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Indoor Fingerprint Positioning Method Based on Real 5G Signals 23

Indoor Fingerprint Positioning Method Based on Real 5G Signa...

引用

7th International Conference on Machine Learning and Soft Computing, ICMLSC 2023

作者： Wang, Changhao Xi, Jin Xia, Changqing Xu, Chi Duan, Yong Shenyang University of Technology Shenyang110870 China 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

ISBN: (纸本)9781450398633

Indoor positioning services are being used more and more widely. However, existing indoor positioning techniques cannot simultaneously take into account low cost, ease of use, high precision, and seamless switching between indoor and outdoor positioning. With the maturity of 5G techniques, 5G-based indoor positioning is gradually being paid attention to. 5G-based indoor positioning does not require additional equipment, and supports flexible indoor and outdoor switching under the same system. However, the 5G-related information used in existing research on 5G indoor positioning is not open to users. Therefore, in this paper, we propose an indoor fingerprint positioning method based on measured 5G signals. This method first collects 5G signals in the positioning area, and processes them to form a fingerprint database. Then, a machine learning algorithm is used to match the signal to be located with the fingerprint database to obtain the positioning result. Finally, we conduct experiments in real field, and the experimental result demonstrates that the positioning accuracy of our proposed method can reach 96%. © 2023 ACM.

关键词： 5G mobile communication systems

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive control

A Real-time Local Planner Design for Smart Wheelchairs Based...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Guanfeng Yu Han Zhang Zehao Wang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities.

关键词： Pedestrians Accuracy Systematics Wheelchairs Estimation Predictive models Real-time systems

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Low-Power Heterogeneous Networking Method Based on NB-IoT and WSN 6

Low-Power Heterogeneous Networking Method Based on NB-IoT an...

引用

6th International Conference on Communication Engineering and Technology, ICCET 2023

作者： Guan, Mo Qi, Liangliang Jin, Xi Guan, Suoling Xia, Changqing Xu, Chi Shenyang University of Technology Shenyang110870 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350336153

Digital oilfields generally adopt the multi-hop technology to expand the network scale, and the data generated depends on the large-scale wireless sensor network (WSN) for transmission. However, multi-hop communication will lead to uneven distribution of network energy consumption and premature death of nodes. To prolong the network lifetime of digital oilfields, we extended the narrowband internet of things (NB-IoT) module on some WSN nodes deployed on site to form heterogeneous nodes. Through the heterogeneity of NB-IoT and WSN, the nodes could transmit as little data as possible from other nodes, fundamentally reducing the node energy consumption. Furthermore, an optimization method was proposed that could simultaneously optimize the network lifetime and node expansion cost. The experimental results revealed that the proposed algorithm could greatly prolong the network lifetime while only introducing a small number of nodes. © 2023 IEEE.

关键词： Internet of things

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AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Zhang, Sichao Liang, Wei Zhang, Yinlong Pang, Zhibo 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Technology Abb Corporate Research Sweden Department of Automation Vasteras72178 Sweden

ISBN: (纸本)9781728119489

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method. © 2022 IEEE.

关键词： Semantics

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Migration node selection strategy based on gray prediction algorithm in trusted environment 2

Migration node selection strategy based on gray prediction a...

引用

2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Wang, Chen Zhang, Bowen Chen, Xin Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9781665408868

This paper studies the selection strategy of task migration nodes. Considering the security of nodes, this paper analyzes the trusted security model of each node of migration candidates. Security credibility includes three aspects: time credibility, behavior credibility and resource credibility. By calculating the trusted values of migration nodes in these three aspects, Three nodes with the lowest trust value are obtained to preliminarily screen the migration nodes, and the final nodes are determined in the remaining nodes. Because the gray prediction algorithm requires a small number of original data models and has a strong discrete type, it is more suitable for the model selected by the task migration nodes. This paper uses the gray prediction algorithm to finally determine the migration nodes, In the experiment, the cloud simulation platform is used to compare the algorithm and random algorithm, and the results show the effectiveness of the algorithm. © 2022 IEEE.

关键词： Forecasting

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Research on information security risk assessment based on integrated influence of neighborhood 6

Research on information security risk assessment based on in...

引用

6th International Conference on Electronic Information Technology and Computer Engineering, EITCE 2022

作者： Wang, Tianyu Zhao, Jianming Zhang, Bowen Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781450397148

At present, the information technology of industrial automation control system is developing rapidly, and the system information security is facing severe challenges. Accurate and efficient risk assessment of industrial control systems is conducive to their protection and efficient production. Although there have been quite a few studies on the risk assessment of industrial control systems, there is less consideration of the interaction between the equipment in the system at present. In view of this, this paper proposes an information security risk assessment method based on the impact of neighborhood integration, which can fully consider the changes of equipment functions within the damaged range of industrial control systems. The experimental results in some model systems reveal that the algorithm in this paper can evaluate the information security risks of industrial control systems more accurately, and provides a theoretical method for the stable operation of industrial systems. © 2022 Association for Computing Machinery.

关键词： Risk assessment

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K-BMPC: Derivative-based Koopman Bilinear Model Predictive control For Tractor-trailer Trajectory Tracking With Unknown Parameters

K-BMPC: Derivative-based Koopman Bilinear Model Predictive C...

引用

IEEE International Conference on robotics and automation (ICRA)

作者： Zehao Wang Han Zhang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC.

关键词： Trajectory tracking Computational modeling Estimation Predictive models control systems Data models Nonlinear dynamical systems

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Design of a Highly Reliable Redundant Network Card Supporting the IEEE1588 Protocol 5

Design of a Highly Reliable Redundant Network Card Supportin...

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5th IEEE International Conference on Electronics Technology, ICET 2022

作者： Zhang, Bo Yan, Bingjun Liu, Mingzhe Xu, Aidong Wang, Kai Wang, Zhiping Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665485081

To adapt to the digital and intelligent trend of ship management and meet the requirements of shipborne industrial Ethernet with high reliability and strong real-time performance, this paper develops a shipboard redundant network card with a Zynq7000 series SoC chip as the main controller, and designs the IEEE1588 IP core and PRP IP core on the FPGA side of SoC. The design of the IEEE1588 IPCore can avoid the impact of the jitter of the upper layer protocol stack on the time stamp accuracy;the PRP IPCore implements dual-network redundancy on the FPGA side, reducing the software overhead of the Ethernet protocol stack on the ARM side, and lowers the impact of network switching on synchronization accuracy. Through testing, the point-to-point synchronization accuracy of the network card is better than 50 ns, and the dual-network redundancy switch can be quickly completed when the network is disconnected. The design of the network card greatly improves the consistency and accuracy of the internal time of the ship system, and meets the requirements for high reliability, fast fault switching and recovery. © 2022 IEEE.

关键词： System-on-chip

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A Novel Semantic-Web Based Technology for control Logic Rapid Reconfiguration of CPPS 7

A Novel Semantic-Web Based Technology for Control Logic Rapi...

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7th International Conference on Intelligent Computing and Signal Processing, ICSP 2022

作者： Wang, Peng Wang, Zhongfeng Wang, Chu Hu, Kunyuan Li, Ligang Song, Chunhe Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665478571

Aiming at solving the problem that the traditional production control system cannot support rapid logical reconfiguration of CPPS, a semantic-web based technology consisting of an overall research framework and three key methods are proposed. Within this overall research framework, product process can be first matched against production resource capabilities, then transformed into the production process of production system, and finally into the control logic of production control system. All the transformations can be done automatically by the help of the proposed semantic-web based methods, namely unified ontology model and related reasoning methods, so that when product process changes, control logic of production can be adjusted efficiently, which enables rapid logical reconfiguration of CPPS. In this paper, the overall framework is first introduced with emphasis on background and technical characteristics of CPPS, analysis of research gaps and overall methods. Then, the three key methods are introduced in detail, namely the unified ontological modelling method of product-process-resources, and the rule-based reasoning methods to automatically transform the production process and control logic, are described in detail. Furthermore, concerning the shortcoming of existing Product-Process-Resource ontological modeling, the description of production system's control behavior is extended within the resource domain, so that key information related to PLC programming such as action sequence and control variable can be integrated and leveraged during the transformation of control logic. Finally, a reconfigurable CPPS prototype is developed based on the proposed framework, and the advantages of the methods are tested and verified. © 2022 IEEE.

关键词： Production control

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RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVED MULTI-OPTIMIZATION ALGORITHM AND SUPPORT VECTOR REGRESSION 14

RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVE...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Tao, Yulong Wang, Jun Wang, Kai School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China Key Laboratory of Intelligent Technology for Chemical Process Industry Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Robotics and Artificial Intelligence Manufacturing Innovation Institute Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781837242672

The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential to mitigate risks and minimize potential losses. This paper introduces a novel fusion algorithm, FPSOGWO, which combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) with an enhanced Circle chaos strategy and a random adaptive weighting strategy. The FPSOGWO algorithm, integrated with Support Vector Regression (FPSOGWO-SVR), was utilized to predict the RUL of health factors in lithium batteries. Compared to other optimization algorithms, FPSOGWO exhibits superior optimization speed and value, effectively overcoming issues of local optimality. Specifically, when benchmarked against the Whale Optimization Algorithm-SVR (WOA-SVR), the R-Square values of FPSOGWO-SVR showed improvements of 15.62%, 1.28%, 5.67%, and 10.65% across four different types of batteries. Experimental results demonstrate that FPSOGWO-SVR provides more accurate RUL predictions for lithium batteries, highlighting its potential for broader application in battery health management systems. © The Institution of Engineering & Technology 2024.

关键词： Support vector regression

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