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IEEE Conference on Decision and control

作者： Chandrasekhar Potluri Madhavi Anugolu Yimesker Yihun Parmod Kumar Steve Chiu Marco P. Schoen D. Subbaram Naidu Measurement and Control Engineering Research Center (MCERC) Idaho State University Pocatello Idaho 83201 USA MCERC Idaho State University Pocatello Idaho 83201 USA MCERC College of Engineering Idaho State University Pocatello Idaho 83201 USA Department of Electrical Engineering and Computer Science MCERC Idaho State University Pocatello Idaho 83209 USA Department of Mechanical and Nuclear Engineering MCERC Idaho State University Pocatello Idaho 83209 USA Department of Electrical Engineering and Computer Science MCERC Idaho State University Pocatello Idaho 83201 USA

ISBN: (纸本)9781612848006

This paper presents surface electromyographic (sEMG)-based, real-time Model Reference Adaptive control (MRAC) strategy for a prosthetic hand prototype. The proposed design is capable of decoding the prerecorded sEMG signal as well as the sensory force feedback from the sensors to control the force of the prosthetic hand prototype using a PIC 32MX360F512L microcontroller. The input sEMG signal is preprocessed using a Half-Gaussian filter and fed to a fusion based Multiple Input Single Output (MISO) skeletal muscle force model. This MISO system provides the estimated finger forces to be produced as input to the prosthetic hand prototype. A simple MRAC method along with a two stage embedded design is used for the force control of the prosthetic hand. The sensed force at the fingertip is fed back to the controller for real-time operation. The data is transmitted to the computer through an universal asynchronous receiver/transmitter (UART) interface of the proposed embedded design. Results show good performance in controlling the finger force as well as shortcomings of the mechanical design of the prosthetic hand prototype to be addressed in future.

关键词： Prosthetic hand Force control model reference adaptive control Force force feedback Equipment Design Fingers Hydrologic models Embedded design

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Spectral analysis of sEMG signals to investigate skeletal muscle fatigue

Spectral analysis of sEMG signals to investigate skeletal mu...

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IEEE Conference on Decision and control

作者： Parmod Kumar Anish Sebastian Chandrasekhar Potluri Yimesker Yihun Madhavi Anugolu Jim Creelman Alex Urfer D. Subbaram Naidu Marco P. Schoen Measurement and Control Engineering Research Center (MCERC) School of Engineering Idaho State University Pocatello ID USA MCERC School of Engineering Idaho State University Pocatello ID USA Department of Physical and Occupational Therapy Idaho State University Pocatello ID USA Department of Electrical Engineering and Computer Science MCERC Idaho State University Pocatello ID USA Department of Mechanical Engineering MCERC Idaho State University Pocatello ID USA

ISBN: (纸本)9781612848006;9781612848013

Our recent investigations are focused to develop dynamic models for skeletal muscle force and finger angles for prosthetic hand control using surface electromyographic sEMG as input. Since sEMG is temporal and spatially distributed and is influenced by various factors, muscle fatigue and its related sEMG becomes of importance. This study is an effort to spectrally analyze the sEMG signal during progression of muscle fatigue. The sEMG is captured from the arms of healthy subjects during muscle fatiguing experiments for dynamic and static force levels. Filtered sEMG signal is segmented in five parts with 75% overlap between adjacent segments. The analysis is done using different classical (fast Fourier transform, Welch's averaged modified periodogram), model-based (Yule-Walker, Burg, Covariance and Modified Covariance autoregressive (AR) method), and eigenvector methods (Multiple Signal Classification (MUSIC) and eigenvector spectral estimation method) in frequency domain. Results show that the classical and eigenvector based methods are more sensitive than the model-based methods to fatigue related changes in sEMG signals.

关键词： Muscles Fatigue Force Multiple signal classification Dynamics Estimation Electromyography

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Study of EMS Statements production and Dispatcher Simulation Training for Regional Smart Grid

Study of EMS Statements production and Dispatcher Simulation...

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第八届IEEE信息与自动化国际会议(ICIC 2011)

作者： Xilin Zhang Fan Zhang Xiaojuan Han Shuo Wang Dispatching center Changchun Power Supply Company Changchun 130012China Developing and Planning Department Zhejiang Electric Company Hangzhou China Department of Control and Computer Engineering North China Electrical Power University Beijing 10220 Transformation controlled company Jilin Electric Power Transmission Engineering Corporation Changchu

ISBN: (纸本)9781457702686

From the characteristics in regional grid,the connotation of smart grid and the change of regulation and control integrated management after meeting the requirement of operating monitoring and scheduling management in regional smart grid,statements production of EMS and simulation training of dispatcher in the region smart grid were discussed in this paper.

关键词： EMS simulation training smart grid statement production Smart grids Simulation Training Energy management systems Dispatchers

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AASVMES: An intelligent expert system for realization of Adaptive Autonomy using Support Vector Machine

AASVMES: An intelligent expert system for realization of Ada...

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International Conference on control, Instrumentation, and Automation

作者： N. Hassanpour M. A. Zamani A. Fereidunian H. Lesani Systems and Machines Research Laboratory (SMRL) Control and Intelligent Processing Center of Excellence (CIPCE) School of ECE University of Tehran Tehran Iran Electrical and Computer Engineering Department K. N. Toosi University of Technology Tehran Iran

We earlier introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI). This study presents an expert system for realization of AA, using Support Vector Machine (SVM), referred to as Adaptive Autonomy Support Vector Machine Expert System (AASVMES). The proposed system prescribes proper Levels of Automation (LOAs) for various environmental conditions, here modeled as Performance Shaping Factors (PSFs), based on the extracted rules from the experts' judgments. SVM is used as an expert system inference engine. The practical list of PSFs and the judgments of GTEDC's (the Greater Tehran Electric Distribution Company) experts are used as expert system database. The results of implemented AASVMES in response to GTEDC's network are evaluated against the GTEDC experts' judgment. Evaluations show that AASVMES has the ability to predict the proper LOA for GTEDC's Utility Management Automation (UMA) system, which changes in relevance to the changes in PSFs; thus providing an adaptive LOA scheme for UMA.

关键词： Support vector machines Training Expert systems Complexity theory Automation Adaptive systems Humans

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Semi-Global Stabilization of Linear Time-Delay Systems with Input Energy Constraint

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IFAC Proceedings Volumes 2011年第1期44卷 5106-5111页

作者： Bin Zhou Zongli Lin James Lam Center for Control Theory and Guidance Technology Harbin Institute of Technology P.O. Box 416 Harbin 150001 P. R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743-4743 Charlottesville VA 22904-4743 U.S.A. Department of Mechanical Engineering University of Hong Kong Hong Kong

Abstract This paper is concerned with semi-global stabilization of linear systems with actuator delay and energy constraints. Under the condition of null controllability by vanishing energy, the parametric Lyapunov equation based L 2 low gain feedback is adopted to solve the problem. If the delay in the system is exactly known, a delay-dependent controller is designed and if the delay in the system is either time-varying or not exactly known, a delay-independent controller is established. The proposed approach is used in the linearized model of the relative motion in the orbit plane of a spacecraft with respect to another in a circular orbit around the Earth to validate its effectiveness.

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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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Hybrid control of planar rotations

Hybrid control of planar rotations

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作者： Mayhew, Christopher G. Teel, Andrew R. Electrical and Computer Engineering Department Center for Control Engineering and Computation University of California Santa Barbara CA 93106-9560 United States

ISBN: (纸本)9781424474264

We propose a Lyapunov-based hybrid controller that ensures robust global asymptotic stability of a desired planar orientation, a task that is impossible by continuous or (non-hybrid) discontinuous state feedback due to topological obstructions. The hybrid control structure relies on hysteretically switching between (almost globally) stabilizing control laws which are generated by a family of diffeomorphisms that stretch the space of planar rotations onto itself. A salient feature of the proposed control technique is that it can produce a robustly globally asymptotically stabilizing controller from an existing control law and a corresponding Lyapunov function. © 2010 AACC.

关键词： State feedback

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A Truncated Prediction Approach to Stabilization of Linear Systems with Long Time-Varying Input Delay

A Truncated Prediction Approach to Stabilization of Linear S...

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IEEE Conference on Decision and control

作者： Bin Zhou Zongli Lin Guang-Ren Duan Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin 150001 P.R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 U.S.A.

ISBN: (纸本)9781612848006

This paper studies the problem of stabilizing a linear system with long time-varying delay in the input. Under the assumption that the open-loop system is not exponentially unstable and stabilizable, a finite dimensional static time-varying linear state feedback controller is obtained by truncating the prediction based controller and by adopting the parametric Lyapunov equation based low gain feedback. As long as the time-varying delay is exactly known and bounded, explicit condition is provided to guarantee the stability of the closed-loop system. It is also shown that the proposed controller achieves semi-global stabilization of the system if its actuator is also subject to saturation. Numerical examples show the effectiveness of the proposed approach.

关键词： Linear system time varying state feedback controller Lyapunov equation stabilization system controllers Closed loop systems actuators Induction loop systems

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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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Effect of polymer thickness on the chemical sensing behavior of polymer-coated mass-sensitive disk resonators

Effect of polymer thickness on the chemical sensing behavior...

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IEEE International Conference on Micro Electro Mechanical Systems

作者： S. Truax K.S. Demirci L. Beardslee Y. Luzinova B. Mizaikoff A. Hierlemann O. Brand School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Texas Instrumenits Inc. Dallas TX USA Center of Disease Control and Prevention Atlanta GA USA Institute of Analytical and Bioanalytical Chemistry Ulm University Ulm Germany Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland

ISBN: (纸本)9781424496327

The chemical sensing behavior of disk microresonators, as it is affected by the thickness of polymer coatings applied to them, is reported. The disk microresonators were fabricated using a CMOS-compatible silicon bulk micro machining process. The disks were subsequently coated with layers of (poly) isobutylene (PIB) as a sensing film and exposed to gaseous benzene, toluene, and m-xylene. The experimental results agree well with analytical models derived for both the chemical sensitivity and limit of detection (LOD). Minimal LODs measured for benzene, toluene, and m-xylene were 5.3 ppm, 1.2 ppm, and 0.6 ppm, respectively.

关键词： Polymers Resonant frequency Chemicals Sensitivity Sensors Heating Chemical sensors

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