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arXiv 2023年

作者： Piao, Jinnan Li, Dong Yu, Xueting Li, Zhibo Yang, Ming Liu, Jindi Zeng, Peng The State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China The Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

In this paper, we first indicate that the block error event of polar codes under successive cancellation list (SCL) decoding is composed of path loss (PL) error event and path selection (PS) error event, where the PL error event is that correct codeword is lost during the SCL decoding and the PS error event is that correct codeword is reserved in the decoded list but not selected as the decoded codeword. Then, we simplify the PL error event by assuming the all-zero codeword is transmitted and derive the probability lower bound via the joint probability density of the log-likelihood ratios of information bits. Meanwhile, the union bound calculated by the minimum weight distribution is used to evaluate the probability of the PS error event. With the performance analysis, we design a greedy bit-swapping (BS) algorithm to construct polar codes by gradually swapping information bit and frozen bit to reduce the performance lower bound of SCL decoding. The simulation results show that the BLER performance of SCL decoding is close to the lower bound in the medium to high signal-to-noise ratio region and we can optimize the lower bound to improve the BLER performance of SCL decoding by the BS algorithm. Copyright © 2023, The Authors. All rights reserved.

关键词： Decoding

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Agent self-assessment: Determining policy quality without execution

Agent self-assessment: Determining policy quality without ex...

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IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Alexander Hans Siegmund Duell Steffen Udluft Neuroinformatics and Cognitive Robotics Laboratory Ilmenau University of Technology Ilmenau Germany Machine Learning Group Berlin Institute of Technology Berlin Germany Intelligent Systems and Control Siemens AG Munich Germany

With the development of data-efficient reinforcement learning (RL) methods, a promising data-driven solution for optimal control of complex technical systems has become available. For the application of RL to a technical system, it is usually required to evaluate a policy before actually applying it to ensure it operates the system safely and within required performance bounds. In benchmark applications one can use the system dynamics directly to measure the policy quality. In real applications, however, this might be too expensive or even impossible. Being unable to evaluate the policy without using the actual system hinders the application of RL to autonomous controllers. As a first step toward agent self-assessment, we deal with discrete MDPs in this paper. We propose to use the value function along with its uncertainty to assess a policy's quality and show that, when dealing with an MDP estimated from observations, the value function itself can be misleading. We address this problem by determining the value function's uncertainty through uncertainty propagation and evaluate the approach using a number of benchmark applications.

关键词： Uncertainty Equations Markov processes Benchmark testing Approximation algorithms Machine learning Histograms

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Distributed Hierarchical Fault Diagnosis Based on Sparse Auto-Encoder and Random Forest 4th

Distributed Hierarchical Fault Diagnosis Based on Sparse Aut...

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4th International Conference on Machine Learning and intelligent Communications, MLICOM 2019

作者： Li, Tong Song, Chunhe Liu, Yang Wang, Zhongfeng Yu, Shimao Su, Shanting Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9783030323875

For the diagnosis of large-scale local devices, the traditional centralized fault diagnosis systems are becoming incompetent to meet the requirement of real-time monitoring. This paper proposes the Distributed hierarchical Fault Diagnosis System (DFDS). Specifically, DFDS implements fault monitoring by an improved Sparse Auto-Encoder (SAE) on the monitor layer, classifies faults and identifies unknown faults by an improved random forest on the classification layer, learns new knowledge and updates the system on the decision layer. We apply DFDS in the laboratory data of Case Western Reserve University to verify the efficiency of the proposed system. The experimental results show that our method can accurately detect the fault and accurately identify the fault type. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Fault detection

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Adaptive visual servoing using common image features with unknown geometric parameters

Adaptive visual servoing using common image features with un...

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作者： Liu, Yun-Hui Wang, Hesheng Chen, Weidong Zhou, Dongxiang Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Hong Kong Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China State Key Laboratory of Robotics Technology and System Harbin Institute of Technology Harbin 150001 China Joint Center for Intelligent Sensing and Systems National University of Defense Technology China

This paper generalizes the concept of the depth-independent interaction matrix, developed for point and line features in our early work, to generalized image features. We derive the conditions under which the depth-independent interaction matrix can be linearly parameterized by the geometric parameters of the generalized image features, and propose an adaptive visual servo controller for robot manipulators using the generalized image features whose geometric parameters are unknown. To estimate the unknown parameters on-line, we propose new error functions that are linear to estimation errors of the parameters and an algorithm that minimizes the error functions using multiple images. The Lyapunov theory is used to prove asymptotic stability of the proposed controller based on the nonlinear dynamics of the manipulator. It is also shown that in addition to points and lines, other common image features like distances, angles, areas, and centroids all satisfy the conditions for the linear parameterization. Experiments have been conducted to validate the proposed control method. © 2013 Elsevier Ltd. All rights reserved.

关键词： controllers

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A Novel Text Personalized Analysis Model Based on BP Neural Network 6th

A Novel Text Personalized Analysis Model Based on BP Neural ...

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6th International Conference on Life System Modeling and Simulation, LSMS 2020, and 6th International Conference on intelligent Computing for Sustainable Energy and Environment, ICSEE 2020

作者： Wang, Zhongfeng Wang, Chu Li, Ligang Pan, Zhudong Zou, Yunfeng 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 DongFang Eleceronics CO. LTD Yantai264001 China State Grid Jiangsu Marketing Service Nanjing210019 China

ISBN: (纸本)9789813363779

In online interactive platform, text analysis has greatly changed people's communication, thinking, and promoted the explosive growth of user-generated information. A large number of texts generated by users have become one of the most representative data sources of big data in recent years. Mining and analyzing user-generated information has become essential part on research of social development. The sentiment analysis on social media text as an information processing technology for analyzing, processing, summarizing and reasoning subjective texts with emotions has received extensive attention in academia and industry in recent years, and has been used among many areas of social media and many applications. The traditional text sentiment analysis research work mainly focuses on analyzing emotions from texts, but ignores the individualized differences of users in emotional expression, thus affecting the quality of analysis results. To solve the problems, this paper is about solving the problem of personalized sentiment analysis of social media texts. Considering the wide application of BP neural network technology in social media was proposed to solve the possible challenges of social media text personalized sentiment analysis. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Research on intrusion detection of industrial control system based on improved QPSO-SVM

Research on intrusion detection of industrial control system...

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2022 International Conference on Electronic Information Technology, EIT 2022

作者： Yu, Yajie Liu, Xianda Wei, Weixuan Chen, Hengfei 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

ISBN: (纸本)9781510655096

Intrusion detection technology can effectively evaluate the security state of the system. However, the accuracy of traditional intrusion detection methods still needs to be improved. Therefore, this paper proposed a SVM model based on improved QPSO. QPSO is used to optimize the hyperparameters of SVM to improve its accuracy. In addition, the shrinkage expansion coefficient in QPSO is improved to make QPSO adaptive. Experiment shows that the proposed algorithm has good performance. © 2022 SPIE. All rights reserved.

关键词： Intrusion detection

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Industrial Wireless Network Access Selection Based on Multilevel Fuzzy Neural Network

Industrial Wireless Network Access Selection Based on Multil...

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Chinese control and Decision Conference, CCDC

作者： Yan Xu Zhijun Gao Sichao Zhang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China 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

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In order to solve the issues in the heterogeneous industrial wireless network access selection such as delay and reliability, this paper present an industrial wireless network access selection based on multilevel fuzzy neural network. The algorithm divides the input attributes into three categories: network attributes, terminal attributes, and environment attributes. It synchronously inputs them into the fuzzy neural network to obtain the candidate network scores, which effectively reduces the number of fuzzy rules and reduces the algorithm complexity. Furthermore, this paper also consider the influence of the industrial environment on network selection and quantitatively reduce the number of switching and blocking rate. The simulation experimental results show that this algorithm is able to achieve fast network access selection in noisy and occluded industrial heterogeneous wireless networks, and the blocking rate can remain low in the presence of dense terminals.

关键词： Wireless networks Neural networks Switches Mean square error methods Interference Fuzzy neural networks Delays

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Development of an anthropomorphic flute robot for the application in science and technology museum

Development of an anthropomorphic flute robot for the applic...

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IEEE International Conference on robotics and Biomimetics

作者： Gao Huang Weimin Zhang Fei Meng Ye Tian Qing Shi Klaus Petersen Atsuo Takanishi Qiang Huang Key Laboratory of Biomimetic Robots and Systems Ministry of Education China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Faculty of Science and Engineering Waseda University Tokyo Japan Key Laboratory of Intelligent Control and Decision of Complex System China

ISBN: (纸本)9781479973989

To resemble the appearance of human beings, humanoid robots should be designed with many DOFs, however, it increases the complexity of the mechanical design and the real-time control, which will make a high cost and have a poor reliability and will not fit for the application in museums or human's daily lives. In this paper, to enable the low cost and high reliability robot to interact with humans naturally and sever humans more friendly, we imported advanced technology of the Waseda's flute robot and retained the most important mechanical parts, such as the lip, lungs and the fingers for the flute playing, on this basis, some other mechanical structures were redesigned; particularly, the robot's appearance was carefully designed; in addition, we also redesigned the hardware structure using our own joint controllers and software system based on CAN bus communication for the cost saving and high reliability. The redesigned robot had just 16 DOFs. Preliminary performance test results showed that this new redesigned robot achieved in producing high quality of flute sound and high sound conversion efficiency, and the period of communication was about 4ms.

关键词： Robot kinematics Robot sensing systems Lungs Joints Legged locomotion control systems

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Dynamical Balance Optimization and control of Quadruped Robots Under Perturbing External Force

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IFAC Proceedings Volumes 2013年第20期46卷 199-205页

作者： Zhijun Li Sijia Yu Sibang Liu Key Laboratory of Autonomous Systems and Networked Control Ministry of Education College of Automation Science and Engineering South China University of Technology Guangzhou China The Robotics Institute and School of Mechanical Engineering University of Electronic Science and Technology of China Chengdu China 610054 The Robotics Institute and Institute of Intelligent Systems and Information Technology University of Electronic Science and Technology of China Chengdu China 610054

This paper investigates the optimal feet forces distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamic model of quadruped robots and derive a reduced order dynamical model of motion/force. Consider an external wrench on quadruped robots, the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to minimize the optimized objective function with linear equality and inequality constraints, and hybrid motion/force control based on adaptive neural network is used to compensate for the external perturbation in the environment and approximate feedforward force and impedance of the leg joints on line. The verification of the proposed control is conducted using the extensive simulations.

关键词： quadruped robot forces distribution external wrench motion/force control

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Multimode Industrial Process Monitoring using Hierarchical Mode Division and Serial Independent Component Analysis

Multimode Industrial Process Monitoring using Hierarchical M...

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第32届中国过程控制会议(CPCC2021)

作者： Shuai Li Xiaofeng Zhou Haibo Shi 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 University of Chinese Academy of Sciences

With the increasing scale and complexity,how to analyze the hybrid characteristics including multimode,nonGaussianity and nonlinearity is one of the most difficult problems faced by multimode industrial process *** paper proposes a monitoring method using hierarchical mode division with serial independent component analysis for multimode processes with *** the multimodal uncertainty and transition mode,hierarchical mode information with transitions is first obtained by mode division using hierarchical density peaks ***,by integrating independent component analysis(ICA) and kernel independent component analysis(KICA) using the serial structure,a hybrid non-Gaussian and nonlinear process modeling method using serial independent component analysis is used for hierarchical process ***,the stable and transition mode identification using geodesic distance is developed for multimode industrial process *** monitoring results for the penicillin fermentation process show the feasibility and effectiveness.

关键词： Process monitoring multimode industrial process transition mode hierarchical mode division serial independent component analysis

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