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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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Decentralized Coordinated control of Hybrid Wind-thermal Power system

Decentralized Coordinated Control of Hybrid Wind-thermal Pow...

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第三十三届中国控制会议

作者： Li Xiao ming Niu Yu guang Wang Shi lin Zhao Zi ang Lin Zhong wei School of Control and Computer Engineering North China Electric Power University State Key Laboratory for Alternate Electric Power System with Renewable Energy Source North China Electric Power University

ISBN: (纸本)9781479947249

Modern power system is a hybrid power system, which contains renewable power plants. In those power plants, wind farm has shown the world's fastest rate of growth. The reported researches about decentralized coordinated control of power system are all based on synchronous generator(SG). It is not suitable that applying this decentralized-coordinated method to a hybrid power system for that the wind-generated energy capacity has been reached a considerable level. Combining correlative measurement modeling and multiple model predictive control, this paper proposes a decentralized coordinated multiple model predictive control(DCM-MPC) for a hybrid wind-thermal power(HWP) system. The transient problems of wind power integration are discussed subsequently. A simple, generic HWP system is used to illustrate the contributions. The results show that the proposed DCM-MPC not only provides an accurate tracking performance, but also improves transient stability of the HWP.

关键词： doubly fed induction generator,synchronous generator,excitation control,decentralized-coordinated control,correlative measured method,transient stability,system damping

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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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On mobilizing processes of Cyber Movement Organizations 19

On mobilizing processes of Cyber Movement Organizations

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Wang, Tao Liu, Zhong Cui, Kainan Zhang, Jie Wang, Fei-Yue Philip Chen, C.L. College of Information System and Management National University of Defense Technology Changsha410073 China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China Department of Computer and Information Science Science and Technology University of Macau China

ISBN: (纸本)9783902823625

Cyber Movement Organization (CMO) is a special kind of social movement organization on the Web. In this paper, we propose a model to simulate the mobilizing process of CMO, which consists of the individual unit, organization unit, and the mobilizing mechanisms. The mobilizing mechanisms has three sub-mechanisms: the participation mechanism, the choice mechanism, and the inviting mechanism. A dataset of more than two million "human flesh search" related microblogs is used to validate the model. Empirical results show that our model can capture the key features of the real-world mobilizing process. © IFAC.

关键词： Automation

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On stability analysis and synthesis of reset control systems with output uncertainties

On stability analysis and synthesis of reset control systems...

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第三十三届中国控制会议

作者： Guanglei Zhao Jingcheng Wang Kang Li Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Electronics Electrical Engineering and Computer ScienceQueens University BelfastUK

ISBN: (纸本)9781479947249

This paper considers reset control systems with output *** present sufficient conditions for the quadratic stability and finite L2 gain ***,the results are extended to piecewise quadratic stability which is much less ***,an iterative algorithm is proposed to design the reset *** the obtained results are given as linear matrix inequalities(LMIs) that can be solved *** examples are given to illustrate the results.

关键词： reset control output uncertainties quadratic stability iterative algorithm

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Real-coded genetic algorithm with oriented evolution towards promising region for parameter optimization

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computer Modelling and New Technologies 2014年第12期18卷 93-101页

作者： Chen, Zhiqiang Yun, Jiang Chen, Xudong School of Computer Science and Information Engineering 125 Chongqing Technology and Business University Chongqing China Chongqing Engineering Laboratory for Detection Control and Integrated System 19 Xuefu Avenue Nan'an Chongqing China

In this paper, a novel real-coded genetic algorithm is presented to generate offspring towards a promising polygon field with k+1 vertex, which represents a set of promising points in the entire population at a particular generation. A set of 19 test problems available in the global parameter optimization literature is used to test the performance of the proposed real-coded genetic algorithms. Several performance comparisons with five significant real-coded genetic algorithms, three state-of-the-art differential evolution algorithms and three others significant evolutionary computing techniques are performed. The comparative study shows the proposed approach is statistically significantly better than or at least comparable to twelve significant evolutionary computing techniques over a test suite of 19 benchmark functions.

关键词： Genetic algorithms

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Distributed MPC for Tracking based on Reference Trajectories

Distributed MPC for Tracking based on Reference Trajectories

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第三十三届中国控制会议

作者： Langwen Zhang Jingcheng Wang Zhengfeng Liu Kang Li Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast

ISBN: (纸本)9781479947249

In this paper, we consider the control of large-scale processes with both input and state couplings. A distributed model predictive control(MPC) strategy for tracking based on the reference trajectories is presented. The proposed distributed MPC strategy requires decomposing a large-scale system into several smaller ones and solving convex optimization problems independently. Distributed MPC tracking strategies for unconstrained and constrained processes are presented, respectively. An iterative algorithm is presented to coordinate the distributed MPC controllers. The proposed algorithm is applied to a four-tank process to demonstrate the effectiveness.

关键词： distributed MPC tracking iterative algorithm reference trajectories

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