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On Infinite Time Performance of Nonlinear Model Predictive Controllers

IFAC Proceedings Volumes 2014年第3期47卷 1916-1921页

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 P. R. China School of Electronics Electrical Engineering and Computer Science The Queen's University Belfast Belfast BT7 1NN UK

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

关键词： Model Predictive Control Finite Horizon Optimal Control Value Iteration Principle of Optimality

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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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TIFAflow: Enhancing Traffic Archiving System with Flow Granularity for Forensic Analysis in Network Security

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Tsinghua science and Technology 2013年第4期18卷 406-417页

作者： Zhen Chen Linyun Ruan Junwei Cao Yifan Yu Xin Jiang Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Automation Research Institute of Information Technology and Tsinghua Nationa Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Computer Science of Purdue University Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Computer Science and Technology Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList)Tsinghua University

The archiving of Internet traffic is an essential function for retrospective network event analysis and forensic computer communication. The state-of-the-art approach for network monitoring and analysis involves storage and analysis of network flow statistic. However, this approach loses much valuable information within the Internet traffic. With the advancement of commodity hardware, in particular the volume of storage devices and the speed of interconnect technologies used in network adapter cards and multi-core processors, it is now possible to capture 10 Gbps and beyond real-time network traffic using a commodity computer, such as n2disk. Also with the advancement of distributed file system （such as Hadoop, ZFS, etc.） and open cloud computing platform （such as OpenStack, CloudStack, and Eucalyptus, etc.）, it is practical to store such large volume of traffic data and fully in-depth analyse the inside communication within an acceptable latency. In this paper, based on well- known TimeMachine, we present TIFAflow, the design and implementation of a novel system for archiving and querying network flows. Firstly, we enhance the traffic archiving system named TImemachine＋FAstbit （TIFA） with flow granularity, i.e., supply the system with flow table and flow module. Secondly, based on real network traces, we conduct performance comparison experiments of TIFAflow with other implementations such as common database solution, TimeMachine and TIFA system. Finally, based on comparison results, we demonstrate that TIFAflow has a higher performance improvement in storing and querying performance than TimeMachine and TIFA, both in time and space metrics.

关键词： network security traffic archival forensic analysis phishing attack bitmap database hadoop distributed file system cloud computing NoSQL

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Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM Vehicular Networks

Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM ...

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17th International IEEE Conference on Intelligent Transportation Systems & The Asia-Pacific Council on Systems engineering Conference 2014

作者： Shuangshuang Han Liuqing Yang Xiang Cheng Shichao Chen Fenghua Zhu Zhongdong Yu Haitao Xie Qingdao Academy of Intelligent Industries State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Electronics Engineering and Computer Science Peking University Guang Zhou Communication Information Construction Investment and Operation Co.Ltd.

Multiple-Input Multiple-Output- Orthogonal Frequency Division Multiplexing(MIMO-OFDM) is adopted to vehicular networks to increase the capacity,reliability and *** this paper,iterative demodulation and decoding algorithms are studied to approach the capacity of MIMOOFDM vehicular *** analysing the drawbacks of the Gaussian approximation on the interference cancellation,NonGaussian approximation is proposed to enhance the performance of interference cancellation based detectors with large *** results demonstrate that the proposed non-Gaussian algorithm can achieve a significant performance gain over existing ones with high order constellations.

关键词： Gaussian Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM Vehicular Networks

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A novel feature extracting method for dynamic gesture recognition based on support vector machine

A novel feature extracting method for dynamic gesture recogn...

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International Conference on Information and automation (ICIA)

作者： Yuanrong Xu Qianqian Wang Xiao Bai Yen-Lun Chen Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences University of Science and Technology of China Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

In this paper, we propose a method based on the SVM algorithm to recognize dynamic hand gestures. The information of motion trajectory is captured by a leap motion in three-dimension space. A new methodology of feature extracting is proposed to guarantee the length of samples being the same. The elements of feature vectors are ranged according to two different criteria: one is the amplitude of the variation of orientation angles, and the other criterion is the order of the appearance of features. Experimental results show that this method can classify the dynamic hand gestures effectively.

关键词： Vectors Trajectory Feature extraction Equations Mathematical model Hidden Markov models automation

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TST: Threshold Based Similarity Transitivity Method in Collaborative Filtering with Cloud Computing

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Tsinghua science and Technology 2013年第3期18卷 318-327页

作者： Feng Xie Zhen Chen Hongfeng Xu Xiwei Feng Qi Hou Department of Automation Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Computer Science and Technologies and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University

Collaborative filtering solves information overload problem by presenting personalized content to individual users based on their interests, which has been extensively applied in real-world recommender systems. As a class of simple but efficient collaborative filtering method, similarity based approaches make predictions by finding users with similar taste or items that have been similarly chosen. However, as the number of users or items grows rapidly, the traditional approach is suffering from the data sparsity problem. Inaccurate similarities derived from the sparse user-item associations would generate the inaccurate neighborhood for each user or item. Consequently, its poor recommendation drives us to propose a Threshold based Similarity Transitivity （TST） method in this paper. TST firstly filters out those inaccurate similarities by setting an intersection threshold and then replaces them with the transitivity similarity. Besides, the TST method is designed to be scalable with MapReduce framework based on cloud computing platform. We evaluate our algorithm on the public data set MovieLens and a real-world data set from AppChina （an Android application market） with several well-known metrics including precision, recall, coverage, and popularity. The experimental results demonstrate that TST copes well with the tradeoff between quality and quantity of similarity by setting an appropriate threshold. Moreover, we can experimentally find the optimal threshold which will be smaller as the data set becomes sparser. The experimental results also show that TST significantly outperforms the traditional approach even when the data becomes sparser.

关键词： cloud computing recommender systems big data collaborative filtering data mining similarity transitivity machine learning mapReduce android applications

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Robust fault tolerant control on distributed networked control systems with quantized states

Robust fault tolerant control on distributed networked contr...

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World Congress on Intelligent Control and automation (WCICA)

作者： Yang Ge Jingcheng Wang Yi Zhang Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China Shanghai Urban-Rural Construction and Transportation Development Research Institute Shanghai China Electrical Engineering and Computer Science Queen's University Belfast Belfast UK

The distributed networked control systems are considered in this paper. Several sub-systems which are connected with each other through a communication network make up the whole system. Each sub-system has its own quantizer so that any information which needs be transmitted to other sub-systems will be quantized due to limited bandwidth. Meanwhile, the actuator faults, including outage, loss of effectiveness and stuck are also considered in our research. A mode-based state feedback controller is given in this paper to stable such NCSs and to meet the robust H-inf performance. A simulation example is proposed to illustrate the effectiveness of our method finally.

关键词： Quantization (signal) Networked control systems State feedback Closed loop systems Communication networks Actuators Fault tolerance

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Decision Strategies for Automated Visual Collision Avoidance

Decision Strategies for Automated Visual Collision Avoidance

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International Conference on Unmanned Aircraft Systems

作者： Aaron Mcfadyen Adrien Durand-Petiteville Luis Mejias Australian Research Centre for Aerospace Automation (ARCAA) School of Electrical Engineering and Computer Science Queensland University of Technology (QUT) CyPhy Laboratory School of Electrical Engineering and Computer Science Queensland University of Technology (QUT)

ISBN: (纸本)9781479923779

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

关键词： Collision avoidance spiral motion Avoidance Behavior Air regulation Cost functions Aircraft trajectory Visualization

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Dynamic hand gesture early recognition based on Hidden Semi-Markov Models

Dynamic hand gesture early recognition based on Hidden Semi-...

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IEEE International Conference on Robotics and Biomimetics

作者： Qianqian Wang Yuanrong Xu Yen-Lun Chen Yong Wang Xinyu Wu University of Science and Technology of China Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong. Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

ISBN: (纸本)9781479973989

Real-time performance can be greatly improved, if the early recognition is implemented. In this paper, a dynamic hand gesture early recognition system is proposed. The system can recognize the gesture before it is completed. Our method is based on the Hidden Semi-Markov Models. Three-dimensional information of the gesture trajectory collected by leapmotion is the main data we used. Experiments on the dataset which we established demonstrate the effectiveness of our method.

关键词： Hidden Markov models Gesture recognition Training Conferences Trajectory Arrays

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A fast market competition approach to power system unit commitment using expert systems

Communications in Computer and Information Science

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Communications in computer and Information science 2013年 355卷 442-450页

作者： Xu, Lijun Li, Kang Fei, Minrui Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai University Shanghai China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast University Road Belfast BT9 5AH United Kingdom

This paper proposes a novel two-layer hierarchical market competition algorithm (THMCA) combined with expert system for the unit commitment(UC) problem in power systems. Two hierarchical population individuals are defined in the algorithm, namely the holding companies and the subsidiary companies which altogether form conglomerates. Market competitions among these conglomerates lead to the convergence to a monopoly at the end, resulting in an optimal solution of the above problem. In the meanwhile, expert system is used to produce several expert rules for heavy constraints handling not only in the pre-scheduling process and in the THMCA process as well, ensuring that the positions of all companies are feasible and near-optimal solutions to the UC problem. The algorithm is shown to have a fast execution speed for UC application and the comparison simulation results on a power system with up to 100 generating units have demonstrated the effectiveness on cost reduction of the proposed method. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Cost reduction

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