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An Improved-WM Method Based on Optimization of Centers of Output Fuzzy Subsets for Fuzzy Rules

IFAC-PapersOnLine 2017年第1期50卷 7369-7374页

作者： Jin Y. Cao W. Wu M. She J. Yuan Y. School of Automation China University of Geosciences Wuhan 430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan

The generation of fuzzy rules from samples is significant for fuzzy modelling. To improve the robustness of Wang-Mendel (WM) method, an improved WM method to extract fuzzy rules from all the regularized sample data was proposed. However, the accuracy of the model with this method is degraded for the conflicting rules with small difference between support degrees. And the output subsets can only be chosen from the pre-defined ones. To solve these problems, we develop an improved-WM method based on optimization of centers of output fuzzy subsets for fuzzy rules (COiWM). This method adopts the fuzzy c-means (FCM) clustering algorithm to divide the input and output spaces, and the improved WM method which replaces the original data by regularized data is used to calculate the support degrees. Then the support degrees are used as weights to optimize the centers of output fuzzy subsets with a method of weighted averages, so as to enhance the accuracy of a fuzzy model. Experimental results of a case study on short term daily maximum electric load forecasting prove that our proposed method enhances the accuracy of a fuzzy model. © 2017

关键词： Accuracy Conflicting rules Fuzzy c-means clustering algorithm Fuzzy rules Wang-Mendel method

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Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control

arXiv

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arXiv 2018年

作者： Li, Wenqing Zhao, Chunhui Huang, Biao State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G-2V4 Canada

For large-scale industrial processes under closed-loop control, process dynamics directly resulting from control action are typical characteristics and may show different behaviors between real faults and normal changes of operating conditions. However, conventional distributed monitoring approaches do not consider the closed-loop control mechanism and only explore static characteristics, which thus are incapable of distinguishing between real process faults and nominal changes of operating conditions, leading to unnecessary alarms. In this regard, this paper proposes a distributed monitoring method for closed-loop industrial processes by concurrently exploring static and dynamic characteristics. First, the large-scale closed-loop process is decomposed into several subsystems by developing a sparse slow feature analysis (SSFA) algorithm which capture changes of both static and dynamic information. Second, distributed models are developed to separately capture static and dynamic characteristics from the local and global aspects. Based on the distributed monitoring system, a two-level monitoring strategy is proposed to check different influences on process characteristics resulting from changes of the operating conditions and control action, and thus the two changes can be well distinguished from each other. Case studies are conducted based on both benchmark data and real industrial process data to illustrate the effectiveness of the proposed method. Copyright © 2018, The Authors. All rights reserved.

关键词： Process monitoring

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A Novel Deep Learning Approach: Stacked Evolutionary Auto-encoder

A Novel Deep Learning Approach: Stacked Evolutionary Auto-en...

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International Joint Conference on Neural Networks

作者： Yaoming Cai Zhihua Cai Meng Zeng Xiaobo Liu Jia Wu Guangjun Wang School of Computer Science China University of Geosciences Wuhan China Qinzhou University Guangxi China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Computing Macquarie University Sydney NSW Australia

Deep neural networks have been successfully applied to many data mining problems in recent works. The training of deep neural networks relies heavily upon gradient descent methods, however, which may lead to the failure of training due to the vanishing gradient (or exploding gradient) and local optima problems. In this paper, we present SEvoAE method based on using Evolutionary Multiobjective Optimization (EMO) algorithm to train single layer auto-encoder, and sequentially learning deeper representation in a stacking way. SEvoAE is able to achieve accurate feature representation with good sparseness by globally simultaneously optimizing two conflicting objective functions and allows users to flexibly design objective functions and evolutionary optimizers. We compare results of the proposed method with existing architectures for seven classification problems, showing that the proposed method is able to outperform existing methods with a reduced risk of overfitting the training data.

关键词： Training Optimization Decoding Neural networks Linear programming Feature extraction Stacking

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Estimation of image Jacobian Matrix with time-delay compensation based on Kalman filtering with colored noise 5

Estimation of image Jacobian Matrix with time-delay compensa...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Wang, Xinmei Liu, Zhenzhu Wei, Wu Liu, Feng School of Automation China University of Geosciences Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China College of Automation Science and Engineering South China University of Technology Guangzhou Guangdong510640 China

In order to compensate for the impact of time delay on the estimation of object feature point image and image Jacobian matrix and improve the control precision of image-based visual servo system, a Kalman filtering algorithm with colored noise is proposed to obtained the current motion state estimation of the feature point with time-delay compensation in the image space, then the accurate image Jacobian matrix under time delay can be obtained. For the above, the following work will be done in this paper: (1) the current motion state estimation of the feature point in the image space is predicted by Kalman filtering algorithm, combined with practical applications, measurement noise is usually as colored noise and can be regarded as a one-order Markov sequence excited by Gauss white noise, then a Kalman filtering recursive model can be derived according to the variance minimization principle of the estimation error;(2) to obtain the measurement vectors estimation which cannot be acquired in the Kalman filtering model owing to the existence of time delay, the relationship between the motion state of the feature point at the prior and later point is established, and a polynomial is fitted by using some of the observed data under the relationship to realize the measurement vectors estimation in the time-delay period. Thus the estimation of the motion state of the feature point at the current time in the image space can be obtained, and the estimation of image Jacobian matrix with time-delay compensation can be obtained. Experimental results validate the feasibility and superiority of this method.

关键词： Time delay

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A Novel Forwarding Method for Full-Duplex Two-Way Relay Networks

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China Communications 2017年第4期14卷 65-72页

作者： Shuangshuang Han Xiang Cheng Liuqing Yang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing China and Qingdao Academy of Intelligent Industries The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Department of Electrical and Computer Engineering Colorado State University

An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal from two terminal nodes by a minimum mean squared error(MMSE) estimation and forwards a scaled version of the MMSE estimate to the destination. The proposed EF outperforms conventional amplify-and-forward(AF) and decode-and-forward(DF) across all signal-to-noise ratio(SNR) region. Because its computational complexity is high for relays with a large number of antennas(large MIMO) and/or high order constellations, an approximate EF scheme, called list EF, are thus proposed to reduce the computational complexity. The proposed list EF computes a candidate list for the MMSE estimate by using a sphere decoder, and it approaches the performance of the exact EF relay at a negligible performance loss. The proposed forwarding approach also could be used to other relay networks, such as half-duplex, one-way or massive MIMO relay networks.

关键词： estimate-and-forward full-duplex two-way relay wireless communications

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A maximum power point tracking controller for thermoelectric generators 36

A maximum power point tracking controller for thermoelectric...

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第36届中国控制会议

作者： Wei Xie Guangyue Huang Xiao Zhang Fang Deng School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems China ZhenHua Oil Co

ISBN: (纸本)9781538629185

Thermoelectric generators（TEGs） directly convert heat energy into electricity for power-supplying sensors and other portable electronic *** this paper,a maximum power point tracking（MPPT） controller in the modified perturb and observe（P＆O） algorithm was designed on the basis of analyzing the output characteristics of the TEG *** MPPT controller consists of a voltage sensor,a current sensor,a microcontroller and a SEPIC converter,which keeps the operating point of the thermoelectric generator tracking the maximum power point（MPP）.The thermoelectric generator was heated to generate electricity,and a supercapacitor accumulated that *** results using the MPPT controller present that the thermoelectric generator’s output voltage achieves around 5V,the output power achieves upward of 2W when the temperature difference △T=75℃,and the operating point of the thermoelectric generator accurately tracks the MPP with a tracking efficiency of 99.8%;the charging power can be improved 89.65%.

关键词： Thermoelectric generators（TEGs） Modified P＆O algorithm Maximum power point tracking（MPPT） SEPIC converter

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A 3D Display Parallel System: Light Field Re-rendering and Depth Sense Optimization

A 3D Display Parallel System: Light Field Re-rendering and D...

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International Conference on Display Technology, ICDT 2018

作者： Pei, Renjing Ma, Kui Wang, Feiyue State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences East Zhongguanchun Road No. 95 Haidian District Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Parallel Optics Technology Innovation Center Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781510867659

The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye’s visual mechanism, unartful 3D scene structure design, or bad viewing condition always emerges poor depth perception experience or even physiological discomfort during the watching time, which is often sub-optimal for mass high-quality 3D display productions. To solve this problem, we propose a novel 3D display parallel system for depth sense optimization and it empirically guides how the light field should be re-rendered. Structurally, the parallel system consists of an artificial perception measurement system, a display evaluation model and a light field display rendering system, which includes the display calibration, scene capture, light field data processing and display. Particularly, the system can systematically analyze and model various factors affecting the depth sense which learned through the measurement system, like scene structure, objects’ speeds in 3D video and so on. And those sense factors can be personally modified or increased according to the viewer’s demands or technical improvement. Moreover, the light field could be real-time re-rendered, based on some image processing technology, optical flow analysis and object segmentation (or tracking) (especially the one-shot video segmentation). Theory and algorithms are developed and experimental validation results show a superior performance. © 2018 SID.

关键词： Three dimensional displays

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Network Resilience

arXiv

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arXiv 2020年

作者： Liu, Xueming Li, Daqing Ma, Manqing Szymanski, Boleslaw K. Eugene Stanley, H. Gao, Jianxi Key Laboratory of Image Information Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China School of Reliability and Systems Engineering Beihang University Beijing100191 China College of Safety Science and Engineering Civil Aviation University of China Tianjin 300300 China Department of Computer Science Rensselaer Polytechnic Institute TroyNY12180 United States Network Science and Technology Center Rensselaer Polytechnic Institute TroyNY12180 United States Center for Polymer Studies Department of Physics Boston University BostonMA02215 United States

Many systems on our planet shift abruptly and irreversibly from the desired state to an undesired state when forced across a "tipping point". Some examples are mass extinctions within ecosystems, cascading failures in infrastructure systems, and changes in human and animal social networks. The ability to avoid such regime shifts or to recover quickly from such a non-resilient state demonstrates a system's resilience;system resilience is a quality that enables a system to adjust its activities to retain its basic functionality when errors and failures occur. In the past 50 years, attention has been paid almost exclusively to low-dimensional systems;scholars have focused on the calibration of the resilience functions of such systems and the identification of indicators of early warning signals based on two to three connected components. In recent years, taking advantage of network theory and the availability of lavish real datasets, network scientists have begun to explore real-world complex networked multidimensional systems, as well as their resilience functions and early warning indicators. This report presents a comprehensive review of resilience functions and regime shifts in complex systems in domains such as ecology, biology, society, and infrastructure. The research approach includes empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also review the definitions of some ambiguous terms, including robustness, resilience, and stability. Copyright © 2020, The Authors. All rights reserved.

关键词： complex networks

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An Overview of Smart Contract: Architecture, Applications, and Future Trends

An Overview of Smart Contract: Architecture, Applications, a...

引用

2018 IEEE intelligent Vehicles Symposium, IV 2018

作者： Wang, Shuai Yuan, Yong Wang, Xiao Li, Juanjuan Qin, Rui Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Qingdao Academy of Intelligent Industries Qingdao266109 China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781538644522

With the rapid development of cryptocurrency and its underlying blockchain technologies, platforms such as Ethereum and Hyperledger began to support various types of smart contracts. Smart contracts are computer protocols intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract. Smart contracts have broad range of applications, such as financial services, prediction markets and Internet of Things (IoT), etc. However, there are still many challenges such as security issues and privacy disclosure that await future research. In this paper, we present a comprehensive overview on blockchain powered smart contracts. First, we give a systematic introduction for smart contracts, including the basic framework, operating mechanisms, platforms and programming languages. Second, application scenarios and existing challenges are discussed. Finally, we describe the recent advances of smart contract and present its future development trends, e.g., parallel blockchain. This paper is aimed at providing helpful guidance and reference for future research efforts. © 2018 IEEE.

关键词： Smart contract

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Stability of linear systems with sawtooth input delay and predictor-based controller

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Automatica 2020年 117卷

作者： Haoyuan Sun Jian Sun Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 PR China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 PR China School of Electronic and Information Engineering Tongji University Shanghai 200082 PR China

In this paper, the stability of linear systems with sawtooth input delay widely existing in networked systems and predictor-based controller is considered. Under the assumption that there exists an instant where the input delay is zero, a necessary and sufficient condition is obtained to guarantee the exponential stability of the closed-loop system, that is, the closed-loop system is stable if and only if the matrix A + B K is Hurwitz. Two simulation examples are given to confirm the validity of the obtained results.

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