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Cyber-physical-social System in intelligent Transportation

IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 320-333页

作者： Gang Xiong Fenghua Zhu Xiwei Liu Xisong Dong Wuling Huang Songhang Chen Kai Zhao the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science the Cloud Computing Center Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center for Intelligent Systems and Technology Institute of AutomationChinese Academy of Science

A cyber-physical system (CPS) is composed of a physical system and its corresponding cyber systems that are tightly fused at all scales and levels. CPS is helpful to improve the controllability, efficiency and reliability of a physical system, such as vehicle collision avoidance and zero-net energy buildings systems. It has become a hot R&D and practical area from US to EU and other countries. In fact, most of physical systems and their cyber systems are designed, built and used by human beings in the social and natural environments. So, social systems must be of the same importance as their CPSs. The indivisible cyber, physical and social parts constitute the cyber-physical-social system (CPSS), a typical complex system and it's a challengeable problem to control and manage it under traditional theories and methods. An artificial systems, computational experiments and parallel execution (ACP) methodology is introduced based on which data-driven models are applied to social system. Artificial systems, i.e., cyber systems, are applied for the equivalent description of physical-social system (PSS). Computational experiments are applied for control plan validation. And parallel execution finally realizes the stepwise control and management of CPSS. Finally, a CPSS-based intelligent transportation system (ITS) is discussed as a case study, and its architecture, three parts, and application are described in detail. © 2014 Chinese Association of Automation.

关键词： Amphibious vehicles complex networks Embedded systems intelligent systems Transportation

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Iterative search with emulating nodes' local movement on range-free sensor network localization 34

Iterative search with emulating nodes' local movement on ran...

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第三十四届中国控制会议

作者： QIAO Dapeng GUO Zongben MA Hongwei SHI Shuguang School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Aerospace Control Devices

ISBN: (纸本)9781467374439

This paper proposes an iterative evolutionary algorithm with emulating nodes' local movement for searching the best localization accuracy in range-free scenario. All localization methods face a trade-off between the solution quality and computation cost. When sensor network localization in range-free scenario is considered as a constraint satisfaction problem, localization will reach the highest accuracy but with huge computation complexity. To solve the constraint satisfaction, some characteristics that only exist in range-free localization problem are utilized as heuristics in the search of nodes' positions. They are summarized as simple and complex movement to emulate nodes' local movement, and proved to be effective to find a suitable searching direction and jump out of local-minimums existing in the localization. Those emulations are then included in each iteration of a two-objective evolutionary algorithm minimizing the number of node-pairs with violated connectivity, as well as the value quantitating how worse of the violations. Simulation results show that the proposed algorithm can greatly decrease the reach high-accurate positions within limited iterations.

关键词： Wireless sensor network,Localization,Local movement,Evolutionary algorithm,Non-convex,Connectivity

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Design and dynamic analysis for Amoeba-like robot's turning-mechanism applied with spring and damp system

Design and dynamic analysis for Amoeba-like robot's turning-...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Xiang Dong HengHui Sun Zeng Fu Wang Long Cheng Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui CN The State Key Lab. of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781509033652

A new turning-mechanism for Amoeba-like Robot was proposed in this paper, which based on the amoeba-like robot kinematics characteristics of tail contracting and skin flipping. First, one kind of variable-speed node composed of the spring and damp was designed. Because of the existing of the variable-speed nodes, the velocities of the two strip-skins depended not only on the velocities of threads that gone through the variable-speed nodes, but also on the spring and damp it contained. So, although the velocities of threads that induced the velocities of the strip-skins were the same, the velocities of the strip-skins still can be different since the variable-speed nodes existed. That difference in velocities made the turning movement possible. Second, the dynamic model for the turning movement of the Amoeba-like Robot was established and analyzed. The analysis results included the angular velocity and angle curve related to time, which were computed with the dynamic model when shortening speed of thread's length was constant. The results achieved in this paper provided an important basic for the research on the behaviors and control strategy of amoeba-like robot. The new turning-mechanism can be popularized to the tracked mobile robot, for it provided a new and available turning method.

关键词： Conferences Robots Mechatronics

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ACP-based social computing and parallel intelligence： Societies 5.0 and beyond

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CAAI Transactions on Intelligence Technology 2016年第4期1卷 377-393页

作者： XiaoWang Lingxi Li Yong Yuan Peijun Ye Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Qingduo Academy of Intelligent Industries Qingduo 266100 China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN 46202 USA

Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of ＂social laboratories＂ in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.

关键词： Social computing Societies 5.0 Parallel intelligence Knowledge automation Cyber-physical-social system Artificial societies Computational ex-periments Parallel execution

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Exploring Optimal Frequency Caps in Real Time Bidding Advertising

Exploring Optimal Frequency Caps in Real Time Bidding Advert...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Rui Qin Yong Yuan Fei-Yue Wang Beijing Engineering Research Center of Intelligent Systems and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781509039371

Benefited from the high-speed development of Internet and the popularization of big data technology, Real Time Bidding (RTB) emerged and developed quickly, and has become one of the most important and popular model for online computational advertising. In the pay-per-impression based RTB advertising, frequency capping is undoubtedly one of the most crucial issues faced by advertisers and Demand Side Platforms (DSPs), since there are generally vast amount of ad requests in RTB markets, among which many may be triggered by the same target audience. As such, choosing the optimal frequency cap considering all the advertisers becomes a critical issue faced by DSPs. Considering that displaying one advertisement multiple number of times to the same user will diminish the advertising effect, we introduce the concept of discount factor and establish an optimization model of frequency capping to seek for the optimal frequency cap for each advertiser. We also design some experiments to validate our proposed model by utilizing the computational experiment approach, and the experimental results show that the optimal frequency cap can be influenced by the values of the discount factors, and higher value of the discount factor can deduce the advertising effect of larger frequency cap. Moreover, when the discount factors of the advertisers take different values, there also exists an optimal frequency cap, at which the advertisers can get the expected maximum revenue in the long run.

关键词： Advertising Digital signal processing Computational modeling Big data Time-frequency analysis Radio spectrum management Real-time systems

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Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems

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Chinese Physics B 2015年第9期24卷 147-152页

作者：魏庆来宋睿卓孙秋野肖文栋 The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and TechnologyBeijing School of Information Science and Engineering Northeastern University

This paper estimates an off-policy integral reinforcement learning（IRL） algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman（HJB） equation, an off-policy IRL algorithm is *** is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method.

关键词： adaptive dynamic programming approximate dynamic programming chaotic system optimal tracking control

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Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study

Optimizing Market Segmentation Granularity in RTB Advertisin...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

ISBN: (纸本)9781509039371

Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline, 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs' market segmentation decisions.

关键词： Digital signal processing Computational modeling Advertising Numerical models Big data complex systems Automation

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An overview of recent progress in high-order nonholonomic chained system control and distributed coordination

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Journal of control and Decision 2015年第1期2卷 64-85页

作者： Jie Huang Jie Chen Hao Fang Lihua Dou School of Automation Beijing Institute of TechnologyBeijingChina State Key Laboratory of Intelligent Control and Decision of Complex Systems BeijingChina Fujian Institute of Education FuzhouChina

This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,*** important definitions,lemmas,theorems and dynamics are *** the consensus and formation control problems for networked nonholonomic chained systems are ***,some open questions are proposed.

关键词： distributed coordination multi-agent system nonholonomic system chained system high-order

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Neural learning enhanced teleoperation control of robots with uncertainties

Neural learning enhanced teleoperation control of robots wit...

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Conference on Human System Interactions, HSI

作者： Chenguang Yang Junshen Chen Long Cheng Zienkiewicz Centre for Computational Engineering SA1 8EN UK State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509017300

For most teleoperation tasks, it is desired that the telerobot manipulator follows timely and precisely the reference motion set at the master side. However, the conventional control approach may not guarantee the desired performance when there are dynamic uncertainties, especially when there is a notable variation of the telerobot's payload. In this paper, a neural learning based compensation mechanism has been exploited to overcome the effect of the unknown payload as well as uncertainties associated with the telerobot model and the environment. Guaranteed transient performance has been theoretically established. The deterministic learning technique has been employed, such that the neural learned knowledge can be efficiently reused. We performed comparative experiments and demonstrate the effectiveness of the proposed design techniques.

关键词： Payloads Manipulator dynamics Uncertainty Artificial neural networks Trajectory

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Robust H∞ control for a class of liner neutral delay systems

Robust H∞ control for a class of liner neutral delay system...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Xinlan Guo Hongxia Zhao Mechanical and Electrical Engineering Department Nanjing Communications Institute of Technology The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Huawei Nanjing Institute

This paper design controller for the uncertain neutral delay system. The uncertain neutral delay system includes norm bounded uncertain system parameters and unknown constant delay. The paper uses uncertain neutral systems with structural features, and constructs appropriate Lyapunov function to obtain feedback control law. Compared with the previous methods for solving the Riccati equation, this method overcomes the shortcoming of Riccati equation emphasizing the center solution. Simulation results show that, the conservatism of the controller designed in this paper is reduced, and the controller easy to operate and application.

关键词： Robust H∞ control neutral system uncertain time delay feedback control

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