• Title/Summary/Keyword: Adaptive applications

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Optimization of Cancellation Path Model in Filtered-X LMS for Narrow Band Noise Suppression

  • Kim, Hyoun-Suk;Park, Youngjin
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.1
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    • pp.69-74
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    • 1999
  • Adaptive algorithms based on gradient adaptation have been extensively investigated and successfully joined with active noise/vibration control applications. The Filtered-X LMS algorithm became one of the basic feedforward algorithms in such applications, but is not fully understood yet. Effects of cancellation path model on the Filtered-X LMS algorithm have investigated and some useful properties related to stability were discovered. Most of the results stated that the error in the cancellation path model is undesirable to the Filtered X LMS. However, we started convergence analysis of Filtered-X LMS based on the assumption that erroneous model does not always degrade its performance. In this paper, we present a way of optimizing the cancellation path modern in order to enhance the convergence speed by introducing intentional phase error. Carefully designed intentional phase error enhances the convergence speed of the Filtered X LMS algorithm for pure tone noise suppression application without any performance loss at steady state.

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An Overview of Learning Control in Robot Applications

  • Ryu, Yeong-Soon
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1996.10a
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    • pp.6-10
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    • 1996
  • This paper presents an overview of research results obtained by the authors in a series of publications. Methods are developed both for time-varying and time-invariant for linear and nonlinear. for time domain and frequency domain . and for discrete-time and continuous-time systems. Among the topics presented are: 1. Learning control based on integral control concepts applied in the repetition domain. 2. New algorithms that give improved transient response of the indirect adaptive control ideas. 4. Direct model reference learning control. 5 . Learning control based frequency domain. 6. Use of neural networks in learning control. 7. Decentralized learning controllers. These learning algorithms apply to robot control. The decentralized learning control laws are important in such applications becaused of the usual robot decentralized controller structured.

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Modular and versatile platform for the benchmarking of modern actuators for robots

  • Garcia, Elena;Gonzalez-de-Santos, Pablo
    • Smart Structures and Systems
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    • v.11 no.2
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    • pp.135-161
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    • 2013
  • This work presents a test platform for the assessment and benchmarking of modern actuators which have been specifically developed for the new field and service robotics applications. This versatile platform has been designed for the comparative analysis of actuators of dissimilar technology and operating conditions. It combines a modular design to adapt to linear and rotational actuators of different sizes, shapes and functions, as well as those with different load capacities, power and displacement. This test platform emulates the kinematics of robotic joints while an adaptive antagonist-load actuator allows reproducing the variable dynamic loads that actuators used in real robotics applications will be subjected to. A data acquisition system is used for monitoring and analyzing test actuator performance. The test platform combines hardware and software in the loop to allow actuator performance characterization. The use of the proposed test platform is demonstrated through the characterization and benchmarking of three controllable impedance actuators recently being incorporated into modern robotics.

OPTIMIZATION OF ERROR PATH MODEL IN FILTERED-X LMS ALGORITHM FOR NAROW BAND NOISE SUPPRESSION

  • Kim, Hyoun-Suk;Park, Youngjin
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.43-46
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    • 1995
  • Adaptive algorithms based on gradient adaptation have been extensively investigated and successfully jointed with active noise/vibration control applications. The Filtered-X LMS algorithm became one of the basic feedforward algorithms in such applications, but still is not fully understood. The error path model effect on the Filtered-X LMS algorithm has been under the investigation and some useful properties related stability has been discovered. We are interested in utilizing the fact that the model error caused by the way optimizing the error path model in a view point of convergence speed of Filtered-X LMS algorithm for pure tone noise suppression application without any performance loss at steady state.

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Blast Damage Assessment to a Modern Steel Structures

  • Mestreau Eric;Baum Joseph D.;Charman Chuck;Lee Seung;Sohn Young
    • 한국전산유체공학회:학술대회논문집
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    • 2006.05a
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    • pp.292-295
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    • 2006
  • The terrorist attack of September $11^{th}$ 2001 has enforced a new examination of the response of modern steel structures, such as those found in large warehouses, auditoriums and airport terminals, to terrorist bomb attack. The effort described in this paper assesses the potential damage to such a newly designed structure form a medium-size car bomb. The structure is mostly composed of a lightweight complex beam structure with large windows and skylights piercing through a corrugated roof. The structural response to the terrorist attack requires the modelling of various physics phenomena including bomb detonation, blast wave propagation, reflections, and refractions and resulting blast impact on the structure. Hence, a fluid/structure coupled methodology is used to perform the assessment.

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Adaptive Resource Management and Provisioning in the Cloud Computing: A Survey of Definitions, Standards and Research Roadmaps

  • Keshavarzi, Amin;Haghighat, Abolfazl Toroghi;Bohlouli, Mahdi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4280-4300
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    • 2017
  • The fact that cloud computing services have been proposed in recent years, organizations and individuals face with various challenges and problems such as how to migrate applications and software platforms into cloud or how to ensure security of migrated applications. This study reviews the current challenges and open issues in cloud computing, with the focus on autonomic resource management especially in federated clouds. In addition, this study provides recommendations and research roadmaps for scientific activities, as well as potential improvements in federated cloud computing. This survey study covers results achieved through 190 literatures including books, journal and conference papers, industrial reports, forums, and project reports. A solution is proposed for autonomic resource management in the federated clouds, using machine learning and statistical analysis in order to provide better and efficient resource management.

Heterogeneous Resource Management for Adaptive Grid System (적응형 그리드 시스템을 위한 이질적인 자원 관리)

  • Eui-Nam Huh;Woong-Jae Lee;Jong-Sook Lee
    • Journal of the Korea Society for Simulation
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    • v.12 no.4
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    • pp.51-59
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    • 2003
  • Real-Time applications on Grid environment have several problems in terms of resource management addressed as follows; (1) dynamic resource allocation to provide QoS objectives, (2) heterogeneous resources that is different scale, or capacity in same unit, and (3) resource availability, and resource needs. This paper describes the techniques of resource manager (RM) handling above problems to support QoS of dynamic real-time applications on Grid. The contributions of this paper to solve problems are as follows: unification of dynamic resource requirements among heterogeneous hosts, control of resources in heterogeneous environments, and dynamic load balancing/sharing. Our heuristic allocation scheme works not only 257% better than random, 142% better than round robin, and 36.4% better than least load in QoS sensitivity, but also 38.6% better than random, 28.5% better than round robin, and 31.6% better than least load in QoS.

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Optimal shape design of contact systems

  • Mahmoud, F.F.;El-Shafei, A.G.;Al-Saeed, M.M.
    • Structural Engineering and Mechanics
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    • v.24 no.2
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    • pp.155-180
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    • 2006
  • Many applications in mechanical design involve elastic bodies coming into contact under the action of the applied load. The distribution of the contact pressure throughout the contact interface plays an important role in the performance of the contact system. In many applications, it is desirable to minimize the maximum contact pressure or to have an approximately uniform contact pressure distribution. Such requirements can be attained through a proper design of the initial surfaces of the contacting bodies. This problem involves a combination of two disciplines, contact mechanics and shape optimization. Therefore, the objective of the present paper is to develop an integrated procedure capable of evaluating the optimal shape of contacting bodies. The adaptive incremental convex programming method is adopted to solve the contact problem, while the augmented Lagrange multiplier method is used to control the shape optimization procedure. Further, to accommodate the manufacturing requirements, surface parameterization is considered. The proposed procedure is applied to a couple of problems, with different geometry and boundary conditions, to demonstrate the efficiency and versatility of the proposed procedure.

Internet Roundtrip Delay Prediction Using the Maximum Entropy Principle

  • Liu, Peter Xiaoping;Meng, Max Q-H;Gu, Jason
    • Journal of Communications and Networks
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    • v.5 no.1
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    • pp.65-72
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    • 2003
  • Internet roundtrip delay/time (RTT) prediction plays an important role in detecting packet losses in reliable transport protocols for traditional web applications and determining proper transmission rates in many rate-based TCP-friendly protocols for Internet-based real-time applications. The widely adopted autoregressive and moving average (ARMA) model with fixed-parameters is shown to be insufficient for all scenarios due to its intrinsic limitation that it filters out all high-frequency components of RTT dynamics. In this paper, we introduce a novel parameter-varying RTT model for Internet roundtrip time prediction based on the information theory and the maximum entropy principle (MEP). Since the coefficients of the proposed RTT model are updated dynamically, the model is adaptive and it tracks RTT dynamics rapidly. The results of our experiments show that the MEP algorithm works better than the ARMA method in both RTT prediction and RTO estimation.

Enhancing Method to make Cluster for Filtering-based Sensor Networks (여과기법 보안효율을 높이기 위한 센서네트워크 클러스터링 방법)

  • Kim, Byung-Hee;Cho, Tae-Ho
    • 한국정보통신설비학회:학술대회논문집
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    • 2008.08a
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    • pp.141-145
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    • 2008
  • Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

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