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Iterative Learning control with Unknown control Direction: A Novel Data-Based Approach

IEEE TRANSACTIONS ON NEURAL NETWORKS 2011年第12期22卷 2237-2249页

作者： Shen, Dong Hou, Zhongsheng Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Engn Res Ctr Intelligent Syst & Technol Beijing 100190 Peoples R China Beijing Jiaotong Univ Adv Control Syst Lab Sch Elect & Informat Engn Beijing 100044 Peoples R China

Iterative learning control (ILC) is considered for both deterministic and stochastic systems with unknown control direction. To deal with the unknown control direction, a novel switching mechanism, based only on available system tracking error data, is first proposed. Then two ILC algorithms combined with the novel switching mechanism are designed for both deterministic and stochastic systems. It is proved that the ILC algorithms would switch to the right control direction and stick to it after a finite number of cycles. Moreover, the input sequence converges to the desired one under the deterministic case. The input sequence converges to the optimal one with probability 1 under stochastic case and the resulting tracking error tends to its minimal value.

关键词： Data-based control discrete-time systems iterative learning control unknown control direction

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Neural-Learning-Based Telerobot control With Guaranteed Performance

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IEEE TRANSACTIONS ON CYBERNETICS 2017年第10期47卷 3148-3159页

作者： Yang, Chenguang Wang, Xinyu Cheng, Long Ma, Hongbin Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA1 8EN W Glam Wales Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Beijing Inst Technol State Key Lab Intelligent Control & Decis Complex Beijing 100081 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In this paper, a neural networks (NNs) enhanced telerobot control system is designed and tested on a Baxter robot. Guaranteed performance of the telerobot control system is achieved at both kinematic and dynamic levels. At kinematic level, automatic collision avoidance is achieved by the control design at the kinematic level exploiting the joint space redundancy, thus the human operator would be able to only concentrate on motion of robot's end-effector without concern on possible collision. A posture restoration scheme is also integrated based on a simulated parallel system to enable the manipulator restore back to the natural posture in the absence of obstacles. At dynamic level, adaptive control using radial basis function NNs is developed to compensate for the effect caused by the internal and external uncertainties, e.g., unknown payload. Both the steady state and the transient performance are guaranteed to satisfy a prescribed performance requirement. Comparative experiments have been performed to test the effectiveness and to demonstrate the guaranteed performance of the proposed methods.

关键词： Collision avoidance guaranteed performance neural networks (NNs) telerobot control

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A Scholar of Dignity:Remembering Peter Luh

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1895-1897页

作者： Fei-Yue Wang Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100190China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

It was a shock and disbelief to learn of Peter's death last *** me,he was so fit in his figure,so healthy in his lifestyle,so mild and mindful in his social behavior,and so devout in his religious belief,......,I ... 详细信息

关键词： religious Scholar belief

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Budget planning for coupled campaigns in search auctions

Budget planning for coupled campaigns in search auctions

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22nd Workshop on Information Technologies and systems, WITS 2012

作者： Yang, Yanwu Qin, Rui Zhang, Jie Li, Xin Zeng, Daniel State Key Lab of Intelligent Control and Management of Complex Systems Inst. of Automation CAS Beijing China Department of Information Systems City University of Hong Kong Kowloon Tong Hong Kong Department of Management Information Systems University of Arizona United States

Budget-related decisions in search auctions are recognized as a structured decision problem, rather than a simple constraint. Budget planning over several coupled campaigns remains a challenging but utterly important task in search advertisements. In this paper, we propose a multi-campaign budget plan- ning approach using optimal control techniques, with consideration of the substitute relationship between advertising campaigns. A measure of coupled relationships between campaigns is presented, e.g., the over- lapping degree (O) in terms of campaign contents, promotional periods and target regions. We also discuss some desirable properties of our model and possible solutions. Furthermore, computational experiments are conducted to evaluate our model and identified properties, with real-world data collected from logs and reports of practical campaigns. Experimental results show that, (a) coupled campaigns with higher over- lapping degrees can reduce the optimal budget level and the optimal revenue, and also arrive the budgeting cap earlier;(b) The advertising effort could be seriously weakened when ignoring the overlapping degree between campaigns.

关键词： Budget control

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Co-evolution-based mechanism design for sponsored search advertising

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ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2012年第6期11卷 537-547页

作者： Yuan, Yong Zeng, Daniel Univ Arizona Dept Management Informat Syst Tucson AZ 85721 USA Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing Peoples R China Beijing Engn Res Ctr Intelligent Syst & Technol Beijing Peoples R China

Sponsored search advertising (SSA), the primary revenue source of Web search engine companies, has become the dominant form of online advertising. Search engine companies, such as Google and Baidu, are naturally interested in SSA mechanism design with the aim to improve the overall effectiveness and profitability of SSA ecosystems. Due to model intractability, however, traditional game theory and mechanism design frameworks provide only limited help as to the design and evaluation of practical SSA mechanisms. In this paper, we propose a niche-based co-evolutionary simulation approach, aiming at computationally evaluating SSA auction mechanisms based on advertisers' equilibrium bidding behavior generated through co-evolution of their bidding strategies. Using this approach, we evaluate and compare key performance measures of several practical SSA auction mechanisms, including the generalized first and second price auction, the Vickrey-Clarke-Groves mechanism, and a novel hybrid mechanism adopted by ***, a major search engine in China. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Sponsored search advertising Mechanism design Co-evolutionary simulation Niche-based evolution

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Stealthy FDI Attacks Against Networked control systems Using Two Filters With an Arbitrary Gain

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IEEE TRANSACTIONS ON CIRCUITS AND systems II-EXPRESS BRIEFS 2022年第7期69卷 3219-3223页

作者： Guo, Haibin Sun, Jian Pang, Zhong-Hua Beijing Inst Technol Sch Automat State Key Lab Intelligent Control & Decis Complex Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401120 Peoples R China North China Univ Technol Key Lab Fieldbus Technol & Automat Beijing Beijing 100144 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

This brief investigates a stealthy false data injection (FDI) attack scheme against two communication channels to damage the performance of a networked control system. Compared with most existing works, a more practical and reasonable assumption that an attacker only needs to know the physical system knowledge is considered. By using two filters with an arbitrary gain that can be different from the filter gain of the system, a novel feedback channel attack scheme is proposed to ensure the attack process is stealthy, and the forward channel attack signal can be flexibly designed according to specific attack purposes. It is proved that the proposed attack scheme can render the closed-loop system unstable while bypassing a residual-based detector. Two cases of simulation results are provided to verify the theoretical analysis results.

关键词： Detectors Information filters Networked control systems Communication channels Circuits and systems Automation Sun Kalman filter networked control systems residual-based detector stealthy FDI attacks

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A closed-loop method to generate fast C-start for a robotic fish

A closed-loop method to generate fast C-start for a robotic ...

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2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011

作者： Su, Zongshuai Yu, Junzhi Tan, Min Zhang, Jianwei State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Informatics University of Hamburg Germany

ISBN: (纸本)9781424481149

This paper presents a novel closed-loop method for a multilink robotic fish to mimic the C-start maneuver, in which the turning speed and precision are emphasized. The turning speed is maximized by carefully designed preparatory stage, and the turning precision is achieved by the feedback of the turning angle from a gyroscope and a new design of the propulsive stage. Different types of C-starts are studied, due to the different sizes of caudal fins, in order to achieve the highest turning angular velocity. All the proposed types of C-starts are experimented and compared using a four-joint robotic fish. The experimental results show a fastest angular velocity up to 200°/s and the distinctions between all these different types. © 2011 IEEE.

关键词： Fish

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Optimal budget allocation across search advertising markets

Optimal budget allocation across search advertising markets

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21st Workshop on Information Technologies and systems, WITS 2011

作者： Yang, Yanwu Zhang, Jie Liu, Baiyu Zeng, Daniel State Key Lab. of Intelligent Control and Management of Complex Systems Chinese Academy of Sciences Beijing 100190 China School of Mathematics and Physics University of Science and Technology Beijing China Department of Management Information Systems University of Arizona United States

How to rationally allocate the limited advertising budget is a critical issue in search auctions. However, due to the heterogeneousness of major search markets in terms of auction mechanisms, ranking algorithms and advertising structures, it is becoming increasingly difficult for an advertiser to manipulate advertising budget simultaneously across several search markets. In this paper, we establish a novel optimal budget allocation model across search advertising markets, under a finite time horizon. By considering distinctive features of search auctions, we introduce the quality score q and the dynamic advertising effort u to extend the advertising response function to fit budget decision scenarios. We also provide a feasible solution to our model and study some desirable properties: (a) the marginal return is non-increasing with respect to the advertising budget;(b) the optimal budget solution satisfies the condition that the advertising effort u is positively proportional to the product of the change of accumulated revenue in a market ∂V, the change of market share ∂ θ and the advertising elasticity α. Computational experiments are made to evaluate our model and identified properties. Experimental results show that the advertiser with increasing advertising elasticity is suggested to invest more budget in the late stages, but the advertiser with decreasing advertising elasticity should invest more budget in the initial stage, in order to maximize net profits.

关键词： Marketing

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Weakly Paired Multimodal Fusion for Object Recognition

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2018年第2期15卷 784-795页

作者： Liu, Huaping Wu, Yupei Sun, Fuchun Fang, Bin Guo, Di Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Tsinghua Natl Lab Informat Sci & Technol State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

The ever-growing development of sensor technology has led to the use of multimodal sensors to develop robotics and automation systems. It is therefore highly expected to develop methodologies capable of integrating information from multimodal sensors with the goal of improving the performance of surveillance, diagnosis, prediction, and so on. However, real multimodal data often suffer from significant weak-pairing characteristics, i.e., the full pairing between data samples may not be known, while pairing of a group of samples from one modality to a group of samples in another modality is known. In this paper, we establish a novel projective dictionary learning framework for weakly paired multimodal data fusion. By introducing a latent pairing matrix, we realize the simultaneous dictionary learning and the pairing matrix estimation, and therefore improve the fusion effect. In addition, the kernelized version and the optimization algorithms are also addressed. Extensive experimental validations on some existing data sets are performed to show the advantages of the proposed method. Note to Practitioners-In many industrial environments, we usually use multiple heterogeneous sensors, which provide multimodal information. Such multimodal data usually lead to two technical challenges. First, different sensors may provide different patterns of data. Second, the full-pairing information between modalities may not be known. In this paper, we develop a unified model to tackle such problems. This model is based on a projective dictionary learning method, which efficiently produces the representation vector for the original data by an explicit form. In addition, the latent pairing relation between samples can be learned automatically and be used to improve the classification performance. Such a method can be flexibly used for multimodal fusion with full-pairing, partial-pairing and weak-pairing cases.

关键词： intelligent robot system manipulation and grasping multimodal data projective dictionary learning weakly paired data

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A hierarchical framework for ad inventory allocation in programmatic advertising markets

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ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2018年 31卷 40-51页

作者： Li, Juanjuan Ni, Xiaochun Yuan, Yong Wang, Fei-Yue Beijing Inst Technol Sch Automat Beijing Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Qingdao Peoples R China

Enabled by the big data driven user profiling and precision bidding techniques, online programmatic advertising markets have evolved from the traditional website-buying or ad-slot-buying models to a fine-grained and realtime trading model at the level of ad impressions (i.e., ad inventory). As a result, Web publishers are now facing a challenging decision of allocating the ad inventory across multiple advertising models, which has a direct and important influence on both their individual revenues, and the market-wide supply-demand balance. In this paper, we propose a novel hierarchical ad inventory allocation framework (AIAF), taking into consideration the possible scenarios of ad inventory allocation in programmatic advertising markets. AIAF explicitly captures the specific features of ad inventory allocation in each of three levels (i.e., channel level, market level and platform level), and also their influence-feedback effects. We present the general solution process for solving this model on the basis of its property analysis. An illustrative instantiation of our AIAF model is formulated to demonstrate its applications in supporting publishers' decision-making on the ad inventory allocation. We also conduct experiments based on empirical data so as to validate the model and analysis. Our research findings indicate that 1) our AIAF model outperforms other single-level and two-level allocation strategies;2) the fine-grained optimization is superior to that of the coarse-grained level;3) allocation decisions should be made on the basis of the comparative marginal revenue instead of the absolute marginal revenue.

关键词： Programmatic advertising Ad inventory Real-time bidding Private marketplace Header bidding

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