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International CSI computer Conference, CSICC

作者： A. Shirvani H. Chegini S. Setayeshi C. Lucas Tehran Science and Research Branch Computer Engineering Department Islamic Azad University Iran Faculty of Nuclear Engineering and Physics Amirkabir University of Technology슠 Tehran Iran Electrical and Computer Engineering Department Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran

Polynomials are one of the most powerful functions that have been used in many fields of mathematics such as curve fitting and regression. Low order polynomials are desired for their smoothness, good local approximation and interpolation. Being smooth, they can be used to locally approximate almost any derivable function. This means that when linear functions fail in approximation (e.g. where the first order Taylor expansion equals zero) polynomial functions can be used in local approximation, such that one can achieve better estimations at extremums. In this paper, application of polynomial kernel functions in locally linear neurofuzzy models is shown. Using polynomial kernels in local models, better local approximations in prediction of chaotic time series such as Mackey-Glass is achieved, and the capability of the neurofuzzy network is enhanced.

关键词： Polynomials Kernel Neurons Predictive models Power engineering and energy Chaos Application software Physics computing Power engineering computing Taylor series

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Intelligent-adaptive flight control with a physiologically motivated algorithm

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International Journal of Modelling and Simulation 2009年第1期29卷 12-18页

作者： Mehrabian, A.R. Lucas, C. School of Mechanical Engineering Department of Engineering University of Tehran P.O. Box: 14875 - 347 Tehran Iran Center of Excellence for Control and Intelligent Processing School of Electrical and Computer Engineering Department of Engineering P.O. Box: 14395 - 515 Tehran Iran School of Cognitive Science IPM Tehran Iran

This paper presents a now intelligent approach for adaptive control of non-linear dynamic systems. Based on past researches on emotionally intelligent-control systems, the introduced method is a modified version of Brain Emotional Learning Based Intelligent controller (BELBIC), a physiologically motivated system previously developed and successfully used in control applications. The proposed approach is able to quickly respond to change in environmental and dynamic system and realizes online diroct-adaptivc-control scheme. Showing very good robustness, BELBIC is very simple in implementation and imposes very low computation load on the control system. This modified algorithm has boon successfully applied to real-time longitudinal control of an agile air-to-air missile which has over-changing non-linear dynamics.

关键词： Intelligent systems

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Sensorless vector control of non-salient BLAC machines based on a modified rotor flux-linkage observer

Sensorless vector control of non-salient BLAC machines based...

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International Conference on Power Electronics and Drive Systems (PEDS)

作者： Pongpit Wipasuramonton Z. Q. Zhu David Howe Industrial Control and Automation Laboratory National Electronics and Computer Technology Center Pathum Thani Thailand Department of Electronic and Electrical Engineering University of Sheffield Sheffield UK

The major problems of flux-linkage observer based sensorless techniques are drift and offset effects. To solve such problems, a modified rotor flux-linkage observer is firstly proposed to eliminate the drift phenomena. However, the offset occurrence still exists. Therefore, an adaptive offset cancellation technique is sequentially introduced to solve the offset phenomena. In addition, to further improve the performance of the proposed modified rotor flux-linkage observer, the influence of inaccurate machine parameters to the observer in terms of the estimated rotor position accuracy has been analyzed and, consequently, a simple steady-state rotor position error compensation technique has been introduced which, theoretically, makes the steady-state rotor position error become negligible and parameter insensitive. The performance of the proposed techniques, which was implemented on a low-cost fixed point DSP, is demonstrated experimentally.

关键词： Machine vector control Stators Steady-state Digital signal processing Voltage Automation Error compensation Equations Sensorless control Costs

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Simple initial rotor position estimation method for three-phase star-connected switched reluctance machine

Simple initial rotor position estimation method for three-ph...

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SICE Annual Conference

作者： Pakasit Somsiri Ruchao Pupadubsin Prapon Jitkreeyan Seubsuang Kachapornkul Kanokvate Tungpimolrut Nattapon Chayopitak Pichai Aree Department of Electrical Engineering Thammasat University Pathum Thani Thailand Industrial Control and Automation Laboratory National Electronics and Computer Technology Center Pathum Thani Thailand

This paper proposes a simple method to estimate the initial rotor position of a three-phase star-connected switched reluctance motor at standstill without position or current sensor. The key principle of the initial rotor position estimation is based on the stator inductance variation related to the actual rotor position. In the proposed method, only two narrow pulse voltage injections are applied in sequence and the initial rotor position can be estimated by comparing phase voltages and simple calculation. The method is suitable for low-cost applications where motor parameters and phase current data are not required. The proposed method is implemented for a 6-stator-pole, 4-rotor-pole, and 1.5 kW three-phase star-connected switched reluctance motor. The experimental results show the effectiveness of the proposed method. The accuracy of the initial rotor position estimation is within 2.5 electrical degrees, which is sufficient to start-up the switched reluctance motor without rotor back-kicking.

关键词： Reluctance machines Rotors Reluctance motors Voltage Costs Inductance Motor drives Electric variables control Stator windings Industrial control

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Smart grid design for efficient and flexible power networks operation and control

Smart grid design for efficient and flexible power networks ...

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IEEE PES Power Systems Conference and Exposition, PSCE

作者： James A. Momoh Center of Energy Systems and Control CESaC Department of Electrical and Computer Engineering ECE Howard University College of Medicine Washington D.C. DC USA

The modernization of the US electric power infrastructure, especially in lieu of its aging, overstressed networks; shifts in social, energy and environmental policies, and also new vulnerabilities, is a national concern. Our system are required to be more adaptive and secure more than every before. Consumers are also demanding increased power quality and reliability of supply and delivery. As such, power industries, government and national laboratories and consortia have developed increased interest in what is now called the smart grid of the future. The paper outlines smart grid intelligent functions that advance interactions of agents such as telecommunication, control, and optimization to achieve adaptability, self-healing, efficiency and reliability of power systems. The author also presents a special case for the development of dynamic stochastic optimal power flow (DSOPF) technology as a tool needed in smart grid design. The integration of DSOPF to achieve the design goals with advanced DMS capabilities are discussed herein. This reference paper also outlines research focus for developing next generation of advance tools for efficient and flexible power systems operation and control.

关键词： Smart grids Power system reliability Power systems Power system dynamics control systems Power system control Aging Power quality Telecommunication network reliability Power industry

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Optimal waypoint placement for road surveillance using unmanned aerial vehicles

Optimal waypoint placement for road surveillance using unman...

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作者： McDonald, Suzanne Holsapple, Raymond W. Kingston, Derek University of Maryland College Park MD 20742 United States Air Force Research Laboratory Wright-Patterson AFB OH 45433 United States Department of Electrical and Computer Engineering College Park MD 20742 United States Control Science Center of Excellence Wright-Patterson AFB OH 45433 United States

ISBN: (纸本)9781563479786

In this paper we consider an intelligence, surveillance and reconnaissance (ISR) mission where a human operator and a team of unmanned aerial vehicles (UAVs) are tasked to patrol a road. There are numerous inherent ISR benefits for patrolling a road. For example it might be beneficial to track the suspected movements of enemy troops in a forward operating location. Another example might be to gather intelligence that could then be used, possibly not in real time, to perform change detection, a method that might help with the detection of improvised explosive devices (IEDs). The layout of the road, with respect to a fixed known reference point, is assumed to be known a priori. For example the latitude and longitude coordinates of various points along the road would be sufficient. Most UAV autopilots make use of waypoint navigation to control the vehicle. This work investigates one method of optimally choosing the waypoints for the UAVs along the road. The cost function used minimizes the cross-track area error.

关键词： Cost functions

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Band selection for hyperspectral images based on parallel particle swarm optimization schemes

Band selection for hyperspectral images based on parallel pa...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yang-Lang Chang Jyh-Perng Fang Jon Atli Benediktsson Lena Chang Hsuan Ren Kun-Shan Chen Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Communications Navigation and Control Engineering National Taiwan Ocean University Keelung Taiwan Department of Electrical and Computer Engineering University of Iceland Reykjavik Iceland Center of Space and Remote Sensing Research National Central University Chungli Taiwan

Greedy modular eigenspaces (GME) has been developed for the band selection of hyperspectral images (HSI). GME attempts to greedily select uncorrelated feature sets from HSI. Unfortunately, GME is hard to find the optimal set by greedy operations except by exhaustive iterations. The long execution time has been the major drawback in practice. Accordingly, finding an optimal (or near-optimal) solution is very expensive. In this study we present a novel parallel mechanism, referred to as parallel particle swarm optimization (PPSO) band selection, to overcome this disadvantage. It makes use of a new particle swarm optimization scheme, a well-known method to solve the optimization problems, to develop an effective parallel feature extraction for HSI. The proposed PPSO improves the computational speed by using parallel computing techniques which include the compute unified device architecture (CUDA) of graphics processor unit (GPU), the message passing interface (MPI) and the open multi-processing (OpenMP) applications. These parallel implementations can fully utilize the significant parallelism of proposed PPSO to create a set of near-optimal GME modules on each parallel node. The experimental results demonstrated that PPSO can significantly improve the computational loads and provide a more reliable quality of solution compared to GME. The effectiveness of the proposed PPSO is evaluated by MODIS/ASTER airborne simulator (MASTER) HSI for band selection during the Pacrim II campaign.

关键词： Hyperspectral imaging Particle swarm optimization computer interfaces Concurrent computing Parallel processing Optimization methods Feature extraction computer architecture Graphics Message passing

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A Multi-linear Discriminant Analysis of 2D Frontal Face Images

A Multi-linear Discriminant Analysis of 2D Frontal Face Imag...

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Brazilian Symposium on computer Graphics and Image Processing (SIBGRAPI)

作者： Carlos Eduardo Thomaz Vagner do Amaral Gilson Antonio Giraldi Edson Caoru Kitani João Ricardo Sato Duncan Fyfe Gillies Department of Electrical Engineering FEI Company Sao Paulo Brazil Department of Computer Science LNCC Rio de Janeiro Brazil Department of Electrical Engineering USP-Universidade de São Paulo Sao Paulo Brazil Center of Mathematics Computation and Cognition UFABC Sao Paulo Brazil Department of Computing Imperial College London London UK

We have designed and implemented a multi-linear discriminant method of constructing and quantifying statistically significant changes on human identity photographs. The method is based on a general multivariate two-stage linear framework that addresses the small sample size problem in high-dimensional spaces. Starting with a 2D face data set of well framed images, we determine a most characteristic direction of change by organizing the data according to the features of interest. Our goal here is to use all the facial image features simultaneously rather than separate models for texture and shape information. Our experiments show that the method does produce plausible unseen views for gender, facial expression and ageing changes. We believe that this method could be widely applied for normalization in face recognition and in identifying subjects after a lapse of time.

关键词： Image analysis Principal component analysis Aging Face recognition Active appearance model Linear discriminant analysis Humans Organizing Shape Pixel

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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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Variational Bayesian framework for estimating parameters of integrated E/MEG and fMRI model

Variational Bayesian framework for estimating parameters of ...

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Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Babajani-Feremi, Abbas Bowyer, Susan Moran, John Elisevich, Kost Soltanian-Zadeh, Hamid Image Analysis Lab. Radiology Department Henry Ford Hospital Detroit MI 48202 United States Neuromagnetism Lab. Neurology Department Henry Ford Hospital Detroit MI 48202 United States Department of Neurology Henry Ford Hospital Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran 14395-515 Iran

ISBN: (纸本)9780819475138

The integrated analysis of the Electroencephalography (EEG), Magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) are instrumental for functional neuroimaging of the brain. A bottom-up integrated E/MEG and fMRI model based on physiology as well as a method for estimating its parameters are keys to the integrated analysis. We propose the variational Bayesian expectation maximization (VBEM) method to estimate parameters of our proposed integrated model. VBEM method iteratively optimizes a lower bound on the marginal likelihood. An iteration of the VBEM consists of two steps: a variational Bayesian expectation step implemented using the extended Kalman smoother (EKS) and the posterior probability of the parameters in the previous step, and a variational Bayesian maximization step to estimate the posterior distributions of the parameters. For a given external stimulus, a variety of multi-area models can be considered in which the number of areas and the configuration and strength of connections between the areas are different. The proposed VBEM method can be used to select an optimal model as well as estimate its parameters. The efficiency of the proposed VBEM method is illustrated using simulation and real datasets. The proposed VBEM method can be used to estimate parameters of other non- linear dynamical systems. This study proposes an effective method to integrate E/MEG and fMRI and plans to use these techniques in functional neuroimaging. © 2009 SPIE.

关键词： Electroencephalography

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