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NEURO-FUZZY BASED FAULT DIAGNOSIS OF A STEAM GENERATOR

IFAC Proceedings Volumes 2009年第8期42卷 1180-1185页

作者： Roozbeh Razavi-Far Hadi Davilu Vasile Palade Caro Lucas Department of Nuclear Engineering Amirkabir University of Technology P.O. Box 15875-4413 Tehran Iran (Tel:+98-***) Computing Laboratory Oxford University Wolfson Building Parks Road Oxford OX1 3QD UK Center of Excellence on Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran P.O. Box 14395-1515 Tehran Iran

This paper focuses on the development and application of a Neuro-Fuzzy (NF) networks-based scheme for Fault Detection and Isolation (FDI) in a U-tube Steam Generator (UTSG). First, a NF network is trained with data collected from a full scale UTSG simulator, and residuals are generated for fault detection. To identify the UTSG, a Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained using the Locally Linear Model Tree (LOLIMOT) algorithm which is an incremental tree structure algorithm. Then, an evolutionary algorithm is used to train a Mamdani type NF network to classify the residuals. The residuals are analyzed by using this NF classifier for fault isolation purposes.

关键词： Fault Diagnosis Neuro-Fuzzy Networks Locally Linear Neuro Fuzzy Model Locally Linear Model Tree Steam Generator

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Design of optimal fuzzy logic-PID controller using bee colony optimization for frequency control in an isolated wind-diesel system

Design of optimal fuzzy logic-PID controller using bee colon...

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IEEE/PES Transmission and Distribution Conference and Exhibition: Asia and Pacific

作者： T. Chaiyatham I. Ngamroo S. Pothiya S. Vachirasricirikul Department of Electrical Engineering King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand Center of Excellence for Innovative Energy Systems King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand School of Communication Instrumentation & Control Sirindhorn International Institute of Technology Thammasat University Thailand

ISBN: (纸本)9781424452293

Generally, the inevitable problems in the fuzzy logic-PID (FLPID) control design are the trial and error of the setting of scale factors, membership functions and control rules. To solve these problems, this paper proposes the optimal FLPID controller design using bee colony optimization (BCO) for the load frequency control in the microgrid system. The considered microgrid is the hybrid wind-diesel isolated system. The BCO is applied to automatically optimize the FLPID controllers of governor in the diesel side and blade pitch control in the wind side. Simulation studies show the superior robustness of the optimal FLPID against system parameters variation in comparison with the optimal PID controller and the non-optimal FLPID controller.

关键词： Fuzzy control Fuzzy logic Fuzzy systems Optimal control control systems Design optimization Frequency control Automatic control Fuzzy sets control design

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Model based method for determining the minimum embedding dimension from solar activity chaotic time series

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International Journal of engineering, Transactions A: Basics 2008年第1期21卷 31-44页

作者： Mirmomeni, M. Lucas, C. Center of Excellence of Control and Intelligent Processing Department of Electrical and Computer Engineering University Tehran Iran

Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction's accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several methods have been introduced for prediction of solar activity indices especially the sunspot number, which is a common measure of solar activity. In this paper, the problem of embedding dimension estimation for solar activity chaotic time series based on polynomial models is considered. The optimality of embedding dimension has an important role in computational efforts, Lyapunov exponents' analysis and efficiency of prediction. The method of this paper is based on the fact that the reconstructed dynamics of an attractor should be a smooth map, i.e. with no self intersection in the reconstructed attractor. To check this property, a local general polynomial autoregressive model is fitted to the given data and a canonical state space realization is considered. Then, the normalized one-step forward prediction error for different orders and various degrees of nonlinearity in polynomials is evaluated. Besides the estimation of the embedding dimension, a predictive model is obtained which can be used for prediction and estimation of the Lyapunov exponents. This algorithm is applied to indicate the minimum embedding dimension of sunspot numbers (SSN), Disturbance Storm Time or Dst. and Proton Flux indices are some of the most important among solar activity indices and results depict the power of the proposed method in embedding dimension estimation.

关键词： Polynomials

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Evaluation of Liver Shape Approximation and Characterization

Evaluation of Liver Shape Approximation and Characterization

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Farshid Babapour Mofrad Reza Aghaeizadeh Zoroofi Yen-Wei Chen Ali Abbaspour Tehrani-Fard Yoshinobu Sato Akira Furukawa Faculty of Engineering Science and Research Branch Islamic Azad University Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Engineering College of Engineering University of Tehran Tehran Iran College of Information and Science Ritsumeikan University Shiga Japan Electrical and Electronic Engineering School Sharif University of Technology Tehran Iran Division of Image Analysis Graduate School of Medicine Osaka University Osaka Japan Department of Radiology Shiga University of Medical Science Shiga Japan

A computational framework is presented for 3-D liver shape approximation and characterization in order to determine the accuracy of shape reconstruction via Spherical Harmonics expansion. Spherical Harmonics is a powerful mathematical tool for expanding the shape. But in medical domain, livers have very variation geometry, in shape, size, and volume. In this regards, we evaluated and optimized the Spherical Harmonics to create 3-D parametric surface of the liver from Computed Tomography (CT) imaging system which may useful for Shape modeling, surface representation, physical measurement of objects and mathematical model. We select randomly 5 livers from more 100 dataset. Mean Hausdorff distance Errors and Dice similarity coefficient DSC by liver volumes was measured. The experimental results showed that the best order of Spherical Harmonics Expansion for livers is between 12~17.

关键词： Liver Computed tomography Shape measurement Mathematical model Image reconstruction Power system harmonics Biomedical imaging Geometry Surface reconstruction Power system modeling

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Optimal allocation of spinning reserve in a restructured power system using particle swarm optimization

Optimal allocation of spinning reserve in a restructured pow...

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IEEE Canadian Conference on electrical and Computer engineering, CCECE 2008

作者： Hajian-Hoseinabadi, H. Fotubi-Firuzabad, M. Hajian, M. IEEE Department of Electrical Engineering Sharif University of Technology Tehran Iran Center of Excellence in Power System Control and Management Electrical Engineering Department Sharif University of Technology

ISBN: (纸本)9781424416431

A reasonable amount of spinning reserve is essential to satisfy system security constraints when the power system encounters a contingency. Most ofthe methods previously developed for spinning reserve assessment ignore the probabilistic aspects of system components. This paper presents the design of a market for energy and spinning reserve services. This dispatching method has been developed to minimize the cost associated with theses services while maintaining the system security. Particle swarm optimization (PSO) is used for determining the global optimal solution for this dispatch problem. The effectiveness of the proposed approach is examined by application to the IEEE Reliability Test System (RTS). The results obtained with the proposed approach are presented and compared with those of Genetic Algorithms (GA). © 2008 IEEE.

关键词： Genetic algorithms

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Modelling time dependent swelling potential of mudrock using laboratory tests and artificial neural network

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Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology 2008年第1期117卷 32-41页

作者： Doostmohammadi, R. Moosavi, M. Araabi, B.N. Mining Engineering Department Zanjan University 5 km Tabriz road Zanjan Iran School of Mining Engineering University of Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Iran

The focus of this research work is modelling time dependent swelling strain and pressure simultaneously in weak rock. Various swelling potential under different boundary conditions is considered. Free and semiconfined swelling strain and swelling pressure under oedometric condition are the most proposed tests for determination of the swelling potential of weak rock. In this paper, a modified swelling strain and pressure test is introduced using springs to provide deformable axial stiffness. The swelling strain and pressure of mudrock are modelled by artificial neural network for various swellable clay, carbonate, initial water content and different boundary stiffness, by using a combination of the proposed modified test along with the existing tests. This method correlates the results of laboratory tests with an acceptable accuracy. The proper operation of the developed model for predicting the time dependent swelling strain and pressure of mudrock under deformable and rigid axial boundaries is confirmed. © 2008 Institute of Materials, Minerals and Mining.

关键词： Neural networks

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Introducing an incremental learning method for fuzzy descriptor models to identify nonlinear singular systems

Introducing an incremental learning method for fuzzy descrip...

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2008 Mediterranean Conference on control and Automation, MED'08

作者： Mirmomeni, M. Lucas, C. Shafiee, M. Araabi, B.N. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Eng. University of Tehran Tehran Iran Electrical Engineering Department Amirkabir University of Technology Tehran Iran School of Cognitive Sciences Institute for Studeils in Theoretical Physice and Mathematics Tehran Iran

ISBN: (纸本)9781424425051

Singular systems have been the subject of interest over the last two decades due to their many practical applications. But it has to be said that system identification of such system is still a challenging area because of the difficulty of identification of such systems for their complex structures. In addition, it seems that by developing a useful method for identification of singular system, one can use the useful property of such systems in describing the natural complex phenomena. This paper presents a novel methodology for identifying nonlinear singular systems from empirical data. Singular systems are idealized models for systems with slow and quick modes of change. However, their identification is a challenging problem even for the linear case. A new learning method, generalized locally linear model tree (GLoLiMoT) algorithm is introduced. The contribution of this paper is to provide a method for adjusting the parameters of fuzzy descriptor model, e.g. the splitting ratio and the standard deviation, the number of locally linear neurons or the number of linear singular systems for the consequent part in fuzzy descriptor model as well as the order of the singular system. By these modifications an accurate model of nonlinear singular system is obtained which is compared with several other methods in two case studies. Results depict the power of the proposed approach in describing nonlinear complex phenomena. © 2008 IEEE.

关键词： Trees (mathematics)

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Annual business and news:: Beginning the 31st year of the Journal of Guidance, control, and Dynamics

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JOURNAL OF GUIDANCE control AND DYNAMICS 2008年第1期31卷 1-1页

作者： Schmidt, George T. Aeronautics and Astronautics Massachusetts Institute of Technology (MIT) AIAA Institute of Electrical and Electronics Engineers Russian Federation Academy of Navigation and Motion Control Department of Mechanical and Aerospace Engineering and Engineering Mechanics University of Missouri-Rolla(UMR) Lockheed Electronics Company Center for Space Research University of Texas Austin United States Wright Laboratory Eglin Air Force Base UMR AIAA Guidance Navigation and Control Technical Committee American Automatic Control Council Lockheed Martin Aeronautics Company Palmdale CA United States C4ISR and Unmanned Air Vehicle (UAV) Programs for Air Vehicle Sciences and Systems Accreditation Board Engineering and Technology Inc./Aeronautical National Technical Committee on Guidance Navigation and Control Department of Mechanical and Aerospace Engineering University at Buffalo State University of New York (SUNY) AIAA Technical Committee on GN and C Air Vehicles Directorate Air Force Research Laboratory (AFRL) Wright-Patterson Air Force Base Space Access and Hypersonic Vehicle Guidance and Control Group Control Science Center of Excellence AFRL AIAA Technical Committee on Guidance Navigation and Control Department of Mechanical and Aeronautical Engineering University of California (UC) Davis United States Boeing Company Modernized Flight Control System for the Apache Longbow AIAA Institute of Electrical and Electronics Engineers AHS Jet Propulsion Laboratory California Institute of Technology Boeing Company Flight Sciences and Advanced Design Group Guidance Navigation and Control (GN and C) Systems Engineer Distributed Space Systems NASA Goddard Space Flight Center (GSFC) AIAA GN and C Technical Committee Department of Aerospace Engineering and Engineering Mechanics University of Texas Austin United States Institute of Navigation American Astronautical Society AIAA Guidance Navigation (GN and C) and Control Technical Committee Department of Aerospace Engineering Iowa State University Iowa

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A QFT/EEAS Design of Multivariable Robust Adaptive controllers

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IFAC Proceedings Volumes 2008年第2期41卷 6154-6159页

作者： O. Namaki-Shoushtari A. Khaki Sedigh B. Nadjar Araabi Department of Electrical Engineering K.N. Toosi University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

This paper presents a robust adaptive control design methodology for multi-input multi-output (MIMO) plants based on Quantitative Feedback Theory (QFT) and Externally Excited Adaptive System (EEAS), both of which are the novel ideas of Horowitz. Self Oscillating Adaptive Systems (SOAS) are proposed to mainly overcome the problem of large gain variations, which is important in certain applications. To further improve the SOAS design, the idea of EEAS was developed. Finally, combined QFT and EEAS proposed a robust adaptive controller for SISO uncertain plants. However, due to the complex design nature of the proposed combined methodology and the difficulty of an optimal design, this line of Horowitz's research was not followed further. In this paper, to overcome the above mentioned problems the design procedure is reformulated as a set of cost functions and constraints. Genetic Algorithms are then used to solve the optimal design. Also, QFT/EEAS design is extended to multivariable uncertain plants. Sufficient conditions are derived to assure the achievement of given off-diagonal performance. Then, the given main channel performance could be achieved by using SISO QFT/EEAS method. Simulation studies indicate the effective performance of the proposed QFT/EEAS MIMO design methodology. It is shown that the proposed approach can handle large plant parameter uncertainties with lower loop bandwidths.

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Reliability assessment of distribution system with distributed generation

Reliability assessment of distribution system with distribut...

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National Proceedings Power and Energy Conference (PECon)

作者： Pedram Jahangiri Mahmud Fotuhi-Firuzabad Department of Electrical Engineering Center of Excellence in Power System Control and Management Sharif University of Technology Tehran Iran

Reliability assessment is of primary importance in designing and planning distribution systems that operate in an economical manner with minimal interruption of customer loads. Distributed generation (DG) is expected to play an increasing role in emerging power systems because they use different type of resources and technologies to serve energy to power systems. DG is expected to improve the system reliability as its backup generation. Since DG units are subject to failures as all other generation units, the random behavior of these units must be taken into account in the analysis. Existence of DG units in a distribution system will effect on restoration time of load points. In this paper, an algorithm for assessing restoration time of load points for a radial distribution system with back up DG units is presented. The Impacts of DG units, their location, number of DG units in each location and their availability, on distribution system reliability are investigated using a real distribution network in Tehran utility/Iran.

关键词： Distributed control Power system reliability Power system economics Power generation economics Power system planning Standby generators Fuel economy Wind energy generation Circuit faults Power system analysis computing

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