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A two-stage neural network classifier for condition-based maintenance in wireless sensor networks

International Journal of COMADEM 2010年第2期13卷 17-26页

作者： Ramani, A. McMurrough, C. Middleton, M. Ballal, P. Athamneh, A. Lee, W. Kwan, C. Lewis, F. Automation and Robotics Research Institute University of Texas at Arlington 7300 Jack Newell Blvd. S Fort Worth TX 76118-7115 United States Energy Systems Research Center University of Texas at Arlington 416 S. College St Arlington TX 76019-0048 United States Signal Processing Inc. 13619 Valley Oak Circle Rockville MD 20850-3572 United States Computer Science Engineering University of Texas at Arlington United States Electrical Engineering Department United States

Motor failures in aerospace applications can lead to serious compromises in safety, overall effectiveness, and maintenance costs. In mission critical applications, it is important that motor fault signatures are identified before a failure occurs. It is known that 40% of mechanical failures occur due to bearing faults. Bearing faults can be identified from the motor vibration signatures. Three key contributions are outlined in this paper. First, we develop a low cost test bed for simulating bearing faults in a motor. Second, we develop a wireless sensor module for collection of vibration data from the test bed. Finally, we use a novel two stage neural network to classify various bearing faults using the Generalized Hebbian Algorithm (GHA) in the first stage and a supervised learning vector quantization network (SLVQ) with a self organizing map approach for fault classification in the second stage. © 2010 COMADEM International.

关键词： Wireless sensor networks

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Semi-parametric adaptive control of discrete-time nonlinear systems

Semi-parametric adaptive control of discrete-time nonlinear ...

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IEEE International Conference on automation and Logistics

作者： Chenguang Yang Tianyou Chai Lianfei Zhai Shuzhi Sam Ge Tong Heng Lee Social Robotics Lab Interactive Digital Media Institute and Department of Electrical and Computer Engineering National University of Singapore Singapore Key Laboratory of Process Industry Automation Ministry of Education Research Center of Automation Northeastern University Shenyang China

In this paper, we investigate a novel adaptive design approach for nonlinear systems as an exploration of the new challenging topic on dealing with both parametric and nonparametric internal uncertainties in adaptive control of discrete-time nonlinear systems. The existence of both two kinds of uncertainties makes it very difficult or even impossible to apply the traditional recursive identification algorithms which are designed for parametric systems. To best utilize the existing adaptive control technique, a novel deadzone with threshold converging to zero has been proposed to modify the traditional gradient update law for parameters estimation, while an auxiliary output including both uncertainties is introduced to facilitate the nonparametric uncertainties compensation. It is rigorously proved that the designed adaptive control guarantees the boundedness of all the closed-loop signals and achieves asymptotic tracking performance.

关键词： Adaptive control Nonlinear systems Sampling methods Path planning Testing automation Road accidents Genetic algorithms Unmanned aerial vehicles Ant colony optimization

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Automated learning for parameter optimization of robotic assembly tasks utilizing genetic algorithms

Automated learning for parameter optimization of robotic ass...

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IEEE International Conference on robotics and Biomimetics

作者： Jeremy A. Marvel Wyatt S. Newman Dave P. Gravel George Zhang Jianjun Wang Tom Fuhlbrigge Electrical Engineering and Computer Science Department Case Western Reserve University Cleveland OH USA Ford Advanced Manufacturing Technology Development Center Detroit MI USA Mechatronics and Robotic Automation ABB Corporate Research Center Windsor CT USA

A challenge for automating mechanical assembly is that cumulative uncertainties typically exceed part clearances, which makes conventional position-based tactics unsuccessful. Force-based assembly strategies offer a potential solution, although such methods are still poorly understood and can be difficult to program. In this paper, we describe a force-based robotic assembly approach that uses fixed strategies with tunable parameters. A generic assembly strategy suitable for execution on an industrial robot is selected by the programmer. Parameters are then self-tuned empirically by the robot using a genetic-algorithm learning process that seeks to minimize assembly time subject to contact-force limits. Results are presented for two automotive part assembly examples using ABB robots with commercial force-control software, showing that the approach is highly effective and suitable for industrial use.

关键词： Robotic assembly Genetic algorithms robotics and automation Service robots Force control Orbital robotics Industrial control Robot control Automatic control Manufacturing automation

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Gait control of modular climbing caterpillar robot

Gait control of modular climbing caterpillar robot

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IEEE/ASME (AIM) International Conference on advanced Intelligent Mechatronics

作者： W. Wang H. X. Zhang K. Wang J. W. Zhang W. H. Chen Robotics Institute School of Mechanical Engineering and Automation Beijing Aeronautics and Astronautics University Beijing China Dept of Informatics University of Hamburg Beijing Germany Department of Computer Science University of Hamburg Hamburg Germany Robotics Institute Beijing University of Aeronautics and Astronautics Beijing China Center of Electrical and Electronics Engineering Beijing University of Aeronautics and Astronautics Beijing China

The concept of a modular climbing caterpillar robot is inspired by the kinematics of the real caterpillar. Due to the fixed constraints between the suckers and wall, the gait of the caterpillar robot engages a changing kinematic chain which is from an open chain to a closed chain, and then to an open chain orderly. This paper investigates the joint control methods of the gait in detail. During the open chain periods, an Unsymmetrical Phase Method (UPM) is applied to ensure the reliable attachment of the passive suckers to the wall. But in the closed chain state, a four links kinematics model is adopted to fulfill the fixed constraints produced by the attached suckers. By combining the two methods together, we acquire complete joint control trajectories for a modular caterpillar robot with seven joints. At the end of this paper, on-site tests confirm the above principles and the validity of the climbing gait.

关键词： Legged locomotion Kinematics Climbing robots robotics and automation Mobile robots Intelligent robots Mechanical engineering computer science Joining processes Tail

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Comparison of rotary cement kiln identified models

Comparison of rotary cement kiln identified models

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International Conference on Control and automation (ICCA)

作者： G. Noshirvani A. Fatehi B. Araabi M. Shirvani M. Azizi ACER Markaz Branch Arak Iran Advanced Process Automation & Control Research group Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran Chemical Engineering Department and member of Cement Research Center University of Science and Technology Tehran Iran Saveh Cement Company Saveh Iran

Rotary cement kiln is the main part of a cement plant that clinker is produced in it. Clinker is the main ingredient of cement. Continual and prolonged operation of rotary cement kiln is vital in cement factories. However, prolonged operation of the kiln is not possible and periodic repairs of the refractory lining would become necessary, due to non-linear phenomena existing in the kiln, such as sudden falls of coatings in the burning zone and probability of damages to the refractory materials during production. This is the basic reason behind the needs for a comprehensive model which is severely necessary for better control of this process. Such a model can be derived based on the mathematic analysis with consultation of expert operator experiences. In this paper both linear and nonlinear model are identified for rotary kiln of Saveh white cement factory. The linear model is introduced using Box-Jenkins structure. The results of the obtained model were satisfactory compared to some other linear models and can be used for designing adaptive or robust controllers. Also, nonlinear system identification via Neural Network technique is performed and its result was compared to linear models.

关键词： Kilns Production facilities Coatings Building materials Process control Mathematical model Mathematics Programmable control Adaptive control Robust control

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Real-Time Level Plant Control Using Improved BELBIC

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IFAC Proceedings Volumes 2008年第2期41卷 4631-4635页

作者： M. Masoudinejad R. Khorsandi A. Fatehi C. Lucas S. Fakhimi Derakhshan M.R. Jamali Advanced Process Automation & Control (APAC) Research Group Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Center of Excellence for Control and Intelligent Processing Electrical and Computer engineering Department University of Tehran Iran

Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control applications. Previous studies show that this controller has fast response, simple implementation and robustness with respect to disturbances. It is also possible to define emotional signal based on control application objectives. But in the previous studies, internal instability of this controller was not considered and control task were done in limited time period. In this article mathematical description of BELBIC is investigated and improved to avoid internal instability. Simulation and implementation of improved model was done on level plant. The obtained results showed that instability of model has been solved in the new model without loss of performance by using Integral Anti Windup (IAW).

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Multi-modal Task Apportionment in dynamic multi-factor systems

Multi-modal Task Apportionment in dynamic multi-factor syste...

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Chinese Control and Decision Conference, CCDC

作者： Hooman A. Samani C. Fua T. Chai S. S. Ge C. C. Hang Social Robotics Laboratory Interactive Digital Media Institute Department of Electrical and Computer Engineering National University of Singapore Singapore Key Laboratory of Process Industry Automation Ministry of Education and Research Center of Automation Northeastern University China

The problem of task apportionment for dynamic multi-factor systems is categorized in three different scenarios in this paper: admin, crew and factor based. The system is discussed based on the realistic manufacturing environments as an application platform in order to consider the robust Task Apportionment system for such a case but the proposed system can be generalized to any similar system. Both centralized and decentralized systems are considered and task allocation, re-allocation, exchange and execution as layers of task apportionment methods are designed and described in each system. The system may switch between modes according the feedback information of communication capabilities or uses different modes for each part of the platform.

关键词： Switches Resource management Manufacturing systems Manufacturing Dynamic scheduling Servers Robustness

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Modeling, parameters identification, and control of an electronic throttle control (ETC) system

Modeling, parameters identification, and control of an elect...

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International Conference on Intelligent and advanced Systems, ICIAS

作者： R. N. K. Loh T. Pornthanomwong J. S. Pyko A. Lee M. N. Karsiti Center for Robotics and Advanced Automation Department of Electrical and Computer Engineering Oakland University Rochester MI USA Electrical & Electronic Systems Architecture CIMS 484-08-06 Chrysler LLC Auburn Hills MI USA Electrical & Electronic Engineering Universiti Teknologi Petronas Bandar Seri Iskandar Tronoh Perak Malaysia

The modeling, parameters identification, and linear and nonlinear feedback control designs of an electronic throttle control (ETC) system is considered. A commercially available ETC system made by Bosch is selected for our investigation. The unknown parameters identified are used in designing linear and nonlinear controllers. Simulations and extensive experiments were conducted. A real-time linear controller was implemented with the xPC Target. The ETC model is then extended to a separately excited nonlinear DC motor model. The nonlinear controller is designed using the input-output feedback linearization technique; the extension proves to be of solid theoretical value. The results presented in this paper can be considered as an interesting and important case study encompassing system modeling, parameters identification, linear and nonlinear controller designs, and real-time control. The techniques and methodology developed are applicable to similar and/or other types of systems.

关键词： DC motors Torque Mathematical model Springs Friction Biological system modeling Real time systems

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A Study On Iterative Learning Control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup-Norm

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Asian Journal of Control 2008年第1期4卷

作者： Kwang-Hyun Park Zeungnam Bien Division of EE Department of EECS Korea Advanced Institute of Science and Technology 373–1 Kusong-dong Yusong-gu Taejon 305–701 Korea. Zeungname Bien:received the B.S. degree in electronics engineering from Seoul National University Seoul Korea in 1969 and the M.S. and Ph.D. degrees in electrical engineering from the University of Iowa Iowa City Iowa U.S.A. in 1972 and 1975 respectively. During 1976–1977 academic years he taught as assistant professor at the Department of Electrical Engineering University of Iowa. Then Dr. Bien joined Korea Advanced Institute of Science and Technology summer 1977 and is now Professor of Control Engineering at the Department of Electrical Engineering and Computer Science KAIST. Dr. Bien was the president of the Korea Fuzzy Logic and Intelligent Systems Society during 1990–1995 and also the general chair of IFSA World Congress 1993 and for FUZZ-IEEE99 respectively. He is currently co-Editor-in-Chief for International Journal of Fuzzy Systems (IJFS) Associate Editor for IEEE Transactions on Fuzzy Systems and a regional editor for the International Journal of Intelligent Automation and Soft Computing. He has been serving as Vice President for IFSA since 1997 and is now Chief Chairman of Institute of Electronics Engineers of Korea and Director of Humanfriendly Welfare Robot System Research Center. His current research interests include intelligent control methods with emphasis on fuzzy logic systems service robotics and rehabilitation engineering and large-scale industrial control systems. Kwang-Hyun Park:received the B.S. M.S. and Ph.D. degrees in electrical engineering and computer science from KAIST Korea in 1994 19997 and 2001 respectively. He is now a researcher at Human-friendly Welfare Robot System Research Center. His research interests include learning control machine learning human-friendly interfaces and service robotics.

It has been found that some huge overshoot in the sense of sup-norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ-norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup-norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.

关键词： Iterative learning control monotone convergence learning interval sup-norm

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