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Experimental evaluation of power control algorithms for wireless sensor networks

IFAC Proceedings Volumes 2008年第2期41卷 619-624页

作者： Pan Gun Park Carlo Fischione Karl H. Johansson Automatic Control Lab School of Electrical Engineering Royal institute of technology Stockholm Sweden Department of Electrical Engineering and Computer Sciences UC Berkeley Berkeley CA USA

The main contribution of this paper is the implementation and experimental evaluation of thee radio power control algorithms for wireless sensor networks. We illustrate the necessity of lightweight radio power control algorithms for the deployment of wireless sensor networks in realistic situations. Furthermore, based on a simple loss model, we develop an algorithm that optimizes the transmit power while guaranteeing a desired packet error probability. The simple power control strategy is also compared with two other strategies in experiments using Tmote Sky sensor nodes. A component-based software implementation in the Contiki operating system is used.

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Newton Method based Iterative Learning control of the Upper Limb

Newton Method based Iterative Learning Control of the Upper ...

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2008 American control Conference (ACC), vol.9

作者： I. L. Davies C. T. Freeman P. L. Lewin E. Rogers D. H. Owens School of Electronics and Computer Science University of Southampton Southampton UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

A non-linear iterative learning control algorithm is used for the application of functional electrical stimulation to the human arm. The task is to track trajectories in the horizontal plane and stimulation is applied to the triceps muscle. A model of the system is first produced, and then the equations required to implement the control law are derived. Practical considerations are high-lighted and the issue of parameter selection is discussed. Experimental results are subsequently presented, and are used to confirm that the algorithm is capable of exhibiting robustness together with achieving a high level of performance when practically applied to a control problem.

关键词： Newton method Iterative methods Robots control systems Neuromuscular stimulation Trajectory Muscles Electrical stimulation Iterative algorithms Humans

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Issues in sampling and estimating continuous-time models with stochastic disturbances

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IFAC Proceedings Volumes 2008年第2期41卷 14360-14365页

作者： Lennart Ljung Adrian Wills Division of Automatic Control Linköpings Universitet SE-581 80 Linköping Sweden School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW 2308 Australia

The standard continuous time state space model with stochastic disturbances contains the mathematical abstraction of continuous time white noise. To work with well defined, discrete time observations, it is necessary to sample the model with care. The basic issues are well known, and have been discussed in the literature. However, the consequences have not quite penetrated the practise of estimation and identification. One example is that the standard model of an observation being a snapshot of the current state plus noise independent of the state cannot be reconciled with this picture. Another is that estimation and identification of time continuous models require a more careful treatment of the sampling formulas. We discuss and illustrate these issues in the current contribution. An application of particular practical importance is the estimation of models based on irregularly sampled observations.

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Maximum Likelihood Identification of Wiener Models

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IFAC Proceedings Volumes 2008年第2期41卷 2714-2719页

作者： Anna Hagenblad Lennart Ljung Adrian Wills Division of Automatic Control Linköpings Universitet SE-581 80 Linköping Sweden School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW 2308 Australia

The Wiener model is a block oriented model having a linear dynamic system followed by a static nonlinearity. The dominating approach to estimate the components of this model has been to minimize the error between the simulated and the measured outputs. We show that this will in general lead to biased estimates if there is other disturbances present than measurement noise. The implications of Bussgang's theorem in this context are also discussed. For the case with general disturbances we derive the Maximum Likelihood method and show how it can be efficiently implemented. Comparisons between this new algorithm and the traditional approach confirm that the new method is unbiased and also has superior accuracy.

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Parameter Estimation for Discrete-Time Nonlinear Systems Using EM

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IFAC Proceedings Volumes 2008年第2期41卷 4012-4017页

作者： Adrian Wills Thomas B. Schön Brett Ninness School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW 2308 Australia Division of Automatic Control Linköping University SE-581 83 Linköping Sweden

In this paper we consider parameter estimation of general stochastic nonlinear state-space models using the Maximum Likelihood method. This is accomplished via the employment of an Expectation Maximisation algorithm, where the essential components involve a particle smoother for the expectation step, and a gradient-based search for the maximisation step. The utility of this method is illustrated with several nonlinear and non-Gaussian examples.

关键词： Nonlinear estimation maximum likelihood system identification expectation maximisation

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Model-Based Vibration Suppression in Piezoelectric Tube Scanners through Induced Voltage Feedback

Model-Based Vibration Suppression in Piezoelectric Tube Scan...

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2008 American control Conference (ACC), vol.5

作者： Johannes Maess Andrew J. Fleming Frank Allgower Institute for Systems Theory and Automatic Control Universität Stuttgart Stuttgart Germany School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW Australia

The operation speed and tracking accuracy of piezoelectric tube actuators in scanning probe microscopy is significantly reduced due to the excitation of the scanner eigenfrequencies by the driving voltages. Feedback control is a suitable method for vibration suppression but suffers from the required additional sensor equipment and high cost for generation of a displacement feedback signal. Operating the piezotube in single-electrode excitation mode allows the comparatively uncomplex measurement of the induced voltages at sensor electrodes. The Finite Element (FE) approach enables an accurate modeling of the voltage signals. Furthermore, geometrical details included in the dynamic FE-model are the sample mass attached to the top of the tube as well as tube eccentricity and dislocated electrodes. Additionally, the FE-model accounts for dynamics-coupling effects along the separate axes of the three-dimensional tube motion. Comparison with experimental data demonstrates the accuracy of the FE-model. The controller employing the induced voltage as a feedback signal is designed by means of a reduced order model obtained from modal truncation. The efficacy of the controller is illustrated by closed-loop simulations.

关键词： Electrodes Piezoelectric actuators Scanning probe microscopy Feedback control Vibration control Costs Signal generators Finite element methods Voltage control Signal design

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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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Conflict resolution for collaborative design based on rough set theory

Conflict resolution for collaborative design based on rough ...

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International Conference on computer Supported Cooperative Work in Design

作者： Jun Ma Tian-Yuan Xiao Jian-Chao Zeng Ma Hao Department of Automation National CIMS Engineering Research Center Tsinghua University Beijing China School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan China North Automatic Control Technology Institute Taiyuan China

ISBN: (纸本)9781424416509

Due to the design knowledge discrepancy during collaborative design, conflicts can be revealed from the process of collaborative design decision. A critical element of collaborative design would be conflict resolution. The conflict resolution is correlative with both of the knowledge granulation and specific method provided. In this paper, granularity is used to describe rules acquainted based on the concept of rough degree. In this condition, A feasible distance formula between different rules is constructed according to the requirement of describing the distance between different rules and the definition of attribute significance in information system with rough theory, in which the operator of attribute importance is introduced, and then traditional conflict resolutions are analyzed. As a result, the concept of rule set evolution is put forward, and the instance is introduced to explain the efficiency of new method.

关键词： Collaboration Set theory Collaborative work Process design Design methodology Product design Phase detection Knowledge management Space technology Design automation

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Motivation and Competitive Learning in a Social Robot

Motivation and Competitive Learning in a Social Robot

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2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pages 3661-4172

作者： Salvador Dominguez Eduardo Zalama Jaime G. Garcia-Bermejo Jaime Pulido Robotics Computer Vision and Real Time Division CARTIF Foundation Boecillo Valladolid Spain DepDepartment of Systems Engineering and Automatic Control Industrial Engineering School University of Valladolid Spain University of Valladolid (Spain) Dep. of Systems Engineering and Automatic Control Industrial Engineering School Comput. Vision & Real Time Div. CARTIF Found. Valladolid

ISBN: (纸本)9781424420575

This paper describes the motivation and learning subsystems of Arisco which is a mechatronic head with interactive capacity which includes high expressivity through gesturing, voice recognition, text to speech generation, visual tracking, and internet information retrieval. The general architecture is first described in the paper. Then, the learning capacity of Arisco is addressed. It learns and performs associations between different stimulus responses through several dynamic neural networks, guided by motivational drives. A number of experiments are discussed, covering stimulus competition, habituation, classical and operant conditioning.

关键词： Social robot learning interaction computer vision motivation

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Neural networks for disturbance and friction compensation in hard disk drives

Neural networks for disturbance and friction compensation in...

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IEEE Conference on Decision and control

作者： Chow Yin Lai Frank L. Lewis V. Venkataramanan Xuemei Ren Shuzhi Sam Ge Thomas Liew Centre for Life Sciences (CeLS) Graduate School for Integrative Sciences and Engineering (NGS) National University of Singapore Singapore Automation and Robotics Research Institute University of Texas Arlington Fort Worth TX USA Data Storage Institute Engineering Agency for Science Technology and Research Singapore Department of Automatic Control Beijing Institute of Technology Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781424431236

In this paper, we show that the tracking performance of a hard disk drive actuator can be improved by using two adaptive neural networks, each of which is tailored for a specific task. The first neural network utilizes accelerometer signal to detect external vibrations, and compensates for its effect on hard disk drive position via feedforward action. In particular, no information on the plant, sensor and disturbance dynamics is needed in the design of this neural network disturbance compensator. The second neural network, designed to compensate for the pivot friction, uses a signum activation function to introduce nonlinearities inherent to pivot friction, thus reducing the neural network¿s burden of expectation. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the tracking performance of the hard disk drives can be improved significantly with the use of both neural networks compared to the case without compensation, or when only one of the networks is activated.

关键词： Neural networks Friction Hard disks Actuators Adaptive systems Feedforward neural networks Accelerometers Signal detection Stability analysis Stability criteria

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