Search results for: fuzzy numbers.
882 Robust H8 Fuzzy Control Design for Nonlinear Two-Time Scale System with Markovian Jumps based on LMI Approach
Authors: Wudhichai Assawinchaichote, Sing Kiong Nguang
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This paper examines the problem of designing a robust H8 state-feedback controller for a class of nonlinear two-time scale systems with Markovian Jumps described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain Markovian jump nonlinear two-time scale systems to have an H8 performance are derived. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard nonlinear two-time scale systems. A numerical example is provided to illustrate the design developed in this paper.
Keywords: TS fuzzy, Markovian jumps, LMI, two-time scale systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1445881 CFD Simulation of Non-Newtonian Fluid Flow in Arterial Stenoses with Surface Irregularities
Authors: R. Manimaran
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CFD simulations are carried out in arterial stenoses with 48 % areal occlusion. Non-newtonian fluid model is selected for the blood flow as the same problem has been solved before with Newtonian fluid model. Studies on flow resistance with the presence of surface irregularities are carried out. Investigations are also performed on the pressure drop at various Reynolds numbers. The present study revealed that the pressure drop across a stenosed artery is practically unaffected by surface irregularities at low Reynolds numbers, while flow features are observed and discussed at higher Reynolds numbers.Keywords: Blood flow, Roughness, Computational fluid dynamics, Bio fluid mechanics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4488880 Learning Algorithms for Fuzzy Inference Systems Composed of Double- and Single-Input Rule Modules
Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima
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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.Keywords: Box-Jenkins’s problem, Double-input rule module, Fuzzy inference model, Obstacle avoidance, Single-input rule module.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1948879 Advantages of Fuzzy Control Application in Fast and Sensitive Technological Processes
Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek
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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.Keywords: Control, fuzzy logic, sensitive system, technological proves.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1790878 Solution of Interval-valued Manufacturing Inventory Models With Shortages
Authors: Susovan Chakrabortty, Madhumangal Pal, Prasun Kumar Nayak
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A manufacturing inventory model with shortages with carrying cost, shortage cost, setup cost and demand quantity as imprecise numbers, instead of real numbers, namely interval number is considered here. First, a brief survey of the existing works on comparing and ranking any two interval numbers on the real line is presented. A common algorithm for the optimum production quantity (Economic lot-size) per cycle of a single product (so as to minimize the total average cost) is developed which works well on interval number optimization under consideration. Finally, the designed algorithm is illustrated with numerical example.Keywords: EOQ, Inventory, Interval Number, Demand, Production, Simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1635877 Robust H State-Feedback Control for Uncertain Fuzzy Markovian Jump Systems: LMI-Based Design
Authors: Wudhichai Assawinchaichote, Sing Kiong Nguang
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This paper investigates the problem of designing a robust state-feedback controller for a class of uncertain Markovian jump nonlinear systems that guarantees the L2-gain from an exogenous input to a regulated output is less than or equal to a prescribed value. First, we approximate this class of uncertain Markovian jump nonlinear systems by a class of uncertain Takagi-Sugeno fuzzy models with Markovian jumps. Then, based on an LMI approach, LMI-based sufficient conditions for the uncertain Markovian jump nonlinear systems to have an H performance are derived. An illustrative example is used to illustrate the effectiveness of the proposed design techniques.
Keywords: Robust H, Fuzzy Control, Markovian Jump Systems, LMI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1466876 A Multi-objective Fuzzy Optimization Method of Resource Input Based on Genetic Algorithm
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With the increasing complexity of engineering problems, the traditional, single-objective and deterministic optimization method can not meet people-s requirements. A multi-objective fuzzy optimization model of resource input is built for M chlor-alkali chemical eco-industrial park in this paper. First, the model is changed into the form that can be solved by genetic algorithm using fuzzy theory. And then, a fitness function is constructed for genetic algorithm. Finally, a numerical example is presented to show that the method compared with traditional single-objective optimization method is more practical and efficient.Keywords: Fitness function, genetic algorithm, multi-objectivefuzzy optimization, satisfaction degree membership function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1346875 Optimal Network of Secondary Warehouses for Production-Distribution Inventory Model
Authors: G. M. Arun Prasath, N. Arthi
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This work proposed a multi-objective mathematical programming approach to select the appropriate supply network elements. The multi-item multi-objective production-distribution inventory model is formulated with possible constraints under fuzzy environment. The unit cost has taken under fuzzy environment. The inventory model and warehouse location model has combined to formulate the production-distribution inventory model. Warehouse location is important in supply chain network. Particularly, if a company maintains more selling stores it cannot maintain individual secondary warehouse near to each selling store. Hence, maintaining the optimum number of secondary warehouses is important. Hence, the combined mathematical model is formulated to reduce the total expenditure of the organization by arranging the network of minimum number of secondary warehouses. Numerical example has been taken to illustrate the proposed model.Keywords: Fuzzy inventory model, warehouse location model, triangular fuzzy number, secondary warehouse, LINGO software.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1233874 Force Statistics and Wake Structure Mechanism of Flow around a Square Cylinder at Low Reynolds Numbers
Authors: Shams-Ul-Islam, Waqas Sarwar Abbasi, Hamid Rahman
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Numerical investigation of flow around a square cylinder are presented using the multi-relaxation-time lattice Boltzmann methods at different Reynolds numbers. A detail analysis are given in terms of time-trace analysis of drag and lift coefficients, power spectra analysis of lift coefficient, vorticity contours visualizations, streamlines and phase diagrams. A number of physical quantities mean drag coefficient, drag coefficient, Strouhal number and root-mean-square values of drag and lift coefficients are calculated and compared with the well resolved experimental data and numerical results available in open literature. The Reynolds numbers affected the physical quantities.
Keywords: Code validation, Force statistics, Multi-relaxation-time lattice Boltzmann method, Reynolds numbers, Square cylinder.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3114873 A New Fuzzy DSS/ES for Stock Portfolio Selection using Technical and Fundamental Approaches in Parallel
Authors: H. Zarei, M. H. Fazel Zarandi, M. Karbasian
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A Decision Support System/Expert System for stock portfolio selection presented where at first step, both technical and fundamental data used to estimate technical and fundamental return and risk (1st phase); Then, the estimated values are aggregated with the investor preferences (2nd phase) to produce convenient stock portfolio. In the 1st phase, there are two expert systems, each of which is responsible for technical or fundamental estimation. In the technical expert system, for each stock, twenty seven candidates are identified and with using rough sets-based clustering method (RC) the effective variables have been selected. Next, for each stock two fuzzy rulebases are developed with fuzzy C-Mean method and Takai-Sugeno- Kang (TSK) approach; one for return estimation and the other for risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation method. In parallel, for fundamental expert systems, fuzzy rule-bases have been identified in the form of “IF-THEN" rules through brainstorming with the stock market experts and the input data have been derived from financial statements; as a result two fuzzy rule-bases have been generated for all the stocks, one for return and the other for risk. In the 2nd phase, user preferences represented by four criteria and are obtained by questionnaire. Using an expert system, four estimated values of return and risk have been aggregated with the respective values of user preference. At last, a fuzzy rule base having four rules, treats these values and produce a ranking score for each stock which will lead to a satisfactory portfolio for the user. The stocks of six manufacturing companies and the period of 2003-2006 selected for data gathering.Keywords: Stock Portfolio Selection, Fuzzy Rule-Base ExpertSystems, Financial Decision Support Systems, Technical Analysis, Fundamental Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1834872 H∞ Fuzzy Integral Power Control for DFIG Wind Energy System
Authors: N. Chayaopas, W. Assawinchaichote
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In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.Keywords: H∞ fuzzy integral control, linear matrix inequality, wind energy system, doubly fed induction generator (DFIG).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1142871 Control of Underactuated Biped Robots Using Event Based Fuzzy Partial Feedback Linearization
Authors: Omid Heydarnia, Akbar Allahverdizadeh, Behnam Dadashzadeh, M. R. Sayyed Noorani
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Underactuated biped robots control is one of the interesting topics in robotics. The main difficulties are its highly nonlinear dynamics, open-loop instability, and discrete event at the end of the gait. One of the methods to control underactuated systems is the partial feedback linearization, but it is not robust against uncertainties and disturbances that restrict its performance to control biped walking and running. In this paper, fuzzy partial feedback linearization is presented to overcome its drawback. Numerical simulations verify the effectiveness of the proposed method to generate stable and robust biped walking and running gaits.Keywords: Underactuated system, biped robot, fuzzy control, partial feedback linearization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1763870 Tipover Stability Enhancement of Wheeled Mobile Manipulators Using an Adaptive Neuro- Fuzzy Inference Controller System
Authors: A. Ghaffari, A. Meghdari, D. Naderi, S. Eslami
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In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector and the vehicle. The controller creates proper configurations for the manipulator to prevent the robot from being overturned. The optimal configuration and thus the most favorable control are obtained through soft computing approaches including a combination of genetic algorithm, neural networks, and fuzzy logic. The proposed algorithm, in this paper, is that a look-up table is designed by employing the obtained values from the genetic algorithm in order to minimize the performance index and by using this data base, rule bases are designed for the ANFIS controller and will be exerted on the actuators to enhance the tipover stability of the mobile manipulator. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm.Keywords: Mobile Manipulator, Tipover Stability Enhancement, Adaptive Neuro-Fuzzy Inference Controller System, Soft Computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1955869 A New Fuzzy Decision Support Method for Analysis of Economic Factors of Turkey's Construction Industry
Authors: R. Tur, A. Yardımcı
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Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.
Keywords: Fuzzy logic, decision support systems, construction industry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1624868 Fuzzy Tuned PID Controller with D-Q-O Reference Frame Technique Based Active Power Filter
Authors: Kavala Kiran Kumar, R. Govardhana Rao
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Active power filter continues to be a powerful tool to control harmonics in power systems thereby enhancing the power quality. This paper presents a fuzzy tuned PID controller based shunt active filter to diminish the harmonics caused by non linear loads like thyristor bridge rectifiers and imbalanced loads. Here Fuzzy controller provides the tuning of PID, based on firing of thyristor bridge rectifiers and variations in input rms current. The shunt APF system is implemented with three phase current controlled Voltage Source Inverter (VSI) and is connected at the point of common coupling for compensating the current harmonics by injecting equal but opposite filter currents. These controllers are capable of controlling dc-side capacitor voltage and estimating reference currents. Hysteresis Current Controller (HCC) is used to generate switching signals for the voltage source inverter. Simulation studies are carried out with non linear loads like thyristor bridge rectifier along with unbalanced loads and the results proved that the APF along with fuzzy tuned PID controller work flawlessly for different firing angles of non linear load.
Keywords: Active power filters (APF), Fuzzy logic controller (FLC), Hysteresis current controller (HCC), PID, Total harmonic Distortion (THD), Voltage source inverter (VSI).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2522867 Adaptive Fuzzy Control on EDF Scheduling
Authors: Xiangbin Zhu
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EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.
Keywords: Fuzzy control, real-time systems, EDF, misdeadline ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1483866 Improvements in Edge Detection Based on Mathematical Morphology and Wavelet Transform using Fuzzy Rules
Authors: Masrour Dowlatabadi, Jalil Shirazi
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In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical morphology and wavelet transform is proposed. The combined method is proposed to overcome the limitation of wavelet based edge detection and mathematical morphology based edge detection in noisy images. Experimental results show superiority of the proposed method, as compared to the traditional Prewitt, wavelet based and morphology based edge detection methods. The proposed method is an effective edge detection method for noisy image and keeps clear and continuous edges.Keywords: Edge detection, Wavelet transform, Mathematical morphology, Fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2394865 A Spiral Dynamic Optimised Hybrid Fuzzy Logic Controller for a Unicycle Mobile Robot on Irregular Terrains
Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Talal H. Alzanki
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This paper presents a hybrid fuzzy logic control strategy for a unicycle trajectory following robot on irregular terrains. In literature, researchers have presented the design of path tracking controllers of mobile robots on non-frictional surface. In this work, the robot is simulated to drive on irregular terrains with contrasting frictional profiles of peat and rough gravel. A hybrid fuzzy logic controller is utilised to stabilise and drive the robot precisely with the predefined trajectory and overcome the frictional impact. The controller gains and scaling factors were optimised using spiral dynamics optimisation algorithm to minimise the mean square error of the linear and angular velocities of the unicycle robot. The robot was simulated on various frictional surfaces and terrains and the controller was able to stabilise the robot with a superior performance that is shown via simulation results.
Keywords: Fuzzy logic control, mobile robot, trajectory tracking, spiral dynamic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1725864 Life Estimation of Induction Motor Insulation under Non-Sinusoidal Voltage and Current Waveforms Using Fuzzy Logic
Authors: Triloksingh G. Arora, Mohan V. Aware, Dhananjay R. Tutakne
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Thyristor based firing angle controlled voltage regulators are extensively used for speed control of single phase induction motors. This leads to power saving but the applied voltage and current waveforms become non-sinusoidal. These non-sinusoidal waveforms increase voltage and thermal stresses which result into accelerated insulation aging, thus reducing the motor life. Life models that allow predicting the capability of insulation under such multi-stress situations tend to be very complex and somewhat impractical. This paper presents the fuzzy logic application to investigate the synergic effect of voltage and thermal stresses on intrinsic aging of induction motor insulation. A fuzzy expert system is developed to estimate the life of induction motor insulation under multiple stresses. Three insulation degradation parameters, viz. peak modification factor, wave shape modification factor and thermal loss are experimentally obtained for different firing angles. Fuzzy expert system consists of fuzzyfication of the insulation degradation parameters, algorithms based on inverse power law to estimate the life and defuzzyficaton process to output the life. An electro-thermal life model is developed from the results of fuzzy expert system. This fuzzy logic based electro-thermal life model can be used for life estimation of induction motors operated with non-sinusoidal voltage and current waveforms.
Keywords: Aging, Dielectric losses, Insulation and Life Estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3041863 Determination the Curve Number Catchment by Using GIS and Remote Sensing
Authors: Abouzar Nasiri, Hamid Alipur
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In recent years, geographic information systems (GIS) and remote sensing using has increased to estimate runoff catchment. In this research, runoff curve number maps for captive catchment of Tehran by helping GIS and also remote sensing which based on factors such as vegetation, lands using, group of soil hydrology and hydrological conditions were obtained. Runoff curve numbers map was obtained by combining these maps in ARC GIS and SCS table. To evaluate the accuracy of the results, the maximum flow rate of flood which was obtained from curve numbers, was compared with the measured maximum flood rate at the watershed outlet and correctness of curve numbers were approved.
Keywords: Curve number, GIS, Remote sensing, Runoff.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4965862 Design of Orientation-Free Handler and Fuzzy Controller for Wire-Driven Heavy Object Lifting System
Authors: Bo-Wei Song, Yun-Jung Lee
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This paper presents an intention interface and controller for a wire-driven heavy object lifting system that assists the operator with moving a heavy object. The handler is designed to allow a comfortable working posture for the operator. Plus, as a human assistive system, the operator is involved in the control loop, where a fuzzy control system is used to consider the human control characteristics. The effectiveness and performance of the proposed system are proved by experiments.
Keywords: Fuzzy controller, Handler design, Heavy object lifting system, Human-assistive device, Human-in-the-loop system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1646861 Self-Tuning Fuzzy Control of Seat Vibrations of Active Quarter Car Model
Authors: Devdutt
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An active quarter car model with three degrees of freedom is presented for vibration reduction of passenger seat. The designed Fuzzy Logic Controller (FLC) and Self-Tuning Fuzzy Logic Controller (STFLC) are applied in seat suspension. Vibration control performance of active and passive quarter car systems are determined using simulation work. Simulation results in terms of passenger seat acceleration and displacement responses are compared for controlled and uncontrolled cases. Simulation results showed the improved results of both FLC and STFLC controllers in improving passenger ride comfort compared to uncontrolled case. Furthermore, the best performance in simulation studies is achieved by STFLC controlled suspension system compared to FLC controlled and uncontrolled cases.
Keywords: Active suspension system, quarter car model, passenger ride comfort, self-tuning fuzzy logic controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 874860 Harmonics Elimination in Multilevel Inverter Using Linear Fuzzy Regression
Authors: A. K. Al-Othman, H. A. Al-Mekhaizim
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Multilevel inverters supplied from equal and constant dc sources almost don-t exist in practical applications. The variation of the dc sources affects the values of the switching angles required for each specific harmonic profile, as well as increases the difficulty of the harmonic elimination-s equations. This paper presents an extremely fast optimal solution of harmonic elimination of multilevel inverters with non-equal dc sources using Tanaka's fuzzy linear regression formulation. A set of mathematical equations describing the general output waveform of the multilevel inverter with nonequal dc sources is formulated. Fuzzy linear regression is then employed to compute the optimal solution set of switching angles.Keywords: Multilevel converters, harmonics, pulse widthmodulation (PWM), optimal control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1788859 A Comparison of Grey Model and Fuzzy Predictive Model for Time Series
Authors: A. I. Dounis, P. Tiropanis, D. Tseles, G. Nikolaou, G. P. Syrcos
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The prediction of meteorological parameters at a meteorological station is an interesting and open problem. A firstorder linear dynamic model GM(1,1) is the main component of the grey system theory. The grey model requires only a few previous data points in order to make a real-time forecast. In this paper, we consider the daily average ambient temperature as a time series and the grey model GM(1,1) applied to local prediction (short-term prediction) of the temperature. In the same case study we use a fuzzy predictive model for global prediction. We conclude the paper with a comparison between local and global prediction schemes.Keywords: Fuzzy predictive model, grey model, local andglobal prediction, meteorological forecasting, time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2143858 Learning Classifier Systems Approach for Automated Discovery of Crisp and Fuzzy Hierarchical Production Rules
Authors: Suraiya Jabin, Kamal K. Bharadwaj
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This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1446857 Exponential Stability of Uncertain Takagi-Sugeno Fuzzy Hopfield Neural Networks with Time Delays
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In this paper, based on linear matrix inequality (LMI), by using Lyapunov functional theory, the exponential stability criterion is obtained for a class of uncertain Takagi-Sugeno fuzzy Hopfield neural networks (TSFHNNs) with time delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. Finally, an example is given to illustrate our results by using MATLAB LMI toolbox.
Keywords: Hopfield neural network, linear matrix inequality, exponential stability, time delay, T-S fuzzy model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1498856 Analyzing CPFR Supporting Factors with Fuzzy Cognitive Map Approach
Authors: G. Büyüközkan , O. Feyzioglu, Z. Vardaloglu
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Collaborative planning, forecasting and replenishment (CPFR) coordinates the various supply chain management activities including production and purchase planning, demand forecasting and inventory replenishment between supply chain trading partners. This study proposes a systematic way of analyzing CPFR supporting factors using fuzzy cognitive map (FCM) approach. FCMs have proven particularly useful for solving problems in which a number of decision variables and uncontrollable variables are causally interrelated. Hence the FCMs of CPFR are created to show the relationships between the factors that influence on effective implementation of CPFR in the supply chain.Keywords: Collaborative planning, forecasting and replenishment, fuzzy cognitive map, information sharing, decision synchronization, incentive alignment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1523855 A Fuzzy Mixed Integer Multi-Scenario Portfolio Optimization Model
Authors: M. S. Osman, A. A. Tharwat, I. A. El-Khodary, A. G. Chalabi
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In this paper, we propose a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz-s M-V model we developed a Fuzzy Mixed Integer Multi-Objective Nonlinear Programming Problem (FMIMONLP) to maximize the investors- future gains on equity markets, reach the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.
Keywords: Equity Markets, Future Scenarios, PortfolioSelection, Multiple Criteria Fuzzy Optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1964854 Processing the Medical Sensors Signals Using Fuzzy Inference System
Authors: S. Bouharati, I. Bouharati, C. Benzidane, F. Alleg, M. Belmahdi
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Sensors possess several properties of physical measures. Whether devices that convert a sensed signal into an electrical signal, chemical sensors and biosensors, thus all these sensors can be considered as an interface between the physical and electrical equipment. The problem is the analysis of the multitudes of saved settings as input variables. However, they do not all have the same level of influence on the outputs. In order to identify the most sensitive parameters, those that can guide users in gathering information on the ground and in the process of model calibration and sensitivity analysis for the effect of each change made. Mathematical models used for processing become very complex. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available signals information from sensors. Moreover, the system allows the study of the influence of the various factors that take part in the decision system. Since its inception fuzzy set theory has been regarded as a formalism suitable to deal with the imprecision intrinsic to many problems. At the same time, fuzzy sets allow to use symbolic models. In this study an example was applied for resolving variety of physiological parameters that define human health state. The application system was done for medical diagnosis help. The inputs are the signals expressed the cardiovascular system parameters, blood pressure, Respiratory system paramsystem was done, it will be able to predict the state of patient according any input values.Keywords: Sensors, Sensivity, fuzzy logic, analysis, physiological parameters, medical diagnosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1956853 Network Anomaly Detection using Soft Computing
Authors: Surat Srinoy, Werasak Kurutach, Witcha Chimphlee, Siriporn Chimphlee
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One main drawback of intrusion detection system is the inability of detecting new attacks which do not have known signatures. In this paper we discuss an intrusion detection method that proposes independent component analysis (ICA) based feature selection heuristics and using rough fuzzy for clustering data. ICA is to separate these independent components (ICs) from the monitored variables. Rough set has to decrease the amount of data and get rid of redundancy and Fuzzy methods allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining- (KDDCup 1999) dataset.Keywords: Network security, intrusion detection, rough set, ICA, anomaly detection, independent component analysis, rough fuzzy .
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1945