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Communications in Computer and Information Science 2014年 462卷 397-406页

作者： Zang, Qiang Zhou, Ying Mei, Ping Zheng, Baichao Zhang, Kaifeng School of Information and Control Engineering Nanjing University of Information Science & Technology Nanjing210044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China College of Automation Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783662452608

Components of power systems essentially belong to a special class of nonlinear differential-algebraic equations subsystem, whose index is one and interconnection is locally measurable. In this paper, the decentralized control problem is discussed using inverse systems method for such class of power systems components. Firstly, the definition of α -order integral right inverse system is presented. Secondly, a recursive algorithm is proposed to judge whether the controlled component is invertible. Then a physically feasible α -order integral right inverse system is constructed with which the controlled component is made linearization and decoupled, so that linear control theory and methods can be applied. Finally, a decentralized excitation controller is designed for one synchronous generator within multi-machine power systems based on the proposed method in this *** simulation results demonstrate the effectiveness of the proposed control scheme. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Decentralized control

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Derong Liu [People in control]

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IEEE control systems 2014年第2期34卷 26-27页

作者： Liu, Derong State Key Laboratory of Management and Control for Complex Systems Department of Electrical and Computer Engineering University of Illinois at Chicago United States Institute of Automation Chinese Academy of Sciences 95 Zhongguancun East Road Beijing100190 China

关键词： Laboratories

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A new stochastic budget distribution model with random demands 18

A new stochastic budget distribution model with random deman...

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18th Pacific Asia Conference on Information systems, PACIS 2014

作者： Qin, Rui Yuan, Yong Li, Juanjuan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China

In search auctions, when the total budget for an advertising campaign during a certain promotion period is determined, advertisers have to distribute their budgets over a series of sequential temporal slots (e.g., daily budgets). However, due to the uncertainties existed in search markets, advertisers can only obtain the value range of budget demand for each temporal slot based on promotion logs. In this paper, we present a stochastic model for budget distribution over a series of sequential temporal slots during a promotion period, considering the budget demand for each temporal slot as a random variable. We study some properties and present feasible solution algorithms for our budget model, in the case that the budget demand is characterized either by uniform random variable or normal random variable. We also conduct some experiments to evaluate our model with the empirical data. Experimental results show that the budget demand is more likely to be normal distributed than uniform distributed, and our strategy can outperform the baseline strategy commonly used in practice.

关键词： Marketing

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High-level spatial modeling in convolutional neural network with application to pedestrian detection

High-level spatial modeling in convolutional neural network ...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Feng Liu Yongzhen Huang Wankou Yang Changyin Sun School of Automation. Southeast University Nanjing China Key Lab of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Child Development and Learning Science of Ministry of Education. Southeast University Nanjing China

ISBN: (纸本)9781479958306

Convolutional neural network (CNN) has achieved great success in many vision tasks. A key to this success is its ability to powerful automatically learns both high-level and low-level features. In general, low-level features have a small size of receptive fields and appear multiple times in different locations of objects, while high-level semantic features have a relatively large size of receptive fields and only appear once in a specific location of objects. However, traditional CNN treats these two kinds of features in the same manner, i.e., learning them by the convolution operation, which can be approximately considered as cumulating the probabilities that a feature appears in different locations. This strategy is reasonable for low-level features but not for high-level semantic ones, especially in the case of pedestrian detection, where a local feature can be shared by different locations but a semantic part, e.g., a head, only appears once for a human. To jointly model the spatial structure and appearance of high-level semantic features, we propose a new module to learn spatially weighted max pooling in CNN. The proposed method is evaluated on several pedestrian detection databases and the experimental results show that it achieves much better performance than traditional CNN.

关键词： Convolution Semantics Kernel Deformable models Computational modeling Feature extraction Training

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Synchronization of unicycle robots with proximity communication networks 19

Synchronization of unicycle robots with proximity communicat...

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

作者： Liu, Zhixin Wang, Jinhuan Hu, Xiaoming Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Sciences Hebei University of Technology Tianjin300401 China Optimization and Systems Theory KTH Royal Institute of Technology Stockholm10044 Sweden

ISBN: (纸本)9783902823625

In this paper synchronization of both the orientation and velocity for a group of unicycle robots is studied. It is assumed that a robot can only detect and obtain information from those robots that lie in the proximity (within certain distance). A minimum dwell time is imposed on the updating of neighborhood relation in the controller in order to avoid introducing chattering in the closed-loop system that may be caused by abrupt changes of the relation, which as a consequence implies that the neighbor information will be updated only at discrete time instants in the control. In the paper a distributed feedback control law is designed for each agent, and a sufficient condition for uniformly and independently distributed initial states is provided for reaching the synchronization, which depends on the neighborhood radius, the maximum initial translational velocity and the dwell time. © IFAC.

关键词： Sampled data control systems

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Cooperative adaptive fuzzy control of high-order nonlinear multi-agent systems with unknown dynamics 19

Cooperative adaptive fuzzy control of high-order nonlinear m...

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

作者： Huang, Jie Fang, Hao Chen, Jie Dou, Lihua Deng, Fang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China Fujian Institute of Education Fuzhou350025 China

ISBN: (纸本)9783902823625

This paper focuses on the cooperative adaptive fuzzy control of high-order nonlinear multi-agent systems. The communication network is a undirected graph with a fixed topology. Each agent is modeled by a high-order integrator incorporating with unknown nonlinear dynamics and an unknown disturbance. Under the backstepping framework, a robust adaptive fuzzy controller is designed for each agent such that all agents ultimately achieve consensus. Moreover, these controllers are distributed in the sense that the controller design for each agent only requires relative state information between itself and its neighbors. A four-order simulation example demonstrates the effectiveness of the algorithm. © IFAC.

关键词： Multi agent systems

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Distributed adaptive tracking on Lagrangian systems with reduced interaction 11

Distributed adaptive tracking on Lagrangian systems with red...

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2014 11th World Congress on Intelligent control and Automation, WCICA 2014

作者： Liu, Yuchen Fang, Hao Mao, Yutian School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781479958252

In this paper, we propose a distributed adaptive approach for tracking problem without using leader's velocity information, where agents are modeled by Euler-Lagrange equations. It is assumed that only a small fraction of agents within the leader's communication range are informed about the position of the leader. Without using the leader's velocity information, a connectivity-preserving adaptive controller is proposed to achieve tracking control on Lagrangian systems with the leader of constant velocity. Moreover, position and velocity consensus can be achieved asymptotically with the proposed control strategy. Numerical simulations are further provided to illustrate the theoretical results. © 2014 IEEE.

关键词： Adaptive control systems

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Decentralized flocking of multi-robot systems with connectivity maintenance

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Kongzhi Lilun Yu Yingyong/control Theory and Applications 2014年第10期31卷 1393-1403页

作者： Mao, Yu-Tian Chen, Jie Fang, Hao Dou, Li-Hua Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

Connectivity maintenance of flocking is vital for stability and fast state convergence of the entire multirobot system. To this end, the problem of flocking of multiple nonholonomic wheeled mobile robots with connectivity maintenance on directed communication graphs is investigated, provided that the initial network is strongly connected but not balanced. First, a new class of smooth and bounded artificial potential fields is developed to satisfy the requirements of connectivity maintenance, collision avoidance and distance stabilization, simultaneously. Furthermore, by combining potentialbased gradient control techniques and the consensus seeking control schemes, we propose a set of smooth and bounded control protocols for leaderless flocking or flocking with local leader-follower with connectivity maintenance. Those control protocols not only avoids the chattering and saturation caused by the discontinuous/nonsmooth and unbounded flocking algorithms, but also extend the traditional connectivity-preserving flocking algorithms for both the individual motion model and the network topology types. Finally, nontrivial simulations and experiments are performed to validate the effectiveness of the proposed smooth and bounded control strategies. ©, 2014, South China University of Technology. All right reserved.

关键词： Multipurpose robots

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Global decentralized stabilization for a class of large-scale feedforward nonlinear systems

Global decentralized stabilization for a class of large-scal...

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American control Conference

作者： Qixun Lan Chuanlin Zhang Shihua Li Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 P. R. China College of Automation Engineering Shanghai University of Electric Power Shanghai 200090 P.R. China School of Automation Southeast University Nanjing 210096 P. R. China

ISBN: (纸本)9781479917730

This paper considers the problem of global decentralized stabilization for a class of large-scale feedforward nonlinear systems. First, by using generalized homogeneous systems theory, a local linear decentralized control law is recursively constructed. Second, a series of nested saturation functions are integrated with the proposed local linear control law to render the whole closed-loop large-scale system global asymptotical stability. Due to the flexibility of the generalized homogeneous systems theory, the proposed approach not only weakens the existing restrictions imposed on the interconnected nonlinearities, but also can be applied to more general classes of large-scale feedforward nonlinear systems. Numerical example shows that the effectiveness of the proposed control scheme.

关键词： Decentralized control Feedforward neural networks Nonlinear systems Closed loop systems Lyapunov methods Asymptotic stability Feedforward systems

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A freeway travel time predicting method based on IoV

A freeway travel time predicting method based on IoV

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Daxin Tian Chao Liu Yunpeng Wang Guohui Zhang Haiying Xia Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems & Safety Control Beihang University Beijing China Ministry of Public Security of China Key Lab of Urban ITS Technology Optimization and Integration Hefei China Academy of Armored Forces Engineering School of Information Engineering Beijing China Research Institute of Highway Ministry Transport Beijing China

ISBN: (纸本)9781509003679

Real-time travel time is one of the important value for traffic management and traffic control. With the help of Internet of Vehicles (IOV), the dynamic traffic information can be collected and distributed more correctly. In this paper, we propose a method to predict the remaining travel time (RTT) for a vehicle on the freeway in the IOV environment. The Markov chains are adopted to predict a vehicle's remaining travel time in real-time. The experimental results prove that the mean absolute percent error (MAPE) is less than 10%.

关键词： Vehicles Traffic control Intelligent vehicles Markov processes Computational modeling Cloud computing

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