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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Seppo Sierla Marcin Hurkala Konstantinia Charitoudi Chen-Wei Yang Valeriy Vyatkin Dept. of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Faculty of Computing Engineering and Science (FCES) University of South Wales Pontypridd RCT UK Department of Computer Science Electrical and Space Engineering Lulea University of Technology Lulea Sweden

ISBN: (纸本)9781479924004

The reliability theory used in the design of complex systems including electric grids assumes random component failures and is thus unsuited to analyzing security risks due to attackers that intentionally damage several components of the system. In this paper, a security risk analysis methodology is proposed consisting of vulnerability analysis and impact analysis. Vulnerability analysis is a method developed by security engineers to identify the attacks that are relevant for the system under study, and in this paper, the analysis is applied on the communications network topology of the electric grid automation system. Impact analysis is then performed through co-simulation of automation and the electric grid to assess the potential damage from the attacks. This paper makes an extensive review of vulnerability and impact analysis methods and relevant system modeling techniques from the fields of security and industrial automation engineering, with a focus on smart grid automation, and then applies and combines approaches to obtain a security risk analysis methodology. The methodology is demonstrated with a case study of fault location, isolation and supply restoration smart grid automation.

关键词： IEC standards Security Smart grids automation Substations Software Fault location

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Choosing characteristics of hardware-software systems for word intelligibility of speech scoring

Choosing characteristics of hardware-software systems for wo...

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8th International Forum on Strategic Technology, IFOST 2013

作者： Ivanov, Andrey Valerievich Trushin, Victor Aleksandrovich Novosibirsk State Technical University Faculty of Automation and Computer Engineering Russia

ISBN: (纸本)9781479909315

The article is about hardware and software systems, dedicated for word intelligibility of speech scoring. Following characteristics for procedure and equipment for word intelligibility of speech scoring are reviewed: width of frequency range, which is analyzed, its' frequency partition (bandpass filter choice), measured values' dynamic range, measurements' accuracy. Experiment was performed in order to determine the frequency range width required for analysis. According to experiment results optimal width of frequency range, required for correct discrete word intelligibility valuing, was chosen. Frequency range partitioning was researched. Partitioning is suggested to be rendered correspondingly to human acoustic organ sensitivity. Requirements of choice measuring equipment are suggested. Structural configuration of software and hardware systems are given, including alternative ADC mountings, uses of logarithmic preamp, analogue or software bandpass filter. © 2013 IEEE.

关键词： Bandpass filters

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A Framework for the Nonlinear Control of Dual-Stage Systems

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IFAC Proceedings Volumes 2014年第3期47卷 1140-1145页

作者： Aurélio T. Salton Jeferson V. Flores João M. Gomes da Silva Jinchuan Zheng Zhiyong Chen Group of Automation and Control Systems (GACS) Pontifícia Universidade Católica do Rio Grande do Sul Brazil Department of Electrical Engineering Universidade Federal do Rio Grande do Sul Brazil Faculty of Engineering and Industrial Sciences Swinburne University of Technology Australia School of Electrical Engineering and Computer Science The University of Newcastle Australia

This paper presents a framework for the nonlinear control of dual-stage actuators (DSA). Motivated by various nonlinear controllers that make use of sector bounded and £ ∞ nonlinearities for the control of saturated linear systems, a methodology for integrating such nonlinear functions in order to improve the performance of DSA is presented. The stability of the closed-loop system is assessed by casting the nonlinearities in a mixed sector-bounded plus quasi-Linear Parameter Varying (LPV) framework, leading to a set of linear matrix inequalities (LMIs) to be satisfied by the controller parameters. Taking advantage of the developed framework, a new £ ∞ function is proposed to avoid the saturation of the secondary actuator. Simulation results illustrate the validity of the proposed framework and its potential for the performance improvement of DSA.

关键词： DSA Nonlinear Feedback Time-Optimal Performance Macro-Micro Manipulator

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The research of context-aware conflict based on SPA

The research of context-aware conflict based on SPA

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International Conference on Cyberspace Technology (CCT 2014)

作者： Duo Lin Matturdi Bardi Lai Xiaoyang Liu Zengli Chen Xi Zhou Xianwei School of Computer and Communication Engineering University of Science and Technology Beijing (USTB) 100083 China School of mathematics and information Hotan Teachers College Hetian 848000 Xinjiang China Faculty of Information Engineering and Automation Kunming University of Science and Technology 650500 China

Context-aware plays a key role in the wisdom network information processing. Due to limited resources, context conflict is inevitable in context-aware. User satisfaction is a good reflection for the wisdom degree of the network. In this paper, through considering the user satisfaction, we propose a novel context-aware conflict solution model based on SPA(set pair Analysis). The model obtain the best server mode by the maximum satisfaction connection degree to solve the conflict in context-aware. The simulation analysis show that the proposed method is simple, effective and can solve many users compete for the same scene of conflict.

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Automated Sunspot Detection Using Morphological Reconstruction and Adaptive Region Growing Techniques

Automated Sunspot Detection Using Morphological Reconstructi...

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第三十三届中国控制会议

作者： Lan Yu Linhua Deng Song Feng Department of Information Engineering Yunnan Land and Resources Vocational College National Astronomical Observatories/ Yunnan Astronomical Observatory Chinese Academy of Sciences Yunnan Key Laboratory of Computer Technology Application / Faculty of Information Engineering and Automation Kunming University of Science and Technology

ISBN: (纸本)9781479947249

Sunspots are dark areas with respect to their surrounding area because the temperature of sunspot areas is lower than the average temperature of the solar surface. It provides essential information for many aspects of solar physics. A sunspot is composed of umbra and penumbra. It is a prerequisite for studying solar physics and spatial atmosphere to accurately segment and extract sunspot structures. Consequently, we propose an automated detection technique for segmenting and extracting them. The detection procedure is composed of two steps:(1) segmenting and extracting sunspot umbra with morphological reconstruction;(2) detecting and segmenting sunspot penumbra with region growing. For evaluating the accuracy of the detection procedure,we used a high-resolution observation obtained by Solar Optical Telescope onboard Hinode, and other obtained with the Dutch Open Telescope to illustrate the performance. The results demonstrate that our proposed technique is significant effective and accurate, and is suitable for studying the sunspot evolution and their physical phenomena.

关键词： Automated detection,Sunspot umbrae,Sunspot penumbrae,Morphological reconstruction,Adaptive region growing

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Evaluating dataflow vulnerabilities of scientific workflow based on data dependency patterns

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Journal of Computational Information Systems 2013年第12期9卷 4861-4868页

作者： Fu, Xiaodong Liu, Li Feng, Yong Liu, Xiaoyan Zhang, Jing Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650500 China

If potential contributors leading to system failure can be identified when a scientific workflow is modelled, a lot of system vulnerabilities may thus be revealed and improved. In this paper, we first use data dependency patterns to describe dataflow in a scientific workflow. Then, the state function that describes the causal relations leading to incorrect state of an output is presented. We use a series of fault tree symbols to illustrate the state functions. Thus, fault tree analysis method is used to identify critical elements and elements combinations that lead to the incorrect state of any output item and calculate the probability of the incorrect state based on the probabilities of the basic events in the analysed workflow. Finally, an importance measure is designed to prioritize the contributors of system failure. The feasibility and effectiveness of the proposed methods are proved by example and experiments. © 2013 by Binary Information Press.

关键词： Fault tree analysis

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Stabilization of networked control systems via controller and protocol co-design

Stabilization of networked control systems via controller an...

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International Conference on Mechatronics and Control (ICMC)

作者： Hongbo Song Zhen Hong Department of Computer Sciences Zhejiang University of Finances & Economy Hangzhou China P.R. China Faculty of Mechanical Engineering & Automation Zhejiang Sci-Tech University Hangzhou Zhejiang P.R. China

ISBN: (纸本)9781479925391

This paper studies the stabilization for networked control systems with medium access constraint via controller and protocol co-design. The closed-loop networked control system is modeled as a discrete-time switched system. Sufficient conditions are presented for the exponential stability of the closed-loop networked control system by the average dwell time method. Based on the conditions, stabilizing controllers and the scheduling protocols are designed. Finally a numerical example is employed to demonstrate the effectiveness of the proposed method.

关键词： Protocols Sensors Actuators Networked control systems Stability analysis Switched systems State feedback

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Observer based output feedback tuning for underwater remotely operated vehicle based on linear quadratic performance

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AIP Conference Proceedings 2015年第1期1660卷

作者： Mohd Shahrieel Mohd Aras Shahrum Shah Abdullah Muhammad Nizam Kamarudin Ahmad Fadzli Nizam Abdul Rahman Fadilah Abd Azis Hazriq Izzuan Jaafar Department of Mechatronics Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Department of Electric and Electronics Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia International Campus Jalan Semarak 54100 Kuala Lumpur Malaysia Department of Control and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Faculty of Information Technology and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia

This paper describes the effectiveness of observer-based output feedback for Unmanned Underwater Vehicle (UUV) with Linear Quadratic Regulation (LQR) performance. Tuning of observer parameters is crucial for tracking purpose. Prior to tuning facility, the ranges of observer and LQR parameters are obtained via system output cum error. The validation of this technique using unmanned underwater vehicles called Remotely Operated Vehicle (ROV) modelling helps to improve steady state performance of system response. The ROV modeling is focused for depth control using ROV 1 developed by the Underwater Technology Research Group (UTeRG). The results are showing that this technique improves steady state performances in term of overshoot and settling time of the system response.

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Extreme learning machine for the displacement prediction of landslide under rainfall and reservoir level

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Stochastic Environmental Research and Risk Assessment 2014年第8期28卷 1957-1972页

作者： Cheng Lian Zhigang Zeng Wei Yao Huiming Tang School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan China School of Computer Science South-Central University for Nationalities Wuhan China Faculty of Engineering China University of Geosciences Wuhan China

Landslide prediction is always the emphasis of landslide research. Using global positioning system GPS technologies to monitor the superficial displacements of landslide is a very useful and direct method in landslide evolution analysis. In this paper, an EEMD–ELM model [ensemble empirical mode decomposition (EEMD) based extreme learning machine (ELM) ensemble learning paradigm] is proposed to analysis the monitoring data for landslide displacement prediction. The rainfall data and reservoir level fluctuation data are also integrated into the study. The rainfall series, reservoir level fluctuation series and landslide accumulative displacement series are all decomposed into the residual series and a limited number of intrinsic mode functions with different frequencies from high to low using EEMD technique. A novel neural network technique, ELM, is employed to study the interactions of these sub-series at different frequency affecting landslide occurrence. Each sub-series extracted from accumulative displacement of landslide is forecasted respectively by establishing appropriate ELM model. The final prediction result is obtained by summing up the calculated predictive displacement value of each sub. The EEMD–ELM model shows the best accuracy comparing with basic artificial neural network models through forecasting the displacement of Baishuihe landslide in the Three Gorges reservoir area of China.

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Performance of combined artificial neural networks for forecasting landslide displacement

Performance of combined artificial neural networks for forec...

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International Joint Conference on Neural Networks (IJCNN)

作者： Cheng Lian Zhigang Zeng Wei Yao Huiming Tang School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Hubei China School of Computer Science South-Central University for Nationalities Wuhan China Faculty of Engineering China University of Geo-sciences Wuhan China

An efficient and accurate method for landslide displacement prediction is very important to reduce the casualties and property losses caused by this type of natural hazard. In recent years, many kinds of artificial neural networks (ANNs) have been widely applied to landslide displacement prediction. But we can't know which type of ANN is the best until we have calculated the prediction error. An improper choice of ANN may result in bad prediction results. In this paper, we use a neural networks combination prediction method based on the discounted MSFE (mean squared forecast error) to reduce the risk of selecting the types of ANNs. Four popular ANNs, radial basis function neural network (RBFNN), support vector regression (SVR), least squares support vector machine (LSSVM) and extreme learning machine (ELM), are selected as candidate neural networks. The performance of our model is verified through two case studies in Baishuihe landslide and Bazimen landslide. Experimental results reveal that the combining neural networks can improve the generalization abilities of ANNs.

关键词： Terrain factors Artificial neural networks Monitoring Predictive models Kernel Training

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