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Event-/Self-Triggered Adaptive Optimal Consensus control for Nonlinear Multiagent system With Unknown Dynamics and Disturbances

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IEEE TRANSACTIONS ON CYBERNETICS 2025年第3期55卷 1476-1485页

作者： Wei, Qinglai Jiang, Hao Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

In this article, the optimal consensus tracking control for nonlinear multiagent systems (MASs) with unknown dynamics and disturbances is investigated via adaptive dynamic programming (ADP) technology. Taking into account the disturbance as control inputs, the optimal control problem for the nonlinear MASs is reformulated as a multiplayer zero-sum differential game. In addition, a single network ADP structure is constructed to approach the optimal consensus control policies. Subsequently, an event triggering mechanism is implemented to reduce the workload of the controller and conserve computing and communication resources. Since then, in order to further streamline the intricacies of controller design, this work is extended to self-triggered cases to alleviate the need for hardware devices to continuously monitor signals. By using the Lyapunov method, the stability of the nonlinear MASs and the uniform ultimate boundedness (UUB) of the weight estimation error of the critic neural network (NN) is proved. Finally, the simulation results for an MAS consisting of a single-link robot validate the effectiveness of the proposed control method.

关键词： Consensus control Artificial neural networks Vectors Optimal control Event detection Nonlinear dynamical systems Multi-agent systems Monitoring Hardware Directed graphs Adaptive dynamic programming (ADP) event-triggered control (ETC) nonlinear multiagent systems optimal consensus control self-triggered control (STC)

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Approximate Markov Perfect Equilibrium of Joint Offloading Policy for Multi-IV Using Reward-Shared Distributed Method

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第2期9卷 3658-3671页

作者： Li, Chao Liu, Fagui Wang, Bin Tang, Xuhao Liu, Jie Chen, C. L. Philip South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Peng Cheng Lab Cyberspace Secur Res Ctr Shenzhen 518066 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China

In this article, we investigate the problem of optimizing the joint offloading policy in a distributed manner for multiple intelligent vehicles (IVs). During the journey in vehicular edge computing (VEC) networks, IVs continually optimize their joint offloading policy to minimize the long-term accumulated costs generated by executing computational tasks. The stochastic and repetitive interactions among IVs is modeled as a Markov game process. In this way, the optimization of the joint offloading policy is transformed to approximate a Markov perfect equilibrium in a general-sum Markov game. Moreover, we argue that training in the practical VEC networks using the classical centralized training and decentralized executing (CTDE) framework involves challenges of privacy and computational complexity. Motivated by these, we propose a reward-shared distributed policy optimization (RSDPO) method for the considered VEC networks to optimize the joint offloading policy. The experimental results demonstrate that the set of joint offloading policies using RSDPO approximates a Markov perfect equilibrium, and our RSDPO presents significant advantages in terms of converged latency and energy consumption compared with other methods.

关键词： Vehicular edge computing joint offloading policy distributed policy optimization Markov game

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Parallel Transportation in TransVerse: From Foundation Models to DeCAST

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION systemS 2023年第12期24卷 15310-15327页

作者： Zhao, Chen Wang, Xiao Lv, Yisheng Tian, Yonglin Lin, Yilun Wang, Fei-Yue Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Anhui Univ Sch Artificial Intelligence Hefei 230039 Peoples R China Shanghai AI Lab Shanghai 200232 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau Peoples R China

Rapid development of AI technologies has propelled the seamless integration of physical and cyber worlds with various kinds of online/offline information collected from millions of multimodal sensing systems. The complexity, diversity and uncertainty inherited in such systems, such as Intelligent Transportation systems (ITSs), have gone far beyond human capacity of managing and controlling. Our team is among the first to propose the idea of utilizing the nearly unlimited computational resources in cyberspace to construct a bottom-up and top-down combined artificial ITSs for testing, experimenting, representation, verification, and validation of physical ITSs. Especially, the parallel transportation has been developed for safer, smarter, greener, and more reliable transportation services. After three decades of research and field studies, the DeCAST in Transverse, i.e., Decentralized/Distributed Autonomous Operations/Organizations (DAO) in transportation systems, has been envisioned. In this paper, we introduce its architecture, operational processes, software and hardware platforms, and real world applications. Specifically, a transportation foundation model driven by artificial transportation systems, parallel learning and federated intelligence, named TengYun, is outlined for DeCAST.

关键词： Cyber-physical-social systems (CPSS) artificial systems computational experiments parallel execution (ACP) decentralized/distributed autonomous operations and organizations (DAO) big AI models

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A fuzzy model predictive controller for stick-slip type piezoelectric actuators

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OPTIMAL control APPLICATIONS & METHODS 2023年第3期44卷 1058-1073页

作者： Cheng, Long Wang, Ang Qin, Shijie Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat 95 Zhongguancun East Rd Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China

In nano/micro-positioning applications, stick-slip type piezoelectric actuators (SSPEAs) are usually employed for a satisfactory performance in both the movement range and the positioning accuracy. Unfortunately, the controller design of SSPEAs is a challenging task, which is seldom studied in the literature. So this article presents an idea of using the fuzzy model predictive control approach for the high-precision positioning. First, a prototype of the stick-slip type piezoelectric actuator is designed. Then a Takagi-Sugeno fuzzy model is established for the entire SSPEA, whose parameters can be further adapted by the recursive estimation approach based on the online measurement. Based on this model, a predictive controller can be designed for SSPEAs. Compared to some existing studies, the proposed fuzzy model directly describes the input-output relationship of the entire SSPEA rather than modeling separately. As a result, the controller can be simplified. Finally, some experiments are conducted on the SSPEA prototype, which demonstrates a satisfactory control performance

关键词： adaptive fuzzy model model predictive control piezoelectric actuator stick-slip device

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Optimal Spin Polarization control for the Spin-Exchange Relaxation-Free system Using Adaptive Dynamic Programming

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systemS 2024年第5期35卷 5835-5847页

作者： Wang, Ruigang Wang, Zhuo Liu, Sixun Li, Tao Li, Feng Qin, Bodong Wei, Qinglai Beihang Univ Hangzhou Innovat Inst Zhejiang Prov Key Lab Ultra Weak Magnet Field Spa Hangzhou 310051 Peoples R China Beihang Univ Sch Instrumentat Sci & Optoelect Engn Beijing 100191 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

This work is the first to solve the 3-D spin polarization control (3DSPC) problem of atomic ensembles, which controls the spin polarization to achieve arbitrary states with the cooperation of multiphysics fields. First, a novel adaptive dynamic programming (ADP) structure is proposed based on the developed multicritic multiaction neural network (MCMANN) structure with nonquadratic performance functions, as a way to solve the multiplayer nonzero-sum game (MP-NZSG) problem in 3DSPC under the constraints of asymmetric saturation inputs. Then, we utilize the MCMANNs to implement the multicritic multiaction ADP (MCMA-ADP) algorithm, whose convergence is proven by the compression mapping principle. Finally, the MCMA-ADP is deployed in the spin-exchange relaxation-free (SERF) system to provide a set of control laws in 3DSPC that fully exploits the multiphysics fields to achieve arbitrary spin polarization states. Numerical simulations support the theoretical results.

关键词： 3-D spin polarization control (3DSPC) adaptive dynamic programming (ADP) asymmetric input constraint multicritic multiaction neural networks (MCMANNs) multiphysics multiplayer nonzero-sum game (MP-NZSG) spin-exchange relaxation-free (SERF).

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Web3-Based Decentralized Autonomous Organizations and Operations: Architectures, Models, and Mechanisms

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第4期53卷 2073-2082页

作者： Qin, Rui Ding, Wenwen Li, Juanjuan Guan, Sangtian Wang, Ge Ren, Yuhai Qu, Zhiyou Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau Peoples R China North Automat Control Technol Inst Lab Parallel Intelligence Taiyuan 030006 Peoples R China

Empowered by blockchain and Web3 technologies, decentralized autonomous organizations (DAOs) are able to redefine resources, production relations, and organizational structures in a revolutionary manner. This article aims to reanalyze DAOs from the perspectives of organization and operation, and provide a more precise definition of DAOs as DAOs and Operations. Based on this, the fundamental principles and requirements of DAOs are explained, while the infrastructure based on cyber- physical-social system (CPSS) and parallel intelligence, as well as the supporting technologies, such as digital twins, metaverse, and Web3, are discussed. Besides, a five-layer intelligent architecture is presented, and the closed-loop equation and new function oriented intelligent algorithms are also proposed. Moreover, the governance mechanisms from the individual, organizational and social perspectives are discussed, and the incentive mechanisms for the human, robot, and digital human are analyzed. This article can be regarded as a stepping stone for further research and developments of DAOs.

关键词： Blockchain decentralized autonomous organi-zation (DAO) and operation intelligent algorithms mechanism design metaverse smart contracts Web3

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Towards the Next Level of Vehicle Automation Through Cooperative Driving: A Roadmap From Planning and control Perspective

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第3期9卷 4335-4347页

作者： Wang, Haoran Feng, Yongwei Tian, Yonglin Wang, Ziran Hu, Jia Tomizuka, Masayoshi Tongji Univ Key Lab Rd & Traff Engn Minist Educ Shanghai 201804 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Purdue Univ Coll Engn W Lafayette IN 47907 USA Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA

Cooperative Driving Automation (CDA) stands at the forefront of the evolving landscape of vehicle automation, elevating driving capabilities within intricate real-world environments. This research aims to navigate the path toward the future of CDA by offering a thorough examination from the perspective of Planning and control (PnC). It classifies state-of-the-art literature according to the CDA classes defined by the Society of Automotive Engineers (SAE). The strengths, weaknesses, and requirements of PnC for each CDA class are analyzed. This analysis helps identify areas that need improvement and provides insights into potential research directions. The research further discusses the evolution directions for CDA, providing valuable insights into the potential areas for further enhancement and enrichment of CDA research. The suggested areas include: control robustness against disturbance;Risk-aware planning in a mixed environment of Connected and Automated Vehicles (CAVs) and Human-driven Vehicles (HVs);Vehicle-signal coupled modeling for coordination enhancement;Vehicle grouping to enhance the mobility of platooning.

关键词： Literature review cooperative driving automation planning and control

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RadarVerses in Metaverses: A CPSI-Based Architecture for 6S Radar systems in CPSS

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第4期53卷 2128-2137页

作者： Liu, Yuhang Shen, Yu Tian, Yonglin Ai, Yunfeng Tian, Bin Wu, Er Chen, Long Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China North Automat Control Technol Inst Lab Parallel Intelligence Taiyuan 030006 Peoples R China

Metaverses have caused significant changes in the industry and their academic foundation can be traced back to the term cyber-physical-social systems (CPSS), which was proposed in 2010. Radar is an important sensor in sensing systems that are widely applied in many fields, especially, in autonomous driving. To deal with the complex environment, smart radars with real-time information processing capabilities are required. Human factors play a critical role in the operation and management of radar systems, thus, digital twins' radars in cyber-physical systems (CPS) are unable to achieve intelligence in CPSS due to an incomplete consideration of human involvement. For this consideration, we propose a novel framework of RadarVerses for smart radars in metaverses based on ACP-based parallel intelligence, which is also known as cyber-physical-social intelligence (CPSI). RadarVerses consist of five main parts which are physical radars, descriptive radars, predictive radars, prescriptive radars, and deep radars. To construct RadarVerses at the technical level, we introduce four main technical foundations: 1) communication technology;2) scenarios engineering;3) foundation models;and 4) digital workers. In addition, we also provide a case study about LiDARs' predictive maintenance of accumulated snow in RadarVerses.

关键词： Cyber-physical-social systems (CPSS) meta-verses parallel intelligence RadarVerses

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Foundation Vehicles: From Foundation Intelligence to Foundation Transportation for Future Mobility

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第10期8卷 4287-4291页

作者： Wang, Fei-Yue Lv, Chen Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore

IEEE TIV has received its 3251 manuscript submissions, which is nearly twice as many as that of last year, 236 submissions are still being reviewed in our system, and 18 are overdue for review scoring. I would like to express my sincere gratitude to all authors, reviewers, and editorial board members for your invaluable contributions and unwavering support. Your dedication has been instrumental in maintaining the high quality and great service of our journal and fostering a vibrant scholarly community [1], [2], [3], [4], [5], [6], [7].

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