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World Haptics Conference

作者： Angelika Peer Cristian Secchi Katsunari Sato Cenk Cavusoglu Institute of Automatic Control Engineering (LSR) Technische Universität München Munchen Germany DISMI University of Modena and Reggio Emilia and INFM Reggio Emilia Italy Graduate School of System Design and Management Keio University Yokohama Kanagawa Japan Department of Electrical Engineering and Computer Sciences Case Western Reserve University Cleveland OH USA

Telerobotics is one of the most traditional fields of robotics and it played a crucial role in the history of robotics and of the mankind, especially in the areas of space and undersea exploration and of remote material handling. On the other hand, teleoperation is still a very active research area and many problems are still open. In particular, the design of the control strategy for coupling local and remote site is of paramount importance for implementing telepresence, namely the feeling of being directly interacting with the remote environment. The IEEE RAS Technical Committee on Telerobotics would like to propose a half-day tutorial for illustrating several successful control strategies for implementing high performance bilateral teleoperation systems.

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Low power and fast DCT architecture using multiplier-less method

Low power and fast DCT architecture using multiplier-less me...

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Faible Tension Faible Consommation (FTFC)

作者： M. El Aakif S. Belkouch N. Chabini M. M. Hassani Embedded Systems and Digital Control Laboratory National School of Applied Sciences University of Cadi Ayyad Marrakech Morocco Department of Electrical and Computer Engineering Royal Military College of Canada Kingston ONT Canada Faculty of Sciences Semlalia University of Cadi Ayyad Marrakech Morocco

In this paper, a low power and fast DCT (Discrete Cosine Transform) using multiplier-less method is presented with a new modified FGA (Flow-Graph Algorithm), which is derived from our previously presented FGA of DCT based on Loeffler algorithm. The multiplier-less method is based on the replacement of multiplications with a minimum number of additions and shifts. The proposed FGA is performed and compared to a previous one. The results of FPGA implementations on Altera Cyclone II show the increase of the maximum frequency, the decrease of the resources usage and the reduction of the dynamic power by 7.2 % at 120 MHz of clock frequency with a new proposed FGA algorithm. Another comparison with recent published results has been done and proves the efficiency of the proposed FGA.

关键词： Discrete cosine transforms Hardware computer architecture Power demand Field programmable gate arrays Algorithm design and analysis Equations

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State and unknown input estimation in a CSTR using higher-order sliding mode observer

State and unknown input estimation in a CSTR using higher-or...

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IEEE Latin American Robotics Symposium, LARS

作者： Bertulfo Giraldo Osorio Héctor Botero Castro Juan Diego Sánchez Torres Escuela de Mecatrónica Facultad de Minas Grupo de Investigación en Procesos Dinámicos-Kalman Universidad Nacional de Colombia Colombia Department of Electrical Engineering and Computer Science Automatic Control Laboratory CINVESTAV Unidad Guadalajara Mexico

The aim of this paper is to design and analyze an observer based on high-order sliding mode to estimate states and unknown inputs in a continuous stirred tank reactor (CSTR). Additionally, the designed HOSM allows to ... 详细信息

关键词： Observers Chemical reactors Mathematical model Robustness Equations Heating Observability

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Compressive System Identification in the Linear Time-Invariant Framework

Compressive System Identification in the Linear Time-Invaria...

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IEEE Conference on Decision and control

作者： Roland Toth Borhan M. Sanandaji Kameshwar Poolla Tyrone L. Vincent Delft Center for Systems and Control Delft University of Technology Mekelweg 2 2628 CD Delft The Netherlands Department of Electrical Engineering and Computer Sciences Colorado School of Mines Golden CO 80401 USA Berkeley Center for Control and Identification University of California at Berkeley 5105 Etcheverry Hall Berkeley CA 94720-1740 USA

ISBN: (纸本)9781612848006

Selection of an efficient model parametrization (model order, delay, etc.) has crucial importance in parametric system identification. It navigates a trade-off between representation capabilities of the model (structural bias) and effects of over-parametrization (variance increase of the estimates). There exists many approaches to this widely studied problem in terms of statistical regularization methods and information criteria. In this paper, an alternative l_(1) regularization scheme is proposed for estimation of sparse linear-regression models based on recent results in compressive sensing. It is shown that the proposed scheme provides consistent estimation of sparse models in terms of the so-called oracle property, it is computationally attractive for large-scale over-parameterized models and it is applicable in case of small data sets, i.e., underdetermined estimation problems. The performance of the approach w.r.t. other regularization schemes is demonstrated in an extensive Monte Carlo study.

关键词： Compressive Sensing System Identification Linear Time-Invariant Systems

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An application of fractional intelligent robust controller for electromechanical valve

An application of fractional intelligent robust controller f...

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World Congress on Information and Communication Technologies (WICT)

作者： Tribeni Prasad Banerjee Suman Saha Swagatam Das Ajith Abraham Department of Electronics and Telecommunication Engineering Jadavpur University Kolkata India Drives and Control System Laboratory CSIR-Central Mechanical Engineering Research Institute Durgapur West Bengal India IT For Innovations EU Center of excellence Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic Scientific Network for Innovation and Research Excellence Machine Intelligence Research Laboratories-MIR Laboratories WA USA

The paper analyzed and model of a fault tolerant electromechanical controlled worm gear driven fuel shut off valve for aerospace application. The analysis is mainly on design a reduced order fractional controller. This is for controlling the velocity of worm gear so that the friction torque due to uneven rotational speed can be avoided. Because with the friction and stiction and backlash the valve system performance is reduced and more and more unstable this leads the system to failure. The proposed controller can provide robustness against the uncertain loading torque and system parameter.

关键词： Valves Gears Equations control systems Robustness Mathematical model Torque

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Adaptive and Repetitive controller for Robotic Manipulators with Slowly Updating Scheme Using B-Spline Shape Function

Adaptive and Repetitive Controller for Robotic Manipulators ...

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IEEE International Conference on Robotics and Biomimetics

作者： Pannatee Rakprayoon Peerayot Sanposh Nattapon Chayopitak Intelligent Mechatronics Automation Robotics and Control Laboratory Department of Electrical Engineering Kasetsart University Industrial Control and Automation Laboratory National Electronics and Computer Technology Center

ISBN: (纸本)9781457721366

This paper studies the real-time adaptive and repetitive control problem using the Desired Compensation Learning Law (DCLL) that has the advantage of robustness under the presence of unknown parameters with low memory requirement. The control structure of DCLL consists of a feedforward compensator that is designed by a linear combination of shape functions that is adaptable to parameter variations;hence the selection of appropriate shape functions plays an important role in the adaptive ability and accuracy of DCLL. In this study, the B-spline shape function is proposed to be used under the slowly updating scheme and the obtained results show that the robustness and accuracy of the tracking can be greatly improved even under payload variation and torque limits.

关键词： shape functions Repetitive controllers Self tuning splines (mathematics) Scheme Robot Manipulator adaptive capacity memory requirements control Architecture Manipulators Unknown parameter Linear Combination

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures.

关键词： Tumors Anisotropic magnetoresistance Diffusion tensor imaging Support vector machines Feature extraction Artificial neural networks

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Decision tree based fault detection and classification in distance relaying

Engineering Intelligent Systems

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engineering Intelligent Systems 2011年第3期19卷 139-147页

作者： Samantaray, S.R. Kamwa, I. Joos, Geza School of Electrical Sciences Indian Institute of Technology Bhubaneswar Odisha India Hydro-Quebec/IREQ Power System Analysis Operation and Control Varennes QC J3X 1S1 Canada Department of Electrical and Computer Engineering McGiII University McConnell 6333480 University Street Montreal QC H3A 2A7 Canada

This paper presents a new approach for fault detection and classification in transmission line using Decision Tree (DT). The DT based fault detection algorithm uses 1/4th cycle data of fault currents from fault inception, to generate the optimal decision tree for fault detection. Similarly, the DT based classification algorithm takes half cycle data from fault inception of three phase currents along with zero sequence current, and constructs the optimal decision tree for classifying all 10 types of shunt faults in the transmission line fault process. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network. The results indicate that the proposed method can reliably detect and classify faults in transmission line within the sub-cycle time-frame while keeping the computational burden sufficiently low to make a real-time implementation feasible. © 2011 CRL Publishing Ltd.

关键词： Decision trees

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High-Order Sliding-Mode control of Blood Glucose Concentration via Practical Relative Degree Identification

High-Order Sliding-Mode Control of Blood Glucose Concentrati...

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IEEE Conference on Decision and control

作者： Ana Gabriela Gallardo Hernandez Leonid Fridman Arie Levant Yuri Shtessel Ron Leder Cristina Revilla Monsalve Sergio Islas Andrade Universidad Nacional Autonoma de Mexico (UNAM) Department of Control Engineering Faculty. C.P. 04510. Mexico D.F. Control Department of Cinvestav IPN on leave of UNAM Applied Mathematics Department in Tel-Aviv University Tel-Aviv 69978 Israel Department of Electrical and Computer Engineering University of Alabama in Huntsville Huntsville AL 35899 Centro Medico Nacional Siglo XXI Av. Cuauhtemoc 330 Col. Doctores C.P. 06725 Mexico D.F.

ISBN: (纸本)9781612848006

This research introduces a novel concept of practical relative degree and presents a numerical method of practical relative degree identification. The concept efficacy is demonstrated by computer simulation of a High-Order Sliding-Mode controller, effectively stabilizing the blood glucose concentration for two well known models with different relative degrees.

关键词： Blood Glucose Variable structure systems higher-order Family Members glucose concentration Numerical methods Slip forming

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Experimental comparison of AdaBoost algorithms applied on leg detection with different range sensor setups

Experimental comparison of AdaBoost algorithms applied on le...

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19th International Workshop on Robotics in Alpe-Adria-Danube Region, RAAD 2010

作者： Jurić-Kavelj, Srećko Petrović, Ivan Department of Control and Computer Engineering University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9781424468867

When tracking people or other moving objects with a mobile robot, detection is the first and most critical step. At first most researchers focused on the tracking algorithms, but recently AdaBoost (supervised machine learning technique) was used for people legs detection in 2D range data. The results are promising, but it is unclear if the obtained classifier could be used on the data from another sensor. As it would be a huge inconvenience having to train a classifier for every sensor (setup), we set out to find if, and when is a classifier trained on one sensor setup transferable to another sensor setup. We tested two sensors in five different setups. In total, we acquired 2455 range scans. Experiments showed that the classifier trained on noisier sensor data performed better at classification of data coming from other sensor setups. Classifiers trained on less noisy data were shown to be overconfident, and performed poorly on noisy data. Furthermore, experiments showed that classifiers learned on ten times smaller datasets performed as good as classifiers trained on larger datasets. Since AdaBoost is a supervised learning technique, obtaining same classifier efficiency with significantly smaller dataset means less hand labeling of the data for the same results. © 2010 IEEE.

关键词： Adaptive boosting

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