Search results for: Fuzzy logic system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9011

Search results for: Fuzzy logic system

8651 H∞ Takagi-Sugeno Fuzzy State-Derivative Feedback Control Design for Nonlinear Dynamic Systems

Authors: N. Kaewpraek, W. Assawinchaichote

Abstract:

This paper considers an H TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an HTS fuzzy state-derivative feedback control law which guarantees L2-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and H performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller.

Keywords: H∞ fuzzy control, LMI, Takagi-Sugano (TS) fuzzy model, nonlinear dynamic systems, state-derivative feedback.

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8650 A Comparison of Fuzzy Clustering Algorithms to Cluster Web Messages

Authors: Sara El Manar El Bouanani, Ismail Kassou

Abstract:

Our objective in this paper is to propose an approach capable of clustering web messages. The clustering is carried out by assigning, with a certain probability, texts written by the same web user to the same cluster based on Stylometric features and using fuzzy clustering algorithms. Focus in the present work is on comparing the most popular algorithms in fuzzy clustering theory namely, Fuzzy C-means, Possibilistic C-means and Fuzzy Possibilistic C-Means.

Keywords: Authorship detection, fuzzy clustering, profiling, stylometric features.

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8649 A Multi-Agent Intelligent System for Monitoring Health Conditions of Elderly People

Authors: Ayman M. Mansour

Abstract:

In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: Fuzzy Logic, Inference system, Monitoring system, Multi-agent system.

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8648 Fuzzy Estimation of Parameters in Statistical Models

Authors: A. Falsafain, S. M. Taheri, M. Mashinchi

Abstract:

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameters of two Normal distributions, as well as the parameters of the Exponential and Poisson distributions.

Keywords: Confidence interval. Fuzzy number. Fuzzy estimation.

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8647 A Fuzzy Mathematical Model for Order Acceptance and Scheduling Problem

Authors: E. Koyuncu

Abstract:

The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: Fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling.

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8646 Evolution of Fuzzy Neural Networks Using an Evolution Strategy with Fuzzy Genotype Values

Authors: Hidehiko Okada

Abstract:

Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.

Keywords: Evolutionary algorithm, evolution strategy, fuzzy number, feedforward neural network, neuroevolution.

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8645 Design of Power System Stabilizer with Neuro-Fuzzy UPFC Controller

Authors: U. Ramesh Babu, V. Vijay Kumar Reddy, S. Tara Kalyani

Abstract:

The growth in the demand of electrical energy is leading to load on the Power system which increases the occurrence of frequent oscillations in the system. The reason for the oscillations is due to the lack of damping torque which is required to dominate the disturbances of Power system. By using FACT devices, such as Unified Power Flow Controller (UPFC) can control power flow, reduce sub-synchronous resonances and increase transient stability. Hence, UPFC is used to damp the oscillations occurred in Power system. This research focuses on adapting the neuro fuzzy controller for the UPFC design by connecting the infinite bus (SMIB - Single machine Infinite Bus) to a linearized model of synchronous machine (Heffron-Phillips) in the power system. This model gains the capability to improve the transient stability and to damp the oscillations of the system.

Keywords: Power System, UPFC, (ANFIS) Adaptive Neuro Fuzzy Inference System, transient, Low frequency oscillations.

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8644 Application of Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA

Authors: Eleftherios Giovanis

Abstract:

In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms significant the Logit and Probit models in the out-of sample period. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.

Keywords: ANFIS, discrete choice models, financial crisis, USeconomy

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8643 Discovery of Fuzzy Censored Production Rules from Large Set of Discovered Fuzzy if then Rules

Authors: Tamanna Siddiqui, M. Afshar Alam

Abstract:

Censored Production Rule is an extension of standard production rule, which is concerned with problems of reasoning with incomplete information, subject to resource constraints and problem of reasoning efficiently with exceptions. A CPR has a form: IF A (Condition) THEN B (Action) UNLESS C (Censor), Where C is the exception condition. Fuzzy CPR are obtained by augmenting ordinary fuzzy production rule “If X is A then Y is B with an exception condition and are written in the form “If X is A then Y is B Unless Z is C. Such rules are employed in situation in which the fuzzy conditional statement “If X is A then Y is B" holds frequently and the exception condition “Z is C" holds rarely. Thus “If X is A then Y is B" part of the fuzzy CPR express important information while the unless part acts only as a switch that changes the polarity of “Y is B" to “Y is not B" when the assertion “Z is C" holds. The proposed approach is an attempt to discover fuzzy censored production rules from set of discovered fuzzy if then rules in the form: A(X) ÔçÆ B(Y) || C(Z).

Keywords: Uncertainty Quantification, Fuzzy if then rules, Fuzzy Censored Production Rules, Learning algorithm.

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8642 Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

Abstract:

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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8641 Stabilization of the Lorenz Chaotic Equations by Fuzzy Controller

Authors: Behrooz Rezaie, Zahra Rahmani Cherati, Mohammad Reza Jahed Motlagh, Mohammad Farrokhi

Abstract:

In this paper, a fuzzy controller is designed for stabilization of the Lorenz chaotic equations. A simple Mamdani inference method is used for this purpose. This method is very simple and applicable for complex chaotic systems and it can be implemented easily. The stability of close loop system is investigated by the Lyapunov stabilization criterion. A Lyapunov function is introduced and the global stability is proven. Finally, the effectiveness of this method is illustrated by simulation results and it is shown that the performance of the system is improved.

Keywords: Chaotic system, Fuzzy control, Lorenz equation.

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8640 Qualitative Modelling for Ferromagnetic Hysteresis Cycle

Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira

Abstract:

In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.

Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.

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8639 Fuzzy T-Neighborhood Groups Acting on Sets

Authors: Hazem. A. Khorshed, Mostafa A. El Gendy, Amer. Abd El-Razik

Abstract:

In this paper, The T-G-action topology on a set acted on by a fuzzy T-neighborhood (T-neighborhood, for short) group is defined as a final T-neighborhood topology with respect to a set of maps. We mainly prove that this topology is a T-regular Tneighborhood topology.

Keywords: Fuzzy set, Fuzzy topology, Triangular norm, Separation axioms.

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8638 Measuring Banks’ Antifragility via Fuzzy Logic

Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

Abstract:

Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Keywords: Complex adaptive systems, X-events, risk management, antifragility, banking antifragility index, triangular fuzzy number.

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8637 Representation of Coloured Petri Net in Abductive Logic Programming (CPN-LP) and Its Application in Modeling an Intelligent Agent

Authors: T. H. Fung

Abstract:

Coloured Petri net (CPN) has been widely adopted in various areas in Computer Science, including protocol specification, performance evaluation, distributed systems and coordination in multi-agent systems. It provides a graphical representation of a system and has a strong mathematical foundation for proving various properties. This paper proposes a novel representation of a coloured Petri net using an extension of logic programming called abductive logic programming (ALP), which is purely based on classical logic. Under such a representation, an implementation of a CPN could be directly obtained, in which every inference step could be treated as a kind of equivalence preserved transformation. We would describe how to implement a CPN under such a representation using common meta-programming techniques in Prolog. We call our framework CPN-LP and illustrate its applications in modeling an intelligent agent.

Keywords: Abduction, coloured petri net, intelligent agent, logic programming.

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8636 More on Gaussian Quadratures for Fuzzy Functions

Authors: Shu-Xin Miao

Abstract:

In this paper, the Gaussian type quadrature rules for fuzzy functions are discussed. The errors representation and convergence theorems are given. Moreover, four kinds of Gaussian type quadrature rules with error terms for approximate of fuzzy integrals are presented. The present paper complements the theoretical results of the paper by T. Allahviranloo and M. Otadi [T. Allahviranloo, M. Otadi, Gaussian quadratures for approximate of fuzzy integrals, Applied Mathematics and Computation 170 (2005) 874-885]. The obtained results are illustrated by solving some numerical examples.

Keywords: Guassian quadrature rules, fuzzy number, fuzzy integral, fuzzy solution.

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8635 H∞ Fuzzy Integral Power Control for DFIG Wind Energy System

Authors: N. Chayaopas, W. Assawinchaichote

Abstract:

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).

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8634 Characterizations of Ordered Semigroups by (∈,∈ ∨q)-Fuzzy Ideals

Authors: Jian Tang

Abstract:

Let S be an ordered semigroup. In this paper we first introduce the concepts of (∈,∈ ∨q)-fuzzy ideals, (∈,∈ ∨q)-fuzzy bi-ideals and (∈,∈ ∨q)-fuzzy generalized bi-ideals of an ordered semigroup S, and investigate their related properties. Furthermore, we also define the upper and lower parts of fuzzy subsets of an ordered semigroup S, and investigate the properties of (∈,∈ ∨q)-fuzzy ideals of S. Finally, characterizations of regular ordered semigroups and intra-regular ordered semigroups by means of the lower part of (∈ ,∈ ∨q)-fuzzy left ideals, (∈,∈ ∨q)-fuzzy right ideals and (∈,∈ ∨q)- fuzzy (generalized) bi-ideals are given.

Keywords: Ordered semigroup, regular ordered semigroup, intraregular ordered semigroup, (∈, ∈ ∨q)-fuzzy left (right) ideal of an ordered semigroup, (∈, ∈ ∨q)-fuzzy (generalized) bi-ideal of an ordered semigroup.

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8633 Fuzzy Hyperbolization Image Enhancement and Artificial Neural Network for Anomaly Detection

Authors: Sri Hartati, 1Agus Harjoko, Brad G. Nickerson

Abstract:

A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.

Keywords: Image processing, artificial neural network, anomaly detection.

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8632 Sensorless PM Motor with Multi Degree of Freedom Fuzzy Control

Authors: Faeka M. H. Khater, Farouk I. Ahmed, Mohamed I. Abu El- Sebah

Abstract:

This paper introduces application of multi degree of freedom fuzzy(MDOFF) controller in permanent magnet (PM)drive system. The drive system model is developed for FO control. Simulation of the system is carried out to predict the performance at NL and under load,. The results indicate that application of MDOFF controller is effective for sensorless PM drive system.

Keywords: Sensorless FO controller, PM drives system, MDOFF controller.

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8631 Improvements in Edge Detection Based on Mathematical Morphology and Wavelet Transform using Fuzzy Rules

Authors: Masrour Dowlatabadi, Jalil Shirazi

Abstract:

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.

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8630 A Neuro-Fuzzy Approach Based Voting Scheme for Fault Tolerant Systems Using Artificial Bee Colony Training

Authors: D. Uma Devi, P. Seetha Ramaiah

Abstract:

Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.

Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)

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8629 Prioritization Method in the Fuzzy Analytic Network Process by Fuzzy Preferences Programming Method

Authors: Tarifa S. Almulhim, Ludmil Mikhailov, Dong-Ling Xu

Abstract:

In this paper, a method for deriving a group priority vector in the Fuzzy Analytic Network Process (FANP) is proposed. By introducing importance weights of multiple decision makers (DMs) based on their experiences, the Fuzzy Preferences Programming Method (FPP) is extended to a fuzzy group prioritization problem in the FANP. Additionally, fuzzy pair-wise comparison judgments are presented rather than exact numerical assessments in order to model the uncertainty and imprecision in the DMs- judgments and then transform the fuzzy group prioritization problem into a fuzzy non-linear programming optimization problem which maximize the group satisfaction. Unlike the known fuzzy prioritization techniques, the new method proposed in this paper can easily derive crisp weights from incomplete and inconsistency fuzzy set of comparison judgments and does not require additional aggregation producers. Detailed numerical examples are used to illustrate the implement of our approach and compare with the latest fuzzy prioritization method.

Keywords: Fuzzy Analytic Network Process (FANP), Fuzzy Non-linear Programming, Fuzzy Preferences Programming Method (FPP), Multiple Criteria Decision-Making (MCDM), Triangular Fuzzy Number.

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8628 Fuzzy Decision Making via Multiple Attribute

Authors: Behnaz Zohouri, Mahdi Zowghiand, Mohsen haghighi

Abstract:

In this paper, a method for decision making in fuzzy environment is presented.A new subjective and objective integrated approach is introduced that used to assign weight attributes in fuzzy multiple attribute decision making (FMADM) problems and alternatives and fmally ranked by proposed method.

Keywords: Multiple Attribute Decision Making, Triangular fuzzy numbers, ranking index, Fuzzy Entropy.

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8627 Isomorphism on Fuzzy Graphs

Authors: A.Nagoor Gani, J.Malarvizhi

Abstract:

In this paper, the order, size and degree of the nodes of the isomorphic fuzzy graphs are discussed. Isomorphism between fuzzy graphs is proved to be an equivalence relation. Some properties of self complementary and self weak complementary fuzzy graphs are discussed.

Keywords: complementary fuzzy graphs, co-weak isomorphism, equivalence relation, fuzzy relation, weak isomorphism.

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8626 Control Strategy for Two-Mode Hybrid Electric Vehicle by Using Fuzzy Controller

Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: Hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control.

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8625 An Intelligent Combined Method Based on Power Spectral Density, Decision Trees and Fuzzy Logic for Hydraulic Pumps Fault Diagnosis

Authors: Kaveh Mollazade, Hojat Ahmadi, Mahmoud Omid, Reza Alimardani

Abstract:

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. The aim of this work is to investigate the effectiveness of a new fault diagnosis method based on power spectral density (PSD) of vibration signals in combination with decision trees and fuzzy inference system (FIS). To this end, a series of studies was conducted on an external gear hydraulic pump. After a test under normal condition, a number of different machine defect conditions were introduced for three working levels of pump speed (1000, 1500, and 2000 rpm), corresponding to (i) Journal-bearing with inner face wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii) Journal-bearing with inner face wear plus Gear with tooth face wear (B&GW). The features of PSD values of vibration signal were extracted using descriptive statistical parameters. J48 algorithm is used as a feature selection procedure to select pertinent features from data set. The output of J48 algorithm was employed to produce the crisp if-then rule and membership function sets. The structure of FIS classifier was then defined based on the crisp sets. In order to evaluate the proposed PSD-J48-FIS model, the data sets obtained from vibration signals of the pump were used. Results showed that the total classification accuracy for 1000, 1500, and 2000 rpm conditions were 96.42%, 100%, and 96.42% respectively. The results indicate that the combined PSD-J48-FIS model has the potential for fault diagnosis of hydraulic pumps.

Keywords: Power Spectral Density, Machine ConditionMonitoring, Hydraulic Pump, Fuzzy Logic.

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8624 Hybridized Technique to Analyze Workstress Related Data via the StressCafé

Authors: Anusua Ghosh, Andrew Nafalski, Jeffery Tweedale, Maureen Dollard

Abstract:

This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach) has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a superior hybrid solution. Recent researches have shown that there is a need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.

Keywords: Fuzzy logic, intelligent agent, multi-agent systems, neural network, workplace stress.

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8623 Supervisory Control for Induction Machine with a Modified Star/Delta Switch in Fluid Transportation

Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain

Abstract:

This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.

Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.

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8622 Preconditioned Jacobi Method for Fuzzy Linear Systems

Authors: Lina Yan, Shiheng Wang, Ke Wang

Abstract:

A preconditioned Jacobi (PJ) method is provided for solving fuzzy linear systems whose coefficient matrices are crisp Mmatrices and the right-hand side columns are arbitrary fuzzy number vectors. The iterative algorithm is given for the preconditioned Jacobi method. The convergence is analyzed with convergence theorems. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.

Keywords: preconditioning, M-matrix, Jacobi method, fuzzy linear system (FLS).

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