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ZMP analysis for dynamic walking of a passivity-based biped robot with flat feet

ZMP analysis for dynamic walking of a passivity-based biped ...

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作者： Fatehi, Nima Akbarimajd, Adel Asadpour, Masoud Mechatronic Group Electrical and Computer Engineering Faculty Qazvin Branch of Islamic Azad University Qazvin Iran ECE Group Faculty of Engineering University of Mohaghegh Ardabili Ardabil Iran Control and Intelligent Processing Center of Excellence Electrical Engineering Faculty University of Tehran Tehran Iran

ISBN: (纸本)9781424474530

Zero moment point has been usually employed for balance keeping and walking analysis of active biped robots with bent knees, while balance and walking stability analysis of passive robots has been done using cyclic analysis approaches. While the problem in general is common, the two approaches have been separated in the literature for two different classes of passivity-based and ZMP-based robots. In this paper we have made a ZMP analysis for a passivity-based biped robot. The robot has been simulated using MSC Adams and Matlab/Simulink and a stable walking is achieved for a defined walking policy which is based on passivity-based walking with hips and ankles actuated and knee joints considered passive. The trajectory of ZMP is extracted and discussed during a stable walking. The role of Achill's spring on ZMP is discussed and the overall profile of ZMP trajectory and its changes at specific crucial events, like knee strike and heel strike, is analyzed. ©ICROS.

关键词： Robots

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Shared Situation Awareness System Architecture for Network Centric Environment Decision Making

Shared Situation Awareness System Architecture for Network C...

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International Conference on Computer and Network Technology (ICCNT)

作者： Hossein Parvar Mehdi N. Fesharaki Behzad Moshiri CE Department Science & Research Branch Islamic Azad University Tehran Iran Control & Intelligent Processing Center of excellence School of ECE University of Tehran Tehran Iran

ISBN: (纸本)9781424469611

Having full and accurate situation awareness is a critical foundation of successful decision-making in network centric environments. Virtual collaboration, virtual organization and people coordination are the result of Situation awareness in net centric systems. On the other hand, having situation awareness reduces operation cost and risk and increases speed of responsibility, speed of operation and total performance of decision makers. In this paper, we present a new architecture to provide shared situation awareness for net centric decision-making using multi-resolution level architecture. In this system decision-maker requests the needed information and the system provides the requested information and situation awareness for decision-making. According to this architecture, knowledge organization, activity principles, theoretical approach for design, control and software engineering provide for shared situation awareness system.

关键词： Decision making Computer architecture Bandwidth control systems Humans Robust stability Computer networks Process control intelligent control intelligent networks

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Adaptive generalized predictive control and model reference adaptive control for CSTR Reactor

Adaptive generalized predictive control and model reference ...

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International Conference on intelligent control and Information processing (ICICIP)

作者： Mahboobeh Delbari Karim Salahshoor Behzad Moshiri Islamic Azad University Iran Department of Automation and Instrumentation Petroleum University of Technology Iran Control & Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran

Large numbers of industrial chemical process have nonlinear and time varying behavior, so to achieve good control properties it's necessary to use a powerful identification method that can track these variations properly. In this paper, an on- line recursive least square identification method based on ARX is used to have good knowledge about dynamic behavior of system, then for control goals two adaptive method is present: indirect adaptive control based pole placement and adaptive general predict control(GPC). The advantages of the methodologies are demonstrated on nonlinear Continuous Stirred Tank Reactor (CSTR) simulations. desired control properties is reached with a good parameter estimation and achieved results show the successful identifications and control methodologies. Result of two control strategy are compared together and advantages of Adaptive GPC is shown for time varying systems like CSTR.

关键词： Adaptation model Chemical reactors Adaptive control Mathematical model Process control Parameter estimation Inductors

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Recursive Gath-Geva clustering as a basis for evolving neuro-fuzzy modeling

Recursive Gath-Geva clustering as a basis for evolving neuro...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Hossein Soleimani-B Caro Lucas Babak N. Araabi Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Fundamental Sciences (IPM) Institute for Research in Fundamental Sciences Tehran Iran

A recursive extension of Gath-Geva clustering algorithm is proposed in this paper which is used as a basis for online tuning and development of neuro-fuzzy models. In comparison with other online modeling approaches which use spherical clusters for defining validity region of neurons, the proposed evolving neuro-fuzzy model (ENFM) has the ability to take advantage of elliptical clusters. This extension increases the ability of local linear neurons of ENFM to capture system behavior in more sophisticated regions which leads to decrease in number of neurons as well as increase in the modeling ability. The proposed model is capable of adapting to changes in system behavior by adding new neurons or merging similar existing fuzzy rules. Efficiency of evolving neuro-fuzzy model is investigated in prediction of Mackey-Glass and smoothed sunspot number time series. Results of these simulations show better performance of the proposed model as compared with other online modeling approaches.

关键词： Clustering algorithms Neurons Covariance matrix Time series analysis Mathematical model Computational modeling Adaptation model

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Error Concealment in Image Communication Using Edge Map Watermarking and Spatial Smoothing 2nd

Error Concealment in Image Communication Using Edge Map Wate...

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2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Shabnam Sodagari Alireza Nasiri Avanaki Peyman Hesami Electrical Engineering Dept. The Pennsylvania State University University Park PA 16803 Control and Intelligent Processing Center of Excellence School of ECE University of Tehran TehranIr

ISBN: (纸本)9781424463473

We propose a novel error concealment algorithm to be used at the receiver side of a lossy image transmission system. Our algorithm involves hiding the edge map of the original image at the transmitter within itself using a robust watermarking scheme. At the receiver,wherever a lost block is detected,the extracted edge information is used as border constraint for the spatial smoothing employing the intact neighboring blocks in order to conceal errors. Simulation results show the superiority of our technique over existing methods even in case of high packet loss ratios in the communication network.

关键词： edge detection error concealment image communication spatial smoothing watermarking

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Single Channel Speech Separation with a Frame-based Pitch Range Estimation Method in Modulation Frequency

Single Channel Speech Separation with a Frame-based Pitch Ra...

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International Symposium on Telecommunications

作者： A. Mahmoodzadeh H. R. Abutalebi H. Soltanian-Zadeh H. Sheikhzadeh Speech Proc. Research Lab ECE Dept. Yazd University Control and Intelligent Processing Center of Excellence University of Tehran EE Dept. Amirkabir University of Technology

ISBN: (纸本)9781424481835

Computational Auditory Scene Analysis (CASA) has attracted a lot of interest in segregating speech from monaural mixtures. In this paper, we propose a new method for single channel speech separation with frame-based pitch range estimation in modulation frequency domain. This range is estimated in each frame of modulation spectrum of speech by analyzing onsets and offsets. In the proposed method, target speaker is separated from interfering speaker by filtering the mixture signal with a mask extracted from the modulation spectrogram of mixture signal. Systematic evaluation shows an acceptable level of separation comparing with classic methods.

关键词： Modulation frequency Speech separation Pitch frequency Acuostic frequency

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Decision making strategy in the designing of a fuzzy controller for inverted pendulum-cart system

Decision making strategy in the designing of a fuzzy control...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： S. Khailaie P. Bahmanyar Caro Lucas Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Electrical Engineering Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran

In this paper, a multi-objective heuristic-based method of design of a fuzzy controller for an inverted pendulum-cart system is investigated. A heuristic search optimization called “Imperialist Competitive Algorithm” is proposed to be used in generating and optimizing the fuzzy rules engine. The main purpose of this paper is to design a model-free nonlinear controller for inverted pendulum-cart system which can regulate a wide range of initial conditions and minimize a pre-defined quadratic performance index by taking into account the physical system constraints. Also the system constraints are proposed to be coded using Pontryagin method. All the objectives and system constraints are assumed to be fuzzy objectives and fuzzy constraints. The simulation results show the effectiveness of the proposed algorithm in problem objectives and constraints satisfaction compared to the optimal linear and nonlinear controller.

关键词： Performance analysis Mathematical model Optimization Decision making Indexes Equations Approximation methods

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Traffic state variables estimating and predicting with neural network via extended Kalman filter algorithm with estimated parameters as offline

Traffic state variables estimating and predicting with neura...

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8th IEEE International Symposium on intelligent Systems and Informatics, SIISY 2010

作者： Abdi, J. Moshiri, B. Jafari, E. Khaki Sedigh, A. Department of Electrical and Computer Engineering Islamic Azad University Science and Research Branch Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781424473946

Developing mathematical models and estimating their parameters are fundamental issues for studying dynamic behaviors of traffic systems. METANET model is one of the most applicable models in traffic modeling in which the parameters have plenty of effects on the model behavior. In this paper, the effects of the model parameters on the model behavior and the estimation quality of the system states in the undetermined parameters are described. The extended Kalman filtering (EKF) algorithm instead of the error back-propagation (BP) algorithm is used to train artificial neural networks (ANNs) for dynamical traffic networks modeling. The basic idea is to prevent over fitting discrepancy occurrence caused by outliers in the training samples by the EKF. Numerical simulations show that the EKF algorithm is greater to the BP algorithm. ©2010 IEEE.

关键词： Neural networks

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A chaotic model for generating heart rate variability signal using integral pulse frequency modulation

A chaotic model for generating heart rate variability signal...

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Computers in Cardiology (CinC)

作者： Mahdi Lak Nader Jafarnia Dabanloo S Kamaledin Setarehdan Biomedical Engineering Faculty Science and Research Islamic Azad University Tehran Iran Control and Intelligent Processing Center of Excellence Faculty of Electrical & Computer Engineering University of Tehran Tehran Iran

Heart rate variability (HRV) is a very useful signal to investigate the activity of the autonomic nervous system (ANS), which affects and the heart function. Constructing a mathematical model for producing artificial HRV signal is needed to get a conceptual understanding of how ANS controls the heart rate (HR). The integral pulse frequency modulation (IPFM) structure is employed in this paper to model the sino-atrial node (SAN). Considering the complexity and nonlinear dynamics in the real HRV signal, a chaotic input is used in the proposed model. Instead of using a fixed threshold in IPFM model as in most previous works, we applied an appropriate variable signal, which has nonlinear chaotic dynamics. After running the model, the power spectrum of the output signal is extracted, which was then followed by calculating the nonlinear characteristics. The results were closely correlated with the real data, which confirm the effectiveness of the proposed model.

关键词： Heart rate variability Mathematical model Computational modeling Pacemakers Biological system modeling

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A statistical shape model using 2D-principal component analysis from few medical samples and its evaluation

A statistical shape model using 2D-principal component analy...

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International Conference on Software Engineering and Data Mining (SEDM)

作者： Tomoko Tateyama Taishi Tanaka Shinya Kohara Amir Hossein Foruzan Akira Furukawa Yen-Wei Chen Intelligent Image Processing Laboratory College of Information Science and Engineering Ritsumeikan University Shiga Japan Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Radiology Shiga University of Medical Science Shiga Japan

ISBN: (纸本)9781424473243;9788988678220;9788988678213

Since the medical training samples are very limited, it is difficult to construct a statistical shape model with good generalization using few samples. In this paper, we propose a novel statistical shape modeling method using 2D PCA. The 3D shape is represented as a matrix by spherical parameterization. The experiments showed that our proposed method can reconstruct statistical shape model with good generalization even using fewer samples.

关键词： Biomedical imaging Shape control Biomedical engineering Principal component analysis Liver Information analysis Educational institutions Azimuth Covariance matrix Image analysis

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