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2nd International Conference on Cyber-Energy systems and intelligent Energy, ICCSIE 2024

作者： Lv, Changyao Wang, Yaqi Chen, Yudong Yu, Zhuo Hu, Guoliang Wu, Hongliang Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China Shanghai Aircraft Manufacturing Co. Ltd. Shanghai201324 China

ISBN: (纸本)9798350373318

In the aviation industry, anodic oxidation serves as a core process for surface modification of aluminum alloy components, albeit accompanied by high energy consumption. Accurate prediction of key parameters can offer decision support for the intelligent control and energy optimization of anodic oxidation. However, the limited sample size resulting from the high cost of data collection and the complex nonlinear patterns caused by the synergy of multiple factors pose a challenge in accurately predicting key parameters. Therefore, we propose a key parameters prediction method based on the Maximum Information Coefficient (MIC), Beluga Whale Optimization algorithm (BWO), and XGBoost algorithm. Considering the adverse impact of low correlation parameters on prediction accuracy, we first use MIC to extract features from the original data. Then, XGBoost is used to integrate multiple decision trees to ensure the strong fitting ability for nonlinear relationships. Compared to deep learning models, XGBoost performs well even in a limited sample size. In addition, considering XGBoost is prone to overfitting training data as an ensemble learning algorithm, we employ the BWO to optimize four key parameters of the model that are difficult to choose, thereby enhancing model's generalization. The model's performance is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with values of 0.04388, 0.09410, and 0.20730%, respectively. The experimental results demonstrate that the proposed method outperforms traditional approaches, enabling precise prediction of key parameters and holding significant value for the intelligent control and energy optimization of anode oxidation processes. © 2024 IEEE.

关键词： Anodic oxidation

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The improved approach for calculating residual error rates in SIS communication 12

The improved approach for calculating residual error rates i...

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12th International Conference on CYBER Technology in Automation, control, and intelligent systems, CYBER 2022

作者： Zhou, Xiufang Xu, Aidong Yan, Bingjun Sun, Yue Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

The residual error rate is an essential parameter for evaluating the functional safety of a communication system, based on the requirements of safety communication in the safety instrumented system (SIS). The traditional approach of quantifying residual error rates is incomplete in some cases. The proposed improvements focus on the different cases addressing full and partial redundancy models, time expectations and different verification approaches for connection identification. A hypergeometric distribution approach is used when the partial message redundancy mode is considered. © 2022 IEEE.

关键词： Redundancy

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Design of Functional Safety Pressure Transmitter and Safety Assessment 23

Design of Functional Safety Pressure Transmitter and Safety ...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Yan, Bingjun Zhou, Xiufang Zhang, Bo Wang, Zhiping Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781665494571

Based on functional safety standard IEC61508, this paper studies the functional safety approaches of the pressure transmitter. Following the 1oo1D architecture, self-diagnostics measures are used in this functional safety pressure transmitter. In order to improve diagnostic coverage, dual CPUs are used to compare results at different calculation stages. The FTA analysis and Markov model are used for safety verification. Furthermore, the safety failure fraction (SFF) and probability of failure on demand (PFD) are analysed, and the results indicate that safety integrity level is SIL2. © 2021 IEEE.

关键词： Transmitters Smart cities Phase frequency detectors Markov processes Reliability engineering Hardware Safety

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Research on Optimization of Aluminum Electrolysis Product Tending Machine Queuing System with Non-preemptive Priority

Research on Optimization of Aluminum Electrolysis Product Te...

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2022 International Conference on Mechanisms and robotics, ICMAR 2022

作者： Song, Libo Shi, Haibo Liu, Chang Zhu, Jun Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510657328

Product tending machine (PTM) is one of the most important equipment in the aluminum electrolysis production process, for the problem of PTM optimization, a queuing system model of aluminum electrolysis PTM is proposed for the first time. According to the actual production situation of the aluminum electrolysis industry, a non-preemptive priority M/G/1 aluminum electrolysis PTM queuing system model is defined, and the general calculation formula of the operating index of the non-preemptive priority PTM queuing system is given, including queuing system length, waiting time, optimal service rate, etc. According to the actual production data of an aluminum factory, the relevant indicators were calculated and analyzed, and the relationship between the operating indicators and the number of electrolysis cells was drawn. Finally, under the conditions of meeting different operating indicators, the optimal matching scheme of PTM and aluminum electrolysis cells was given. © 2022 SPIE.

关键词： Queueing theory

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A History Information-Based A* Algorithm for the Path Planning with Multiple Alternative Destinations

A History Information-Based A* Algorithm for the Path Planni...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Ke Wang Wei Liang Huaguang Shi Jialin Zhang Qi Wang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Artificial Intelligence Henan University Zhengzhou China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

As a cornerstone technology in automation, path planning plays a crucial role across various domains, including logistics, autonomous vehicles, and robotics. A novel path planning challenge, focusing on routes with multiple alternative destinations, has emerged as a focal point in industrial settings. Traditional approaches such as breadth-first and heuristic searches lack specific optimizations for this challenge, resulting in suboptimal efficiency. This paper introduces a new approach to the path planning problem with multiple alternative destinations that utilizes historical data. It features three heuristic strategies: leveraging historical information for search acceleration, pruning based on the length of the current shortest path, and searching in ascending order of the Manhattan distance. These strategies enhance the search efficiency by leveraging historical information for faster searches and pruning based on real-time search outcomes. Simulation results show that the proposed algorithm outperforms the existing works in terms of the computational cost.

关键词： Service robots Navigation Simulation Focusing Path planning Real-time systems Computational efficiency

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Discrete particle swarm algorithm with Q-Learning for solving flexible job shop scheduling problem with parallel batch processing machine 2

Discrete particle swarm algorithm with Q-Learning for solvin...

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2022 2nd International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2022

作者： Song, Libo Liu, Chang Shi, Haibo Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

For the flexible job shop scheduling problem with parallel batch processing machines (FJSP-PBPM), the mathematical model of the problem is defined, and an improved enhanced discrete particle swarm algorithm is proposed to solve this problem. In terms of global search, an improved discrete particle swarm algorithm is adopted, and effective particle velocity and position update formulas are designed;in the local search, in order to speed up the convergence speed and avoid local convergence, it is integrated into the q-learning method in reinforcement learning. The state space, action space, reward function, and Q-table update methods that meet the scheduling problem are designed, and the proposed hybrid algorithm achieves an effective balance between global search and local search capabilities. At the same time, according to the characteristics of FJSP-PBPM, effective process sequence scheduling rules and batch machine selection rules are designed respectively to improve the search ability of the algorithm. Through the standard FJSP benchmark problem and the production data of a transformer manufacturer that meets the characteristics of the FJSP-PBPM problem, the validity and feasibility of the proposed algorithm are verified. © Published under licence by IOP Publishing Ltd.

关键词： Reinforcement learning

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Blockchain-based Dependable Task Offloading and Resource Allocation for IIoT via Multi-Agent Deep Reinforcement Learning

Blockchain-based Dependable Task Offloading and Resource All...

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IEEE Conference on Vehicular Technology (VTC)

作者： Peifeng Zhang Chi Xu Changqing Xia Xi Jin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

Task offloading and resource allocation are fundamental and crucial for the edge computing-enhanced industrial Internet of things, where the security and credibility among massive heterogeneous devices are being challenged. This paper first proposes a novel blockchain consensus scheme named replicated and Byzantine fault tolerant, which can enhance the trust among nodes with the low communication cost. Then, with the objective of minimizing the task completion time, which includes credible verification, task offloading and transaction record, a joint task offloading and resource allocation problem with respect to blockchain verification ratio, offloading decision, communication and computing resources is formulated. Due to its non-convexity and the decentralized characteristic of blockchain, a multi-agent deep reinforcement learning algorithm with deterministic policy gradient is proposed to appropriate the optimal solution. Experiment results confirm the effectiveness of the proposed scheme in guaranteeing the timeliness and security.

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Description and fault diagnosis in autonomous underwater vehicles based on ontologies

Description and fault diagnosis in autonomous underwater veh...

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Ocean Studies (ICOS), International Conference on

作者： Timoshenko Alexander Zuev Alexander Mursalimov Eduard Gribova Valeria Inzartsev Alexander Department of Automation and Robotics Laboratory of intelligent systems for marine robots Far Eastern Federal UniversityInstitute of Marine Technology Problems FEB RAS Vladivostok Russia Laboratory of Intelligent Systems Institute of Automation and Control FEB RAS Vladivostok Russia Laboratory of Control Systems Institute of Marine Technology Problems FEB RAS Vladivostok Russia

ISBN: (纸本)9781665473736

The paper proposes new ontologies for describing and diagnosing malfunctions of subsystems of autonomous underwater vehicles (AUV) as a part of the development of a previously created approach to the intelligent diagnosis of these vehicles using knowledge bases. To implement this approach, it is proposed to use two knowledge bases, one of which describes malfunctions, features for their identification and actions necessary to adapt to the negative consequences caused by the appearance of these malfunctions. The other database contains information about the main subsystems of the AUV, devices and replaceable modules, as well as the states they may be in. Knowledge bases are used in the work of the intelligent control-emergency system (ICES) on board the AUV, which allows for comprehensive functional diagnostics of all subsystems of the device, including payload modules, as well as adaptation to the consequences of emerging malfunctions, taking into account the actual cause-and-effect relationships between them. To test the system’s operability, a prototype was developed. The results of the prototype simulation showed that ICES performs the tasks and can be implemented on the onboard computers of existing AUV using well-known programming technologies.

关键词： Performance evaluation Autonomous underwater vehicles Simulation Knowledge based systems Prototypes Ontologies Programming

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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The Development of a Marine Internet of Things System Architecture for the control of Heterogeneous Robotic Agents

The Development of a Marine Internet of Things System Archit...

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Ocean Studies (ICOS), International Conference on

作者： Aleksey A. Kabanov Vadim A. Kramar Denis A. Tokarev Kirill V. Dementiev Department of Informatics and Control in Technical Systems Sevastopol State University Sevastopol Russian Federation Robotics and Intelligent Control System Laboratory Sevastopol State University Sevastopol Russian Federation

ISBN: (纸本)9781665473736

To create a platform for the Marine IoT for ensuring the interaction and digital navigation of heterogeneous marine robotic agents, it is necessary to combine into one network heterogeneous robotic agents, active and passive means of communication and illumination of the underwater and surface environment (marine communication buoys, underwater sonar stations, coastal connection posts). For their joint work, it is necessary to create a communication system unifying all elements of the platform, an integrated navigation and information management system for solving complex problems of navigation and motion control of robotic agents included in the platform to implement a joint mission. To do this, it is necessary to define the architecture of the platform to use a unified approach to data exchange.

关键词： Underwater communication systems architecture Sonar Sea measurements Switches Network architecture User interfaces

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