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A non-interactive verifiable computation model of perceptual layer data based on CP-ABE 2

A non-interactive verifiable computation model of perceptual...

引用

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

作者： Zhao, Jianming Miao, Weiwei Zeng, Zeng 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 State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The computing of smart devices at the perception layer of the power Internet of Things is often insufficient, and complex computing can be outsourced to server resources such as the cloud computing, but the allocation process is not safe and controllable. Under special constraints of the power Internet of Things such as multi-users and heterogeneous terminals, we propose a CP-ABE-based non-interactive verifiable computation model of perceptual layer data. This model is based on CP-ABE, NPOT, FHE and other relevant safety and verifiable theories, and designs a new multi-user non-interactive secure verifiable computing scheme to ensure that only users with the decryption key can participate in the execution of NPOT Scheme. In terms of the calculation process design of the model, we gave a detailed description of the system model, security model, plan. Based on the definition given, the correctness and safety of the non-interactive safety verifiable model design in the power Internet of Things environment are proved, and the interaction cost of the model is analyzed. Finally, it proves that the CP-ABE-based non-interactive verifiable computation model for the perceptual layer proposed in this paper has greatly improved security, applicability, and verifiability, and is able to meet the security outsourcing of computing in the power Internet of Things environment. © 2022 IEEE.

关键词： Internet of things

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Optimization method of Data interaction in power IoT based on particle swarm algorithm 2

Optimization method of Data interaction in power IoT based o...

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

作者： Wang, Tianyu Miao, Weiwei Zeng, Zeng 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 State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The ubiquitous power Internet of things (IoT) constructs an intelligent service system with comprehensive perception, efficient response and flexible processing around all departments of the power system and with the support of communication technologies such as mobile Internet and artificial intelligence. With the rapid development of smart IoT perceptual devices and edge computing, it has become possible for perceptual devices and edge IoT agents to cooperate in processing tasks. The task completion time can be greatly reduced through the cooperative processing among multiple entities in the IoT. However, as the scale of the Internet of things and number of to-be-processed tasks expanding year by year, the simple task data interaction between devices can not meet the needs of the completion time. Therefore, it is an urgent problem to optimize data transmission and data interaction in the process of collaborative task processing among IoT devices. Motivated by this point, we propose an optimization method of data interaction in power IoT based on particle swarm algorithm. Evaluation on example IoT networks shows the effectiveness of our method to reduce overall task completion time. © 2022 IEEE.

关键词： Internet of things

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Trajectory Tracking Error Optimization based on Iterative Learning 4

Trajectory Tracking Error Optimization based on Iterative Le...

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4th IEEE International Conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Huang, Haoran Zhang, Tao Jia, Danping Zhang, Hualiang Yan, Hongyu Pei, Quanshen Ding, Fan Shenyang University of Technology School of Information Science and Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

The X-Y precision plane motion platform is widely used in various precision motion control fields. In this paper, to improve the tracking accuracy of the X-Y precision plane motion table, a high-level iterative learning control with forgetting factor is proposed, and it is combined with a kind of PD-type iterative learning control with low-pass filter, and the method is applied to the Simulink model of the linear motor of the X-Y precision plane platform, thereby improving the trajectory accuracy of the X-Y precision plane motion platform. The traditional ILC has the disadvantage that the more number of iterations, the more divergent tracking error is. The new ILC proposed in this paper can not only effectively reduce the noise, reduce the tracking error, but also eliminate the problem of error divergence caused by too many iterations. At last, the experimental results of high-order PD iterative learning with forgetting factor and low-pass filter, PD iterative learning with low-pass filter, ordinary PD iterative learning are compared. The results show that the high-order PD iterative learning with forgetting factor and low-pass filter has better tracking effect than the first-order iterative learning and other several algorithms. It can make the movement trajectory of the X-Y precision plane motion platform more stable and improve the accuracy. © 2022 IEEE.

关键词： Low pass filters

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New simplified model for an under-actuated quadruped robot in bounding motion

New simplified model for an under-actuated quadruped robot i...

引用

International Conference on control, Instrumentation, and Automation

作者： Hamed Kazemi Vahid Johari Majd Majid M. Moghaddam Intelligent Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Moalem University Tehran Iran Intelligent Control Systems Laboratory Tarbiat Modares University Tehran Iran Robotics and Mechatronics Laboratory Mechanical Engineering Department Tarbiat Moalem University Tehran Iran Mechanical Engineering Department Tarbiat Modares University Tehran Iran

In this paper, a quadruped robot is studied in bounding motion. A new simplified model of quadruped robot in bounding motion with four actuated and two unactuated joints is developed. The kinetic and potential energies of the under-actuated mechanical model of the quadruped robot are obtained and the dynamics of the robot model is derived using the Lagrangian method. It is shown that the dynamical equation of the proposed simplified model belongs to a class of second-order nonholonomic mechanical systems. The main motivation of this paper is to obtain quadruped model in bounding motion such that one can apply different control methods directly or after transformation in the obtained dynamic equations. Utilizing MATLAB, dynamics of the planar model has been simulated in backward and forward states. Physical parameters of the Little-Dog robot as an instance of the quadruped robot are considered in simulation The simulation is without control and therefore is unstable but it illustrates robot's manner in bounding motion before instability.

关键词： Mathematical model Legged locomotion Dynamics Equations Joints Robot kinematics

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Service Encapsulation Method Based on Industrial Internet

Service Encapsulation Method Based on Industrial Internet

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作者： Li, Kai Pan, Hao Tong, Xing Li, Dong Wang, Ting Shenyang University of Chemical Technology Liaoning Shenyang110142 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China

Based on the analysis of software and hardware integration and highly heterogeneous infrastructure in the traditional industrial field, this paper puts forward the concept of service packaging engine, puts forward a unified service packaging model for Industry by using the Internet thinking design mode, and can complete the control of complex industrial field equipment by editing only simple logic in the programming interface. This article focuses on basic service encapsulation. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer programming

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Fault Diagnosis Based on RseNet-LSTM for Industrial Process 5

Fault Diagnosis Based on RseNet-LSTM for Industrial Process

引用

5th IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2021

作者： Yao, Peifu Yang, Shaojie Li, Peng China Copper Co.LTD Kunming China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation 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

Aiming at the problems that conventional data-driven diagnosis methods are difficult to adaptively extract effective features from industrial process data, and do not make full use of the time series characteristics of process data, in this paper, a fault diagnosis method based on residual convolutional neural networks and long short-term memory networks (ResNet-LSTM) is developed. Firstly, the local spatial features of process data are captured by the deep residual convolution network. Then, the time series characteristics of process data are extracted by LSTM. Finally, the output of the fault category is performed through the softmax classifier. This method can extract features adaptively, more fully extract features in time series fault data, and effectively reduce the difficulty of deep neural network training. The benchmark Tennessee-Eastman (TE) process is used to validate performance of the proposed method. The ResNet-LSTM model is compared with the CNN, LSTM, ResNets, CNN-LSTM models, and the experiment results show that the ResNet-LSTM method achieves better performance. © 2021 IEEE.

关键词： Failure analysis

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Effective Decoupled Planning for Continuous Multi-Agent Pickup and Delivery

Effective Decoupled Planning for Continuous Multi-Agent Pick...

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第32届中国控制与决策会议

作者： Zhenbang Nie Peng Zeng Haibin Yu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences University of Chinese Academy of Sciences

Continuous MAPD（Multi-Agent Pickup and Delivery） problem is widely encountered in material transportation ***（Token Passing） is a conflict-free,deadlock-free algorithm for continuous MAPD ***,when TP is used,the number of tasks simultaneously handled by agents is limited by the number of task endpoint *** solve this problem,ITP（Improved Token Passing） is proposed in this *** extra path planning procedure is introduced to improve agent utilization.A complete and optimal A*-based algorithm is designed to solve the low level single agent path planning *** increases system throughput by exploiting all available agents,and remains conflict-free and *** result shows that ITP outperforms TP in terms of system makespan under heavy workload in congested workspace.

关键词： Multi-Agent Pickup and Delivery Multi-Agent Path Finding Decoupled Path Planning

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Research and optimization of conflict search algorithm for multi-agent path planning based on incremental heuristic 2

Research and optimization of conflict search algorithm for m...

引用

2nd International Conference on Computer Vision and Data Mining, ICVDM 2021

作者： Li, Yang Wang, Jun Zhang, Hualiang School of Computer Science Shenyang University of Chemical Technology Shenyang110142 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

Conflict Based Search(CBS) is used for multi-agent Pathfinding (MAPF) to enable each Agent to reach the target node. The CBS algorithm uses the heuristic algorithm A* search to calculate the MAPF solution, and the path planning uses forward search, which cannot explore the path of the unknown region. On this basis, this paper proposes that, in the case of unknown map and changing environment at any time, when encountering new obstacles, the information obtained from previous search should be used without completely replanning the path. Because of the idea of incremental programming, the number of reprogramming times and the number of affected nodes can be reduced. The optimized algorithm consumes less time and memory, and improves the efficiency of path planning. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Motion planning

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Research on cloud-side collaborative task migration strategy based on simulated annealing-Bee Colony Algorithm in Power IoT 2

Research on cloud-side collaborative task migration strategy...

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

作者： Zhang, Bowen Zeng, Zeng Miao, Weiwei 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 State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

In the power IoT, in order to make up for the shortcomings of insufficient computing capabilities of edge-side devices, cloud-side collaboration technology has attracted more and more attention. The cloud-side collaboration technology relies on the selection of task migration strategies. However, when the existing migration strategies face the complex edge-side terminal devices in the power IoT, the energy consumption and delay performance are not good enough, which greatly affects the user's power experience. Therefore, it is very valuable to study a cloud-side collaborative task migration strategy under the power IoT environment. This paper proposes a task migration strategy based on simulated annealing-Bee Colony Algorithm in the environment of power IoT, which can solve the problem of task migration. Experimental results show that compared with the existing popular methods, this method has advantages in terms of energy consumption and time delay. This research can meet the real-time requirements of the power IoT, while reducing energy consumption and improving the user's power experience, thereby promoting the further development of the power IoT. © 2022 IEEE.

关键词： Simulated annealing

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Multivariate time series forecast in industrial process based on XGBoost and GRU 9

Multivariate time series forecast in industrial process base...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Zhai, Naiju Yao, Peifu Zhou, Xiaofeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation 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 China Copper Co.LTD Kunming China

In this paper, a time series prediction model that merges eXtreme Gradient Boosting (XGBoost) and Gate Recurrent Unit (GRU), XGB-GRU model, is proposed for multivariate time series prediction in industry. The XGB-GRU model uses XGBoost's strong feature extraction capabilities to extract the hidden information of multiple control variables in industrial data. Next, the model uses GRU's unique gating unit to extract the timing information in the industrial data. Finally, the importance of XGBoost output variables to guide actual production and solve the problem of inexplicability of neural networks. Predicting the temperature of the heating furnace verifies that the proposed XGB-GRU is better than a single XGBoost and GRU model. And the model has a good fit to the predicted value. © 2020 IEEE.

关键词： Time series

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