimes not applicable in cyber-physical-socialsystems (CPSSs),where the large number of human users involves severe heterogeneity and dynamics.To 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 prescription.To 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 knowledge.Preliminary 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

Institutionalized and systematized gaming for multi-agent systems

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Frontiers of Information Technology & Electronic Engineering 2022年第7期23卷 991-994页

作者： Jun LU Fei-Yue WANG Qi DONG qinglai wei China Academy of Electronics and Information Technology Beijing 100049China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China

Multi-agent system gaming(MASG)is widely applied in military intelligence,information networks,unmanned systems,intelligent transportation,and smart grids,exhibiting systematic and organizational characteristics.It requires the multi-agent system perceive and act in a complex dynamic environment and at the same time achieve a balance between individual interests and the maximization of group interests within the system.

关键词： agent networks individual

The First-in-Human Whole-Body Dynamic Pharmacokinetics Study of Aptamer

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Research 2024年第1期2023卷 119-130页

作者： Ding Ding Haitao Zhao Dali wei qinglai Yang Cai Yang Ruowen Wang Yumei Chen Lianghua Li Shuxian An Qian Xia Gang Huang Jianjun Liu Zeyu Xiao weihong Tan Institute of Molecular Medicine(IMM) Renji HospitalState Key Laboratory of Oncogenes and Related GenesShanghai Jiao Tong University School of Medicineand College of Chemistry and Chemical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Nuclear Medicine Renji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai 200127China Center for Molecular Imaging Probes Cancer Research InstituteUniversity of South ChinaHengyangHunan 421001China The Key Laboratory of Zhejiang Province for Aptamers and Theranostics Zhejiang Cancer HospitalHangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiang 310022China Molecular Science and Biomedicine Laboratory(MBL) State Key Laboratory of Chemo/Biosensing and ChemometricsCollege of Chemistry and Chemical EngineeringHunan UniversityChangshaHunan 410082China Shanghai Key Laboratory of Molecular Imaging Shanghai University of Medicine and Health SciencesShanghai 201318China Department of Pharmacology and Chemical Biology Shanghai Jiao Tong University School of MedicineShanghai200127China

Serving as targeting ligands,aptamers have shown promise in precision medicine.However,the lack of knowledge of the biosafety and metabolism patterns in the human body largely impeded aptamers’clinical translation.To bridge this gap,here we report the first-in-human pharmacokinetics study of protein tyrosine kinase 7 targeted SGC8 aptamer via in vivo PET tracking of gallium-68(^(68)Ga)radiolabeled aptamers.The specificity and binding affinity of a radiolabeled aptamer,named ^(68)Ga[Ga]-NOTA-SGC8,were maintained as proven in vitro.Further preclinical biosafety and biodistribution evaluation confirmed that aptamers have no biotoxicity,potential mutation risks,or genotoxicity at high dosage(40 mg/kg).Based on this result,a first-in-human clinical trial was approved and carried out to evaluate the circulation and metabolism profiles,as well as biosafety,of the radiolabeled SGC8 aptamer in the human body.Taking advantage of the cutting-edge total-body PET,the aptamers’distribution pattern in the human body was acquired in a dynamic fashion.

关键词： metabolism dosage Whole

Optimal Constrained Self-learning Battery Sequential Management in Microgrid Via Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 168-176页

作者： qinglai wei Derong Liu Yu Liu Ruizhuo Song IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing Institute of Automation Chinese Academy of Sciences

This paper concerns a novel optimal self-learning battery sequential control scheme for smart home energy systems.The main idea is to use the adaptive dynamic programming(ADP) technique to obtain the optimal battery sequential control iteratively. First, the battery energy management system model is established, where the power efficiency of the battery is considered. Next, considering the power constraints of the battery, a new non-quadratic form performance index function is established, which guarantees that the value of the iterative control law cannot exceed the maximum charging/discharging power of the battery to extend the service life of the battery.Then, the convergence properties of the iterative ADP algorithm are analyzed, which guarantees that the iterative value function and the iterative control law both reach the optimums. Finally,simulation and comparison results are given to illustrate the performance of the presented method.

关键词： Adaptive critic designs adaptive dynamic programming(ADP) approximate dynamic programming battery management energy management system neuro-dynamic programming optimal control smart home

Residential Energy Scheduling for Variable Weather Solar Energy Based on Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 36-46页

作者： Derong Liu Yancai Xu qinglai wei Xinliang Liu Guangdong University of Technology Guangzhou 510006 China The State Key Laboratory of Manage-ment and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China The Bureau of Informationization Development Cyberspace Administration of China Beijing 100010 China IEEE

The residential energy scheduling of solar energy is an important research area of smart grid. On the demand side, factors such as household loads, storage batteries, the outside public utility grid and renewable energy resources, are combined together as a nonlinear, time-varying, indefinite and complex system, which is difficult to manage or optimize. Many nations have already applied the residential real-time pricing to balance the burden on their grid. In order to enhance electricity efficiency of the residential micro grid, this paper presents an action dependent heuristic dynamic programming(ADHDP) method to solve the residential energy scheduling problem. The highlights of this paper are listed below. First,the weather-type classification is adopted to establish three types of programming models based on the features of the solar energy. In addition, the priorities of different energy resources are set to reduce the loss of electrical energy transmissions.Second, three ADHDP-based neural networks, which can update themselves during applications, are designed to manage the flows of electricity. Third, simulation results show that the proposed scheduling method has effectively reduced the total electricity cost and improved load balancing process. The comparison with the particle swarm optimization algorithm further proves that the present method has a promising effect on energy management to save cost.

关键词： Action dependent heuristic dynamic programming adaptive dynamic programming control strategy residential energy management smart grid