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43rd Chinese Control Conference, CCC 2024

作者： Tao, Liujun Wu, Huaiyu Zheng, Xiujuan Wuhan University of Science and Technology Eng. Res. Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan430081 China Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan430081 China

ISBN: (纸本)9789887581581

Accurately predicting the Remaining Useful Life (RUL) of lithium-ion batteries is crucial for their safety and reliability, and it's an important issue of concern for battery management systems. The existing RUL prediction is mainly concentrated on a single source characteristics or a single model, and generally only the time features of the battery Health Indicators (HIs) are considered. This article proposes a multi-feature and multi-graph neural network fusion method for predicting the RUL of batteries. First of all, extract HIs from multiple aspects such as voltage, current, temperature curve and other aspects during partial charging and discharging processes, and construct HIs graph. Secondly, preliminary predictions of RUL were made using Graph Convolutional Network (GCN), Graph Attention Network (GAT), and Graph Sample and Aggregate Network (GraphSAGE), respectively. In order to improve the prediction accuracy of the model, the model extracts spatial features from non-homologous sources and constructs an HI graph as the primary input. Inspired by the advantages of multi-model fusion, random forest regression is used for multi model fusion. To verify the effectiveness of the model, comparative experiments were conducted on the Massachusetts institute of Technology (MIT) battery dataset. The results indicate that the proposed method has better accuracy and stronger robustness in RUL prediction. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Lithium-ion batteries Multi graph neural network Multi source spatial features Prediction of remaining useful life Random forest regression

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Energy Management for Industrial Robots based on automationML

Energy Management for Industrial Robots based on AutomationM...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Valentyn Petrichenko Gregor Thiele Department for Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology IPK Berlin Germany

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Motivated by political regulations and rising energy prices, companies strive for implementing energy management and for reducing their energy consumption. It is an expenditure of work for the energy manager to gather all relevant information about the facilities and machines (e.g. meaning of measurement and control signals, limits of these quantities, installed nominal capacities). In many cases, there is digital planning data from the planning, construction and commissioning phases. Using automationML, this information can be used collaboratively not only for engineering and maintenance but for energy monitoring and optimization. In this study, an industrial robot and two conveyors are integrated in the wide-spread energy management software suite EnEffCo. We document the method and results. Implications for deriving optimization formulations are discussed.

关键词： Service robots Industrial robots Software Regulation Planning Maintenance Energy management Information technology Optimization Monitoring

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FDNet: Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Fourier Series and DenseNet 5

FDNet: Remaining Useful Life Prediction for Lithium-Ion Batt...

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5th International Conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Chen, Siwen Zheng, Xiujuan Shanghai United Imaging Healthcare Co. Ltd. Shanghai China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan China

ISBN: (纸本)9798331530334

To enhance the prediction accuracy of the remaining useful life (RUL) of lithium-ion batteries, this study proposes a novel RUL prediction model, termed FDNet, which integrates Discrete Fourier Series (DFS) and Densely Connected Convolutional Networks (DenseNet). In contrast to traditional methods that rely on one-dimensional (1D) numerical representations of time-series data, this model utilizes a two-dimensional (2D) visual representation for direct RUL prediction. First, the DFS is employed to convert 1D time-series signals into a 2D time-frequency domain, enabling the extraction of high-dimensional features from the original data. Then, these 2D images are subsequently input into DenseNet, which learns the mapping between the image features and the RUL targets. Finally, the proposed model is validated using the NASA lithium-ion battery aging dataset, and the results indicate that FDNet achieves superior prediction accuracy and exhibits notable robustness. © 2024 IEEE.

关键词： Prediction models

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Modeling of the Constant-Current Stimuli Response of a Bio-Robot for Long-Term Motion Control

Modeling of the Constant-Current Stimuli Response of a Bio-R...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhou, Jie Fang, Yuan Chen, Yang Li, Yao Li, Bing Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China

ISBN: (纸本)9781665481090

Bio-robots continue to receive attention because of their small size and low power consumption. Unfortunately, it currently faces two major obstacles before practical application. The first is the habituation issue, insects are difficult to be effectively controlled for a long time by electrical stimuli signals. The other one is the lack of model for motion control. In this research, we established a stimuli-response model for cockroach bio-robot based on long time current. A more convenient optic lobe implantation method has been proposed, which has lower attenuation and better stimuli effect. Constant electrical stimuli also significantly increased the number of effective controls for crawling. A cockroach bio-robot stimuli distance response model was established and validated with experiment data. Five parameters were including in this model, namely sex, length, weight, current amplitude and equivalent stiumated-number. This model can predict the movement distance of biological robots well. © 2024 IEEE.

关键词： Microrobots

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Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3108-3118页

作者： Shi, Xueya Peng, Zhinan Yu, Junzhi Li, Hongfei Southwest University College of Electronic and Information Engineering Chongqing400715 China Sichuan Artificial Intelligence Research Institute Yibin644000 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controllers, the complete timeline is divided, and the AET controller is built with two switching modes based on the intervals of dormant and active periods of DoS attacks in which the system is located. Second, to reconcile AET controller with actuator saturation, a switched system modeling approach is established that explicitly incorporates saturation constraints into the coupled network dynamics. Third, a switched Lyapunov-Krasovskii functional (LKF) is proposed, with which sufficient conditions are provided to ensured the RPS, and a joint design strategy is developed for the desired triggered matrix and feedback gain using linear matrix inequalities (LMIs). Moreover, the results are generalized to the case of actuator faults, indicating that the system is able to achieve RPS with actuator faults. Finally, the proposed method is verified through an example. © 2013 IEEE.

关键词： Lyapunov functions

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System Design and Workspace Optimization of a Parallel Mechanism-Based Portable Robot for Remote Ultrasound 8

System Design and Workspace Optimization of a Parallel Mecha...

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8th International Conference on automation, Control and robotics Engineering, CACRE 2023

作者： Deng, Zhaokun Hou, Xilong Hao, Mingrui Wang, Shuangyi Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong

ISBN: (纸本)9798350302776

The robotic ultrasound system has the potential to improve the conventional practice of diagnosing. Because of the adequate degrees of freedom embedded in a small footprint, the parallel mechanism-based ultrasound robot has attracted attention in the field. However, the analysis of its configuration, design parameters, and workspace is limited. To solve this issue and further promote the potential clinical translation, this paper proposes a task-driven, two-stage mechanism optimization method using the effective regular workspace and the local condition index to determine the parameters for the demanding clinic workspace of a parallel mechanism-based ultrasound robot. The design and implementation method of the robot are then introduced, along with the justification of parameter selection. To analyze the performance, an optical tracking-based experiment and a phantom-based human-robot comparison study were performed. The results show that the workspace meets the required clinical needs, and despite its small footprint, the mechanism could have a reasonable workspace. The kinematic error was found to be 0.2 mm and 0.3°. Based on the above results and the quantitative analysis of the ultrasound images acquired manually and robotically, it was concluded that the robot can effectively deliver the demand function and would be a promising tool for further deployment. © 2023 IEEE.

关键词： Ultrasonics

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Synthesis of Diagnostic Observers for Linear systems Based on Optimal Control Methods

Synthesis of Diagnostic Observers for Linear Systems Based o...

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2022 International Conference on Control, automation and Diagnosis, ICCAD 2022

作者： Kabanov, Aleksey A. Zuev, Aleksandr V. Zhirabok, Aleksey N. Filaretov, Vladimir F. Department of Informatics and Control in Technical Systems Sevastopol State University Russia Laboratory of Intelligent Information Systems for Marine Robots Institute of Marine Technology Problems FEB RAS Russia Department of Automation and Robotics Far Eastern Federal University Russia Robotics Laboratory Institute of Automation and Control Processes FEB RAS Russia

ISBN: (数字)9781665497947

ISBN: (纸本)9781665497947

The paper considers the problem of fault identification in dynamic systems described by linear differential equations. To solve this problem, diagnostic observers constructed on the basis of optimal control methods are used. The proposed new method for the synthesis of such observers is based on the idea of introducing a new system with some auxiliary control which plays a role of an unknown vector function describing emerging faults. This control is proposed to be formed in such a way that it provides a minimum for the residual functional. Unlike popular approaches to solving the problem of fault identification based on observers operating in a sliding mode, the proposed method allows us to expand the class of systems for which the identification problem can be solved. It is known that the methods of sliding mode observers design impose certain restrictions on the systems under consideration. The suggested theory is illustrated by an example. The simulation results confirmed the operability of the diagnostic observers synthesized using the method proposed in the work. © 2022 IEEE.

关键词： Linear systems

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Big Data Processing for Bulgarian Healthcare - Smart Cards and Some Simulating Decisions 8

Big Data Processing for Bulgarian Healthcare - Smart Cards a...

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8th International Conference on Big Data, Knowledge and Control systems Engineering, BdKCSE 2023

作者： Boneva, Ani Ivanova, Veronika Vasilev, Plamen Ivanov, Stoyan Ivanova, Tsvetelina Institute of Information and Communication Technologies Bulgarian Academy of Sciences Department of Communication Systems and Services Sofia Bulgaria Institute of Robotics Bulgaria Academy of Sciences Department of Robotized and Mechatronics Intelligent Systems Sofia Bulgaria University of Chemical Technologies and Metallurgy Department of Industrial Automation Sofia Bulgaria

ISBN: (纸本)9798350313246

This publication presents a review of the application of large databases (Big Data) in medicine. The aim of the work is to provide some positive guidelines for the optimization of health care and improvement of patient care in Bulgaria. Therefore, the article discusses designed applications that can find their place in various fields of medicine. Our proposed optimization is the introduction of electronic chip cards. The development assumes that each patient will be provided with a processor card carrying information about basic data related to the condition and its personalization and possible access to this data when necessary. Thus, the proposed solution provides an opportunity to upgrade (for the future) and build an information system with a connection to the health fund. In addition, an early-stage project is described to integrate data from personal portable devices with the electronic health record, thereby providing information to medical personnel about the individual's health status. Portable personal devices and other non-medical equipment generate a huge, almost continuous flow of data that can be useful in making decisions regarding the treatment of patients with various health conditions. The applications described are a continuation of the team's previous developments. © 2023 IEEE.

关键词： Intelligent systems

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Advances and Challenges in Large Model Compression: A Survey 24

Advances and Challenges in Large Model Compression: A Survey

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Xu, Yingying Song, Chunhe Sun, Yong Yu, Shimao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798400717147

With the development of computer technology, large-scale models have gradually evolved from early simple algorithms to today's complex deep neural networks with huge parameter scale and high computational complexity. These large-scale models have greatly advanced the artificial intelligence technology, which has realized revolutionary progress in the fields of image, speech, text and so on. However, the computational and storage requirements of large-scale models are also growing rapidly, which seriously constrains their deployment and application in computing resource-constrained environments. In order to solve this problem, model compression technology has emerged and has been greatly developed. In this paper, we systematically review the key technologies, application scenarios, challenges and future directions of large-scale model compression from the perspective of model compression technology. Our work aims to provide practitioners and researchers with detailed references on the development of the technology, and emphasizes the important role of model compression technology in promoting the development of lightweight artificial intelligence. © 2024 Owner/Author.

关键词： Deep neural networks

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A new SPICE modeling approach of annular MOSFET in 350 nm commercial CMOS process 3

A new SPICE modeling approach of annular MOSFET in 350 nm co...

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3rd International Conference on Electronic Information Engineering and Computer, EIECT 2023

作者： Cheng, He Yang, Zhijia Zhang, Chao Zhang, Zhipeng Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350357707

Annular gate MOSFETs have emerged as potential solutions for radiation-hardened electronics, demonstrating exceptional total ionizing dose tolerance. However, accurate modeling of annular MOSFETs is crucial when designing analog integrated circuits for use in radiation environments, especially when implementing commercial CMOS processes. To enable circuit simulation using tools like SPECTRE/SPICE, foundry-provided PDKs must incorporate a rigorously verified compact model of annular MOSFET behavior. TCAD simulation can then be used to numerically evaluate the current characteristics of the annular MOSFET against the refined compact model constructed from the foundry-provided PDK. In this paper, by aligning the current characteristics of a standard NMOS between TCAD and SPICE simulations, we can verify the material process conditions. Then, based on the material process parameters, the model of the annular gate MOSFET is established using the TCAD simulator. Finally, reasonable agreements are obtained between the TCAD and SPICE simulation results for the IDS-VGS and IDS-VDS characteristics. © 2023 IEEE.

关键词： Foundries

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