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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Fucheng Qiu Yi Li College of Computer Science Sichuan University Chengdu Sichuan China National Key Laboratory of Air Traffic Control Automation System Technology Chengdu Sichuan China

ISBN: (纸本)9781479932801

The scientific and accurate forecast of air traffic flow is not only an effective protection to maintain the air traffic flow continued and unimpeded, and also is an important basis for the air traffic flow management(ATFM) to make decisions and development strategies. Based on the character of flow prediction, the prediction method of genetic algorithm to optimize wavelet neural network is proposed. It uses genetic algorithms with the natural evolution laws to conduct the pre-optimized training for the connection weights and stretching translation scales of the wavelet neural network, overcoming the drawbacks of easy to fall into local minima and causing oscillation effect of wavelet neural network with a single gradient descent method. The air flow prediction simulation using the GA-WNN prediction model demonstrates the validity of the model.

关键词： Genetic algorithms Optimization Training Atmospheric modeling Biological neural networks Predictive models

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An Adaptive Predictive control Strategy for RMPPT under Partially Shaded Conditions

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IFAC Proceedings Volumes 2014年第3期47卷 4947-4952页

作者： Chao Ma Jing Wu Ning Li Shaoyuan Li Kang Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in I – P curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.

关键词： Photovoltaic systems RMPPT Partial shading Adaptive predictive control

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A GPU-based Parallel Simulation Platform for Large-scale Wind Farm Integration

A GPU-based Parallel Simulation Platform for Large-scale Win...

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IEEE PES Transmission and Distribution Conference and Exposition

作者： Haixiang Gao Ying Chen Yin Xu Zhitong Yu Laijun Chen State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical Engineering Tsinghua University School of Electrical Engineering and Computer Science Washington State University

ISBN: (纸本)9781479936571

Due to the energy crisis of the next fifty years, an increasing number of large-scale wind farms are integrating into power systems. Parallel simulation platforms are indispensable to evaluate the effects of wind farm integration. A GPU-based parallel simulation platform is constructed in this paper to test the feasibility of simulating integration systems on GPU. By adopting previous research work such as averaged model and improved EMTP algorithm, models and algorithm of the platform are firstly introduced. Then the hardware and software architecture of the platform are put forward, which combine CPU configuration and GPU computing. Finally, a wind farm with different numbers of DFIGs are used to test the performance of the platform. Results show that the platform has excellent accuracy, efficiency and scalability. The work of this paper proves the feasibility to simulate wind farm integrating dynamics adopting GPU and its potential to reach tremendous efficiency and scalability.

关键词： Power system simulation Power system modelling

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A formal model for attack mutation using dynamic description logics 8

A formal model for attack mutation using dynamic description...

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8th IFIP International Conference on Intelligent Information Processing, IIP 2014

作者： Wang, Zhuxiao Guo, Jing Shi, Jin He, Hui Zhang, Ying Peng, Hui Tian, Guanhua School of Control and Computer Engineering State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing100029 China Education Technology Center Beijing International Studies University Beijing100024 China Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783662449790

All currently available Network-based Intrusion Detection systems (NIDS) rely upon passive protocol analysis which is fundamentally flawed as an attack can evade detection by exploiting ambiguities in the traffic stream as seen by the NIDS. We observe that different attack variations can be derived from the original attack using simple transformations. This paper proposes a semantic model for attack mutation based on dynamic description logics (DDL(X)), extensions of description logics (DLs) with a dynamic dimension, and explores the possibility of using DDL(X) as a basis for evasion composition. The attack mutation model describes all the possible transformations and how they can be applied to the original attack to generate a large number of attack variations. Furthermore, this paper presents a heuristics planning algorithm for the automation of evasion composition at the functional level based on DDL(X). Our approach employs classical DL-TBoxes to capture the constraints of the domain, DL-ABoxes to present the attack, and DL-formulas to encode the objective sequence of packets respectively. In such a way, the evasion composition problem is solved by a decidable tableau procedure. The preliminary results certify the potential of the approach. © IFIP International Federation for Information Processing 2014.

关键词： Semantics

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Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

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15th Annual Conference on Advances in Autonomous Robotics systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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Finite-time stability and stabilization of Itô stochastic time-varying systems 33

Finite-time stability and stabilization of Itô stochastic t...

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Proceedings of the 33rd Chinese control Conference, CCC 2014

作者： Yan, Zhiguo Zhang, Weihai Lin, Zhongwei School of Electrical Engineering and Automation Qilu University of Technology Jinan Shandong250353 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao Shandong266590 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789881563842

This paper deals with the finite-time stability and stabilization for continuous-time linear stochastic time-varying systems. Several necessary and sufficient conditions and a sufficient condition for finite-time stability are derived. Moreover, a sufficient condition for the existence of state feedback controller is given. Such results involve the feasibility problems of differential linear matrix inequalities with terminal constraint. © 2014 TCCT, CAA.

关键词： Stochastic systems

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A New Class of Learning Automata for Selecting an Optimal Subset

A New Class of Learning Automata for Selecting an Optimal Su...

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IEEE International Conference on systems, Man, and Cybernetics

作者： JunQi Zhang ZeZhou Li Qi Kang MengChu Zhou Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science and Technology Tongji University Department of Control Science and Engineering Tongji University Department of Electrical and Computer Engineering New Jersy Institute of Technology

ISBN: (纸本)9781479938414

Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of Learning Automata to select only the optimal action out of a set of actions, this paper considers a multiple-action selection problem and proposes a novel class of Learning Automata for selecting an optimal subset of actions. Their objective is to identify the optimal subset: the top k out of r actions. Based on conventional continuous pursuit and discretized pursuit learning schemes, this paper introduces four pursuit learning schemes for selecting the optimal subset, called continuous equal pursuit, discretized equal pursuit, continuous unequal pursuit and discretized unequal pursuit learning schemes, respectively. In conjunction with a reward-inaction learning paradigm, the above four schemes lead to four versions of pursuit Learning Automata for selecting the optimal subset. The simulation results present a quantitative comparison between them.

关键词： Learning Automata Optimal subset Pursuit algorithm

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Semi-global leader-following consensus of multiple linear systems with position and rate-limited actuators: The state feedback case

Semi-global leader-following consensus of multiple linear sy...

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World Congress on Intelligent control and Automation (WCICA)

作者： Zhiyun Zhao Zongli Lin Department of Automation Key Laboratory of System Control and Information Processing Shanghai China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

This paper studies the semi-global leader-following consensus problem for a group of linear systems in the presence of both actuator position and rate saturation. Each follower agent in the group is described by a general linear system subject to simultaneous actuator position and rate saturation. We construct a low gain based linear state feedback control law for each follower agent and show that semi-global leader-following consensus can be achieved by using these control laws when the communication topology among follower agents is a connected undirected graph and the leader is a neighbor of at least one follower. Simulation results illustrate the theoretical results.

关键词： Actuators State feedback Topology Linear systems Multi-agent systems Closed loop systems Vectors

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Team of Bayesian optimization algorithms to solve task assignment problems in heterogeneous computing systems

Team of Bayesian optimization algorithms to solve task assig...

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IEEE International Conference on systems, Man and Cybernetics

作者： Jie Li JunQi Zhang Qi Kang ChangJun Jiang Ministry of Education China Key Laboratory of Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai Department of Control Science and Engineering Tongji University Shanghai China

ISBN: (纸本)9781479938414

A Bayesian optimization algorithm (BOA) belongs to estimation of distribution algorithms (EDAs). It is characterized by combining a Bayesian network and evolutionary algorithms to solve nearly decomposable optimization problems. BOA is less popularly applied to solve high dimensionality complex optimization problems. A key reason is that the cost of training all dimensions by BOA becomes expensive with the increase of problem dimensionality. Since data are relatively sparse in a high dimensional space, even though BOA can train all dimensions simultaneously, the interdependent relations between different dimensions are difficult to learn. Its search ability is thus significantly reduced. In this paper, we propose a team of Bayesian optimization algorithms (TBOA) to search and learn dimensionality. TBOA consists of multiple BOAs, in which each BOA corresponds to a dimension of the solution domain and it is responsible for the search of this dimension's value region. The proposed TBOA is used to solve the real problem of task assignment in heterogeneous computing systems. Extensive experiments demonstrate that the computational cost of the overall training in TBOA is decreased very significantly while keeping high solution accuracy.

关键词： Bayes methods Sociology Statistics Optimization Computational efficiency Joints Probability distribution

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On the Estimation of the Domain of Attraction for Saturated systems via Partitioning of the Input Space

On the Estimation of the Domain of Attraction for Saturated ...

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第三十三届中国控制会议

作者： Yuanlong Li Zongli Lin Department of Automation and Key Laboratory of System Control and Information Processing of the Ministry of EducationShanghai Jiao Tong University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

ISBN: (纸本)9781479947249

This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the remaining regions, there is a unique input that saturates everywhere with the time-derivative of its saturated signal being zero. These special properties of the inputs in different regions of the input space are combined with an existing piecewise quadratic Lyapunov functions that contains the information of input saturation to arrive at a set of less conservative stability conditions, from which a larger level set of the piecewise quadratic Lyapunov function can be obtained as an estimate of the domain of *** results indicate that the proposed approach has the ability to obtain a significantly larger estimate of the domain of attraction than the existing methods.

关键词： Actuator saturation,constrained control,domain of attraction,input saturation,piecewise quadratic Lyapunov functions,stability analysis

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