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IEEE Transactions on Industrial Cyber-Physical systems 2024年 2卷 264-280页

作者： Liu, Ruonan Zhang, Quanhu Han, Te Yang, Boyuan Zhang, Weidong Yin, Shen Zhou, Donghua Shanghai Jiao Tong University Department of Automation Shanghai200240 China Tianjin University College of Intelligence and Computing Tianjin300350 China Beijing Institute of Technology Center for Energy and Environmental Policy Research Beijing100081 China Beijing Institute of Technology School of Management Beijing100081 China Beijing Laboratory for System Engineering of Carbon Neutrality Beijing100081 China Nanjing University Center for Advanced Control and Smart Operations Suzhou215163 China Hainan University School of Information and Communication Engineering Haikou570228 China Shanghai Jiaotong University Department of Automation Shanghai200240 China Norwegian University of Science and Technology Trondheim7491 Norway

Industrial Cyber-Physical systems (ICPS) integrating disciplines such as computer science, communication technology, and engineering, have become a crucial component of modern manufacturing and industry. However, ICPS faces numerous challenges during long-term operation, including equipment faults, performance degradation, and security threats, etc. To achieve efficient maintenance and management, prognostics and health management (PHM) has been widely applied in the critical tasks of ICPS such as fault prediction, health monitoring, and maintenance decision-making. The emergence of large-scale foundation models (LFMs) like BERT and GPT marks a significant advancement in artificial intelligence (AI) technology, demonstrating substantial application potential in multiple fields. The accumulation of AI technology, rapid development of LFMs, and the abundance of industrial data and industrial process knowledge provide the foundational conditions for the construction and advancement of industrial LFMs. However, there is currently a lack of consensus on applying LFMs of PHM in ICPS, necessitating a systematic review and roadmap to clarify future development directions. To bridge this gap, this survey provides a comprehensive survey and understanding of the recent advances in LFMs of PHM in ICPS. It provides valuable references for decision makers and researchers in the industry, and helps to further improve the reliability, availability and safety of ICPS. © 2023 IEEE.

关键词： Cyber Physical system

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Optimal control Synthesis of Markov Decision Processes for Efficiency with Surveillance Tasks

Optimal Control Synthesis of Markov Decision Processes for E...

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IEEE Conference on Decision and control

作者： Yu Chen Xuanyuan Yin Hao Ye Shaoyuan Li Xiang Yin Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore Department of Automation Tsinghua University China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We investigate the problem of optimal control synthesis for Markov Decision Processes (MDPs), addressing both qualitative and quantitative objectives. Specifically, we require the system to fulfill a qualitative surveillance task in the sense that a specific region of interest can be visited infinitely often with probability one. Furthermore, to quantify the performance of the system, we consider the concept of efficiency, which is defined as the ratio between rewards and costs. This measure is more general than the standard long-run average reward metric as it aims to maximize the reward obtained per unit cost. Our objective is to synthesize a control policy that ensures the surveillance task while maximizes the efficiency. We provide an effective approach to synthesize a stationary control policy achieving $\epsilon$-optimality by integrating state classifications of MDPs and perturbation analysis in a novel manner. Our results generalize existing works on efficiency-optimal control synthesis for MDP by incorporating qualitative surveillance tasks.

关键词： Measurement Costs Surveillance Perturbation methods Markov decision processes Optimal control Optimization Standards

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Triggered Mechanism for Strict Feedback systems Under Unknown control Directions

Triggered Mechanism for Strict Feedback Systems Under Unknow...

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Asian control Conference

作者： Guilong Liu Hongda Wu Yongliang Yang Wei Xie Weidong Zhang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example.

关键词： Asymptotic stability Target tracking Stability criteria control systems Optimization Convergence

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Collaboration Strategies for Two Heterogeneous Pursuers in A Pursuit-Evasion Game Using Deep Reinforcement Learning

Collaboration Strategies for Two Heterogeneous Pursuers in A...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhanping Zhong Zhuoning Dong Xiaoming Duan Jianping He The School of Automation Science and Electrical Engineering Beihang University Beijing China The Department of Automation Ministry of Education of China Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We investigate a pursuit-evasion game taking place in an unbounded three-dimensional space, where a flexible pursuer with hybrid dynamics collaborates with a fast pursuer and aims to capture a flexible evader within a finite time. The key feature of this problem lies in the hybrid dynamics of the flexible pursuer, which can change its dynamics once during the game and switch to a fast pursuer with increased speed but lower maneuverability. To address this challenge, we devise a hybrid strategy based on the soft actor-critic framework, tailored specifically for the flexible pursuer, which encompasses both maneuvering and switch tactics. We introduce a switch factor to the input of the actor network and incorporate switch actions to further expand the action space. These additions enable the flexible pursuer to execute maneuvering actions and determine a moment to switch to a fast pursuer. The reward function is designed to account for related angle, altitude, speed, and sparse reward. Through extensive ablation experiments conducted in a simulated environment, we demonstrate the efficacy of our algorithm in facilitating the learning of hybrid strategies for the flexible pursuer, resulting in significantly improved capture rates compared to alternative methods.

关键词： Solid modeling Three-dimensional displays Heuristic algorithms Collaboration Switches Games Deep reinforcement learning Vectors Intelligent robots

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Edge-Assisted Flexible Platooning of Connected and Automated Vehicles Under Traffic Anomaly

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IEEE Transactions on Vehicular Technology 2025年

作者： Gao, Fengkun Yang, Bo Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

The platooning of connected and automated vehicles (CAVs) has the great potential to significantly improve travel experience in terms of safety, comfortableness, and energy efficiency. However, constrained by sensing range and prediction accuracy, the performance of CAV platoon can not be guaranteed in the scenario of mixed traffic consisting of CAVs and human-driven vehicles (HDVs). This is not only due to the uncertainty of HDVs but also related to the occurrence of various traffic anomalies, such as emergency braking and accidents. In this paper, we aim to investigate an efficient control strategy to guarantee the operation of the platoon in mixed traffic, especially in the case of traffic anomalies. To tackle the problem, an edge-assisted platoon control strategy, called E-CACC, is proposed. First, an error-aware flexible tracking policy is designed to adapt to HDV uncertainties and speed prediction errors. Based on the tracking policy, a zone model predictive control (ZMPC) method is then designed to guarantee travel safety and avoid undesired acceleration. Further, a coordination strategy of CAV platoon and roadside unit (RSU) is proposed to prevent the platoon from potential collision in the case of traffic anomalies, where an event-based communication trigger is designed to determine whether and when the platoon establishes communication links with RSU to acquire exogenous sensing data of anomaly segment. Finally, the evaluation results illustrate the effectiveness of the proposed method in improving travel safety and comfortableness. © 1967-2012 IEEE.

关键词： Braking performance

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End-To-End Autonomous Exploration for Mobile Robots in Unknown Environments through Deep Reinforcement Learning

End-To-End Autonomous Exploration for Mobile Robots in Unkno...

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Li, Zhi Xin, Jinghao Li, Ning Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Autonomous exploration in unknown environments is a significant capability for mobile robots. In this paper, we present an end-To-end autonomous exploration model based on deep reinforcement learning (DRL), which takes the sensor data and a novel exploration map as inputs, and directly outputs the motion control commands of the robot. In contrast to the existing DRL-based exploration methods, the proposed model has no requirements to be combined with the traditional exploration or navigation algorithms, resulting in lower computational complexity. We directly transfer the DRL-based model trained in the training map to four test maps with different sizes and layouts, and the results show that the robot can rapidly adapt to unknown scenes. Besides, a comparison study with RRT-exploration algorithm indicates that the proposed model can reach a higher map exploration rate within less distance and time. Furthermore, we also conduct experiments on the real physical robot to demonstrate the transferability of learned policy from simulation to reality. A video of our experiments in the Gazebo simulator and real world can be found here1 © 2022 IEEE.

关键词： Reinforcement learning

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Carrier Frequency Offset Estimation for MIMO OCDM Underwater Acoustic Communications Based on Null Symbols

Carrier Frequency Offset Estimation for MIMO OCDM Underwater...

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第43届中国控制会议

作者： Buyiyi Wang Peishuo Huang Yichen Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of information and Communication Engineering Hainan University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Orthogonal chirp division multiplexing(OCDM) has emerged as a promising approach for underwater acoustic(UWA)*** the constraints of limited bandwidth resources in the underwater environment,enhancing the data transmission rate necessitates leveraging spatial resources ***,we should integrate multiple-input multipleoutput(MIMO) technology with OCDM UWA communication ***,existing MIMO OCDM systems ignore the interference caused by carrier frequency offset(CFO),which is a primary challenge faced by co-located MIMO systems in underwater *** this paper,we propose a CFO estimator based on the null symbols of the Fresnel domain tailored for MIMO OCDM *** estimator regards the energy leakage on null symbols as the objective function to identify the optimal CFO ***,we design pilot allocation strategies for different transmitters to mitigate co-channel interference in MIMO *** enables the estimation of the channel transfer matrix and simultaneous transmission of information,thereby enhancing adaptability to dynamic UWA ***,we derive a low-complexity equalizer *** simulations,the proposed algorithm demonstrates superior communication performance compared to existing algorithms with and without CFO interference.

关键词： Orthogonal chirp division multiplexing(OCDM) carrier frequency offset(CFO) multiple-input multiple-output(MIMO) underwater communications

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Development of a UAV-based system for Technical Diagnostics of Overhead Power Lines 24

Development of a UAV-based System for Technical Diagnostics ...

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24th International Conference on Computational Problems of Electrical engineering, CPEE 2023

作者： Kozlovskyi, Oleksandr Trushakov, Dmitro Rendzinyak, Serhiy Korud, Vasyl Central Ukrainian National Technical University Department of Electrical Systems and Energy Management Kropyvnytskyi Ukraine Central Ukrainian National Technical University Department of Automation and Control in Technical Systems Kropyvnytskyi Ukraine Ivan Franko National University of Lviv Faculty of Electronics and Computer Technologies Lviv Ukraine Lviv Polytechnic National University Institute of Power Engineering and Control System Lviv Ukraine

ISBN: (纸本)9798350330342

The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Enhancing Resource Allocation and Performance in Multi-Layer Industrial IoT Through Adjustable Strategy Integrating Cooperative Communication and Edge Computing

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IEEE Internet of Things Journal 2025年

作者： Sun, Mingyue Yuan, Yazhou Ma, Kai Chen, Cailian Zhang, Jianmin Luo, Xiaoyuan The Institute of electrical Engineering Yanshan University Qinhuangdao066004 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The Automation Department of the Baosteel Research Institute Shanghai200240 China

Reliable bidirectional communication between the control center (CC) and manufacturing devices (MDs) along with efficient resource allocation are critical for the Industrial Internet of Things (IIoT). However, due to the limited network resources of IIoT devices and the intertwined nature of communication and computation resources, achieving efficient optimization of these resources presents significant challenges. In this paper, we propose a multi-layer communication architecture for the IIoT based on edge computing and cooperative communication technologies, where resource-constrained MDs upload data to edge servers (ESs) for processing. To address the issues of resource scarcity and coupling, we establish a bandwidth release model (BRM) to analyze and quantify the relationship between computation and communication resources. This elucidates the interaction mechanisms between ‘transmission-computation’ performance. Furthermore, to prevent excessive data upload to ESs, which could lead to node overload and network congestion, we employ game theory to develop a pricing mechanism for resource allocation, where ESs charge for computation services. Specifically, we construct a Lagrangian framework to determine a resource allocation scheme, aiming to maximize the utility of the factory. Simulation results indicate that compared to common methods employed in existing works, our strategy enhances factory utility by 29.79%. © 2014 IEEE.

关键词： Edge computing

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Vision-Based Autonomous Landing of a Quadrotor UAV on a Double-Layered Nested Landing Marker

Vision-Based Autonomous Landing of a Quadrotor UAV on a Doub...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Mu, Lingxia Zhang, Yuan Xin, Jing Zhang, Youmin School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Department of Mechanical and Industrial Engineering Concordia University MontrealH3G 1M8 Canada

ISBN: (纸本)9789811966125

This paper focuses on the vision-based autonomous landing mission of a quadrotor unmanned aerial vehicle (UAV). A double-layered nested Aruco landing marker is designed which can adapt to the situation that the field of sight of airborne camera changes as the UAV’s altitude decreases during the landing. Then, considering that the landing marker might be obstructed in certain situation, traditional Aruco detection method cannot effectively recognize marker. A YOLOv4 deep learning algorithm is used for marker detection. In addition, to address the problem of false detection in some test results, normalized Wasserstein distance is used to replace the non-maximum suppression to deal with redundant frames. The UAV’s relative location to the marker is then calculated and landing mission is finally achieved by the image-based visual servoing strategy. The simulation on Gazebo demonstrates that the designed marker is effective for the UAV landing mission and the revised YOLOv4 detection algorithm can increase detection results accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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