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共 546 条记录，以下是341-350 订阅

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Analysis of Two Robust Learning Control Schemes in the Presence of Random Iteration-Varying Noise

Analysis of Two Robust Learning Control Schemes in the Prese...

引用

American Control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper deals with the design problem of robust iterative learning control (ILC), in the presence of noise that is varying randomly from iteration to iteration. Two ILC schemes are considered: one adopts the previous iteration tracking error (PITE) and the other adopts the current iteration tracking error (CITE), in the updating law. For both schemes, the convergence results are obtained by using a frequency-domain approach, and a comparison between them is presented from the viewpoints of the convergence condition, robustness against plant uncertainty, and delay compensation. It shows that sufficient conditions can be derived to bound the tracking error and make its expectation monotonically convergent in the sense of L_(2)-norm, which work effectively with robustness for all admissible plant uncertainties. Furthermore, the sufficient conditions for both schemes can also be formulated in terms of two complementary functions, which do not depend on the delay time as well as the plant uncertainty and, thus, make them convenient to be checked and solved using the frequency-domain tools. Numerical simulations are included to illustrate the effectiveness of the two proposed ILC schemes.

关键词： Iterative learning control monotonic convergence previous iteration tracking error current iteration tracking error random iteration-varying noise delay compensation delay compensation monotone convergence iterative methods Iterative learning control follow error Scheme design problems Delay time Sufficient conditions learning control

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A New Resampling Algorithm for Generic Particle Filters

A New Resampling Algorithm for Generic Particle Filters

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American Control Conference

作者： X. Fu Y. Jia J. Du F. Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper is devoted to the resampling problem of particle filters. We firstly demonstrate the performance of classical Resampling algorithm (also called as systematic resampling algorithm) using a novel metaphor, through which the existing defects of Resampling algorithm is vividly reflected simultaneously. In order to avoid these defects, the exquisite resampling (ER) algorithm is induced which involves some exquisite actions such as comparing the weights by stages and generating the new particles based on quasi-Monte Carlo method. Simulations indicate that the proposed ER algorithm can reduce the sample impoverishment effectively and improve the accuracy of estimation evidently, which confirm that ER algorithm is a competitive alternative to Resampling algorithm.

关键词： resampling algorithm Particle filters

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Non-Fragile Control for Trajectory Tracking of Nonholonomic Mobile Robots

Non-Fragile Control for Trajectory Tracking of Nonholonomic ...

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American Control Conference

作者： Na Ni Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper is devoted to the non-fragile controller design for the trajectory tracking of nonholonomic mobile robots. Using non-linear state feedback and proper coordinate transformation, the model of nonholonomic mobile robots is exactly linearized. Based on which, the non-fragile controller is designed by employing the linear matrix inequality (LMI) approach. Simulation examples are included to illustrate the effectiveness of the proposed controller.

关键词： Trajectory Mobile robots Control systems Tracking Robot kinematics Orbital robotics State feedback Error correction Sliding mode control Laboratories

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Kalman filtering with multiple nonlinear-linear mixing state constraints

Kalman filtering with multiple nonlinear-linear mixing state...

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IEEE Conference on Decision and Control

作者： X. Fu Y. Jia J. Du F. Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Beihang University Beijing CN Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper is devoted to the problem of state estimation for a class of dynamic system with multiple nonlinear-linear (NL) mixing state constraints. A computational algorithm was developed by C. Yang and E. Blasch to incorporate a positive definite quadratic form equality constraint into the Kalman filtering for the ground vehicle tracking. However, when the target tracked in multidimensional space, a single positive definite quadratic form constraint is not enough due to the involvement of other surface such as hyperboloid, paraboloid, or even plane. A analytic method of incorporating multiple nonlinear-linear mixing state constraints into the Kalman filter is presented here, and a sufficient condition is obtained that guarantee the existence of solution. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraints surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a nonlinear-linear mixing spacecraft positioning problem.

关键词： Kalman filters Symmetric matrices State estimation Optimization Covariance matrix Noise

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A heuristic approach for capacity control in clouds

A heuristic approach for capacity control in clouds

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2009 IEEE Conference on Commerce and Enterprise Computing, CEC 2009

作者： Anandasivam, Arun Buschek, Stefan Buyya, Rajkumar Institute for Information Systems and Management University of Karlsruhe Germany Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia

ISBN: (纸本)9780769537559

Cloud resource providers in a market face dynamic and unpredictable consumer behavior. The way, how prices are set in a dynamic environment, can influence the demand behavior of price sensitive customers. A Cloud resource provider has to decide on how to allocate his scarce resources in order to maximize his profit. The application of bid price control for evaluating incoming service requests is a common approach for capacity control in network revenue management. In this paper we introduce a customized version of the concept of self-adjusting bid prices and apply it to the area of Cloud Computing. Furthermore, we perform a simulation in order to test the efficiency of the proposed model. © 2009 IEEE.

关键词： Consumer behavior

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Dependable workflow scheduling in global grids

Dependable workflow scheduling in global grids

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2009 10th IEEE/ACM International Conference on Grid Computing, Grid 2009

作者： Rahman, Mustafizur Ranjan, Rajiv Buyya, Rajkumar Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia Service Oriented Computing Research Group School of Computer Science and Engineering University of New South Wales Australia

ISBN: (纸本)9781424451494

In this paper, a reputation-based Grid workflow scheduling algorithm is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Grid overlays. The proposed approach builds upon structured peer-to-peer indexing and overlay networking techniques to create a scalable wide-area networking of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers (Grid Resource Brokers). The proposed algorithm can dynamically adapt to changing resource conditions and offer significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. We evaluate and demonstrate the feasibility of our approach through an extensive trace driven simulation. The results show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system. © 2009 IEEE.

关键词： Scheduling algorithms

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A distributed heuristic for decentralized workflow scheduling in global grids

A distributed heuristic for decentralized workflow schedulin...

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2009 10th IEEE/ACM International Conference on Grid Computing, Grid 2009

ISBN: (纸本)9781424451494

Efficient scheduling is a key concern for the effectual execution of performance driven Grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized Grid environment. However, in this paper, we present a distributed list heuristic for decentralized scheduling of workflow applications in global Grids. The simulation results show that the proposed scheduling approach is scalable with respect to increased workload on the system. © 2009 IEEE.

关键词： Scheduling

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Scheduling parallel applications on Utility Grids: Time and cost trade-off management

Scheduling parallel applications on Utility Grids: Time and ...

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32nd Australasian computer science Conference, ACSC 2009

作者： Garg, Saurabh Kumar Buyya, Rajkumar Siegel, H.J. Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne VIC 3010 Australia Electrical and Computer Engineering Department Colorado State University Fort Collins United States Computer Science Department Colorado State University Fort Collins United States

ISBN: (纸本)9781920682729

With the growth of Utility Grids and various Grid market infrastructures, the need for efficient and cost effective scheduling algorithms is also increasing rapidly, particularly in the area of meta-scheduling. In these environments,users not only may have conflicting requirements with other users, but also they have to manage the trade-off between time and cost such that their applications can be executed most economically in the minimum time. Thus, choosing of the best Grid resources becomes a challenge in such a competitive market. This paper presents two novel heuristics for scheduling parallel applications on Utility Grids that manage and optimize the trade-off between time and cost constraints. The performance of the heuristics is evaluated through extensive simulations of a real-world environment with real parallel workload models to demonstrate the practicality of our algorithms. We compare our scheduling algorithms against other common algorithms used by current meta-schedulers. The results shows that our algorithms outperform other algorithms by minimizing the time and cost of application execution on Utility Grids. Copyright © 2009, Australian computer Society, Inc.

关键词： Scheduling algorithms

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Offer-based scheduling of deadline-constrained Bag-of-Tasks applications for utility computing systems

Offer-based scheduling of deadline-constrained Bag-of-Tasks ...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Marco A. S. Netto Rajkumar Buyya Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia

Metaschedulers can distribute parts of a bag-of-tasks (BoT) application among various resource providers in order to speed up its execution. When providers cannot disclose private information such as their load and computing power, which are usually heterogeneous, the metascheduler needs to make blind scheduling decisions. We propose three policies for composing resource offers to schedule deadline-constrained BoT applications. Offers act as a mechanism in which resource providers expose their interest in executing an entire BoT or only part of it without revealing their load and total computing power. We also evaluate the amount of information resource providers need to expose to the metascheduler and its impact on the scheduling. Our main findings are: (i) offer-based scheduling produces less delay for jobs that cannot meet deadlines in comparison to scheduling based on load availability (i.e. free time slots); thus it is possible to keep providers' load private when scheduling multi-site BoTs; and (ii) if providers publish their total computing power they can have more local jobs meeting deadlines.

关键词： Processor scheduling computer applications Job shop scheduling Grid computing Cloud computing Application software Information resources Delay Biological system modeling Message passing

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High-Performance Cloud Computing: A View of Scientific Applications

High-Performance Cloud Computing: A View of Scientific Appli...

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International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN)

作者： Christian Vecchiola Suraj Pandey Rajkumar Buyya Cloud computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a service level agreement (SLA), which ensure the desired quality of service (QoS). Aneka, an enterprise cloud computing solution, harnesses the power of compute resources by relying on private and public clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.

关键词： Cloud computing Quality of service Application software Scientific computing Availability Large-scale systems Context-aware services Finance computer applications Gene expression

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