Search results for: Generalized Fuzzy Soft set

Authors: Rada Somkhuean, Suparat Niwitpong, Sa-aat Niwitpong

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This paper presents the generalized p-values for testing the Behrens-Fisher problem when a ratio of variance is known. We also derive a closed form expression of the upper bound of the proposed generalized p-value.

Keywords: Generalized p-value, hypothesis testing, ratio of variances, upper bound.

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Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.

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Authors: Ezzatallah Baloui Jamkhaneh, Bahram Sadeghpour-Gildeh, Gholamhossein Yari

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This purpose of this paper is to present the acceptance single sampling plan when the fraction of nonconforming items is a fuzzy number and being modeled based on the fuzzy Poisson distribution. We have shown that the operating characteristic (oc) curves of the plan is like a band having a high and low bounds whose width depends on the ambiguity proportion parameter in the lot when that sample size and acceptance numbers is fixed. Finally we completed discuss opinion by a numerical example. And then we compared the oc bands of using of binomial with the oc bands of using of Poisson distribution.

Keywords: Statistical quality control, acceptance single sampling, fuzzy number.

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Authors: Wei-Hsuan Lee, Chien-Hua Wang, Chin-Tzong Pang

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This paper applies fuzzy set theory to evaluate the service quality of online auction. Service quality is a composition of various criteria. Among them many intangible attributes are difficult to measure. This characteristic introduces the obstacles for respondent in replying to the survey. So as to overcome this problem, we invite fuzzy set theory into the measurement of performance. By using AHP in obtaining criteria and TOPSIS in ranking, we found the most concerned dimension of service quality is Transaction Safety Mechanism and the least is Charge Item. Regarding to the most concerned attributes are information security, accuracy and information.

Keywords: AHP, Fuzzy set theory, TOPSIS, Online auction, Servicequality

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Authors: R. Goede, E. Taylor

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This paper demonstrates how the soft systems methodology can be used to improve the delivery of a module in data warehousing for fourth year information technology students. Graduates in information technology needs to have academic skills but also needs to have good practical skills to meet the skills requirements of the information technology industry. In developing and improving current data warehousing education modules one has to find a balance in meeting the expectations of various role players such as the students themselves, industry and academia. The soft systems methodology, developed by Peter Checkland, provides a methodology for facilitating problem understanding from different world views. In this paper it is demonstrated how the soft systems methodology can be used to plan the improvement of data warehousing education for fourth year information technology students.

Keywords: Data warehousing, education, soft systems methodology, stakeholders, systems thinking.

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Authors: Yuanjie Zheng, Jie Yang, Yue Zhou

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In this paper, we propose an approach of unsupervised segmentation with fuzzy connectedness. Valid seeds are first specified by an unsupervised method based on scale space theory. A region is then extracted for each seed with a relative object extraction method of fuzzy connectedness. Afterwards, regions are merged according to the values between them of an introduced measure. Some theorems and propositions are also provided to show the reasonableness of the measure for doing mergence. Experiment results on a synthetic image, a color image and a large amount of MR images of our method are reported.

Keywords: Image segmentation, unsupervised imagesegmentation, fuzzy connectedness, scale space.

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Authors: Joabe Silva, Ginalber Serra

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This paper proposes the analysis and design of robust fuzzy control to Stochastic Parametrics Uncertaint Linear systems. This system type to be controlled is partitioned into several linear sub-models, in terms of transfer function, forming a convex polytope, similar to LPV (Linear Parameters Varying) system. Once defined the linear sub-models of the plant, these are organized into fuzzy Takagi- Sugeno (TS) structure. From the Parallel Distributed Compensation (PDC) strategy, a mathematical formulation is defined in the frequency domain, based on the gain and phase margins specifications, to obtain robust PI sub-controllers in accordance to the Takagi- Sugeno fuzzy model of the plant. The main results of the paper are based on the robust stability conditions with the proposal of one Axiom and two Theorems.

Keywords: Fuzzy Systems; Robust Stability, Stochastic Control, Stochastic Process

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Authors: Chien-Hua Wang, Chin-Tzong Pang

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In data mining, the association rules are used to search for the relations of items of the transactions database. Following the data is collected and stored, it can find rules of value through association rules, and assist manager to proceed marketing strategy and plan market framework. In this paper, we attempt fuzzy partition methods and decide membership function of quantitative values of each transaction item. Also, by managers we can reflect the importance of items as linguistic terms, which are transformed as fuzzy sets of weights. Next, fuzzy weighted frequent pattern growth (FWFP-Growth) is used to complete the process of data mining. The method above is expected to improve Apriori algorithm for its better efficiency of the whole association rules. An example is given to clearly illustrate the proposed approach.

Keywords: Association Rule, Fuzzy Partition Methods, FWFP-Growth, Apiroir algorithm

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Authors: K. Prasertwong, N. Mithulananthan

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This paper investigates and compares performance of various conventional and fuzzy logic based controllers at generator locations for oscillation damping. Performance of combination of conventional and fuzzy logic based controllers also studied by comparing overshoot on the active power deviation response for a small disturbance and damping ratio of the critical mode. Fuzzy logic based controllers can not be modeled in the state space form to get the eigenvalues and corresponding damping ratios of various modes of generators and controllers. Hence, a new method based on tracing envelop of time domain waveform is also presented and used in the paper for comparing performance of controllers. The paper also shows that if the fuzzy based controllers designed separately combining them could not lead to a better performance.

Keywords: Automatic voltage regulator, damping ratio, fuzzylogic controller, power system stabilizer.

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Authors: Sheroz Khan, I. Adam, A. H. M. Zahirul Alam, Mohd Rafiqul Islam, Othman O. Khalifa

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This paper attempts to model and design a simple fuzzy logic controller with Variable Reference. The Variable Reference (VR) is featured as an adaptability element which is obtained from two known variables – desired system-input and actual system-output. A simple fuzzy rule-based technique is simulated to show how the actual system-input is gradually tuned in to a value that closely matches the desired input. The designed controller is implemented and verified on a simple heater which is controlled by PIC Microcontroller harnessed by a code developed in embedded C. The output response of the PIC-controlled heater is analyzed and compared to the performances by conventional fuzzy logic controllers. The novelty of this work lies in the fact that it gives better performance by using less number of rules compared to conventional fuzzy logic controllers.

Keywords: Fuzzy logic controller, Variable reference, Adaptability, Rule-based.

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

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Using neural network we try to model the unknown function f for given input-output data pairs. The connection strength of each neuron is updated through learning. Repeated simulations of crisp neural network produce different values of weight factors that are directly affected by the change of different parameters. We propose the idea that for each neuron in the network, we can obtain quasi-fuzzy weight sets (QFWS) using repeated simulation of the crisp neural network. Such type of fuzzy weight functions may be applied where we have multivariate crisp input that needs to be adjusted after iterative learning, like claim amount distribution analysis. As real data is subjected to noise and uncertainty, therefore, QFWS may be helpful in the simplification of such complex problems. Secondly, these QFWS provide good initial solution for training of fuzzy neural networks with reduced computational complexity.

Keywords: Crisp neural networks, fuzzy systems, extraction of logical rules, quasi-fuzzy numbers.

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Authors: R. Karbalaei, A. Ghaffari, R. Kazemi, S. H. Tabatabaei

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An integrated vehicle dynamics control system is developed in this paper by a combination of active front steering (AFS) and direct yaw-moment control (DYC) based on fuzzy logic control. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer (yaw rate controller) to keep the yaw rate in its desired value. The yaw rate error and its rate of change are applied to the upper controlling layer as inputs, where the direct yaw moment control signal and the steering angle correction of the front wheels are the outputs. In the lower layer (fuzzy integrator), a fuzzy logic controller is designed based on the working region of the lateral tire forces. Depending on the directions of the lateral forces at the front wheels, a switching function is activated to adjust the scaling factor of the fuzzy logic controller. Using a nonlinear seven degrees of freedom vehicle model, the simulation results illustrate considerable improvements which are achieved in vehicle handling through the integrated AFS/DYC control system in comparison with the individual AFS or DYC controllers.

Keywords: Intelligent strategy, integrated control, fuzzy logic, AFS/DYC.

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Authors: Zeynep Sener, Mehtap Dursun

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Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision methodology.

Keywords: Fuzzy decision making, fuzzy multiple objective programming, medical supply chain, supplier selection.

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Authors: Yongxian Jin, Jingzhou Huang

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In an open real-time system environment, the coexistence of different kinds of real-time and non real-time applications makes the system scheduling mechanism face new requirements and challenges. One two-level scheduling scheme of the open real-time systems is introduced, and points out that hard and soft real-time applications are scheduled non-distinctively as the same type real-time applications, the Quality of Service (QoS) cannot be guaranteed. It has two flaws: The first, it can not differentiate scheduling priorities of hard and soft real-time applications, that is to say, it neglects characteristic differences between hard real-time applications and soft ones, so it does not suit a more complex real-time environment. The second, the worst case execution time of soft real-time applications cannot be predicted exactly, so it is not worth while to cost much spending in order to assure all soft real-time applications not to miss their deadlines, and doing that may cause resource wasting. In order to solve this problem, a novel two-level real-time scheduling mechanism (including scheduling profile and scheduling algorithm) which adds the process of dealing with soft real-time applications is proposed. Finally, we verify real-time scheduling mechanism from two aspects of theory and experiment. The results indicate that our scheduling mechanism can achieve the following objectives. (1) It can reflect the difference of priority when scheduling hard and soft real-time applications. (2) It can ensure schedulability of hard real-time applications, that is, their rate of missing deadline is 0. (3) The overall rate of missing deadline of soft real-time applications can be less than 1. (4) The deadline of a non-real-time application is not set, whereas the scheduling algorithm that server 0 S uses can avoid the “starvation" of jobs and increase QOS. By doing that, our scheduling mechanism is more compatible with different types of applications and it will be applied more widely.

Keywords: Hard real-time, two-level scheduling profile, open real-time system, non-distinctive schedule, soft real-time

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Authors: Thi Nguyen, Lee Gordon-Brown, Jim Peterson, Peter Wheeler

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An additive fuzzy system comprising m rules with n inputs and p outputs in each rule has at least t m(2n + 2 p + 1) parameters needing to be tuned. The system consists of a large number of if-then fuzzy rules and takes a long time to tune its parameters especially in the case of a large amount of training data samples. In this paper, a new learning strategy is investigated to cope with this obstacle. Parameters that tend toward constant values at the learning process are initially fixed and they are not tuned till the end of the learning time. Experiments based on applications of the additive fuzzy system in function approximation demonstrate that the proposed approach reduces the learning time and hence improves convergence speed considerably.

Keywords: Additive fuzzy system, improving convergence, parameter learning process, unsupervised learning.

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Authors: Madhukar Nagare, Pankaj Dutta

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Inventory decisional environment of short life-cycle products is full of uncertainties arising from randomness and fuzziness of input parameters like customer demand requiring modeling under hybrid uncertainty. Prior inventory models incorporating fuzzy demand have unfortunately ignored stochastic variation of demand. This paper determines an unambiguous optimal order quantity from a set of n fuzzy observations in a newsvendor inventory setting in presence of fuzzy random variable demand capturing both fuzzy perception and randomness of customer demand. The stress of this paper is in providing solution procedure that attains optimality in two steps with demand information availability in linguistic phrases leading to fuzziness along with stochastic variation. The first step of solution procedure identifies and prefers one best fuzzy opinion out of all expert opinions and the second step determines optimal order quantity from the selected event that maximizes profit. The model and solution procedure is illustrated with a numerical example.

Keywords: Fuzzy expected value, Fuzzy random demand, Hybrid uncertainty, Optimal order quantity, Single-period inventory

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Authors: I. Laurence Aroquiaraj, K. Thangavel

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Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the second removes the pectoral muscle portion (present in Medio Lateral Oblique (MLO) views) from the rest of the breast tissue. In this paper we propose hybridization of Connected Component Labeling (CCL), Fuzzy, and Straight line methods. Our proposed methods worked good for separating pectoral region. After removal pectoral muscle from the mammogram, further processing is confined to the breast region alone. To demonstrate the validity of our segmentation algorithm, it is extensively tested using over 322 mammographic images from the Mammographic Image Analysis Society (MIAS) database. The segmentation results were evaluated using a Mean Absolute Error (MAE), Hausdroff Distance (HD), Probabilistic Rand Index (PRI), Local Consistency Error (LCE) and Tanimoto Coefficient (TC). The hybridization of fuzzy with straight line method is given more than 96% of the curve segmentations to be adequate or better. In addition a comparison with similar approaches from the state of the art has been given, obtaining slightly improved results. Experimental results demonstrate the effectiveness of the proposed approach.

Keywords: X-ray Mammography, CCL, Fuzzy, Straight line.

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Authors: Marziyeh Halimi, Roushanak Lotfikar, Simin Mansouri Borojeni

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In this paper we considered the Neumann problem for the fourth order differential equation. First we define the weighted Sobolev space 2 Wα and generalized solution for this equation. Then we consider the existence and uniqueness of the generalized solution, as well as give the description of the spectrum and of the domain of definition of the corresponding operator.

Keywords: Neumann problem, weighted Sobolev spaces, generalized solution, spectrum of linear operators.2000 mathematic subject classification: 34A05, 34A30.

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Authors: N.Subramanian, C.Murugesan

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This paper is devoted to the study of the general properties of Orlicz space of entire sequence of fuzzy numbers by using infinite matrices.

Keywords: Fuzzy numbers, infinite matrix, Orlicz space, entiresequence.

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Authors: Chao Wang, Yongkun Li

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In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.

Keywords: Discrete-time fuzzy BAM neural networks, ımpulses, global exponential stability, global asymptotical stability, equilibrium point.

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Authors: Shiuh-Jer Huang, Ming-Tien Su

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Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.

Keywords: Fuzzy control, gain tuning and optical disk drive.

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Authors: Qianhong Zhang, Lihui Yang, Daixi Liao

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In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of neural networks. Moreover an example is given to illustrate the effectiveness and feasible of results obtained.

Keywords: Fuzzy BAM neural networks, Periodic solution, Global exponential stability, Time-varying delays

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Authors: Mohanad Alata , Moh'd Al-Nimr, Rami Al-Jarrah

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The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.

Keywords: Air Conditioning, ANFIS, Fuzzy Control, Sugeno System.

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Authors: Naga Brahmendra Yadav Gorla, Dr. Lakshmi Narasamma N

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This paper proposes an active soft-switching circuit for bridge converters aiming to improve the power conversion efficiency. The proposed circuit achieves loss-less switching for both main and auxiliary switches without increasing the main switch current/voltage rating. A winding coupled to the primary of power transformer ensures ZCS for the auxiliary switches during their turn-off. A 350 W, 100 kHz phase shifted full bridge (PSFB) converter is built to validate the analysis and design. Theoretical loss calculations for proposed circuit is presented. The proposed circuit is compared with passive soft switched PSFB in terms of efficiency and loss in duty cycle.

Keywords: soft switching, passive soft switching, ZVS, ZCS, PSFB.

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Authors: A. V. Sai Balasubramanian, N. Ravi Shankar, S. Subbaraman, R. Rengaraj

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One of the major cause of eye strain and other problems caused while watching television is the relative illumination between the screen and its surrounding. This can be overcome by adjusting the brightness of the screen with respect to the surrounding light. A controller based on fuzzy logic is proposed in this paper. The fuzzy controller takes in the intensity of light surrounding the screen and the present brightness of the screen as input. The output of the fuzzy controller is the grid voltage corresponding to the required brightness. This voltage is given to CRT and brightness is controller dynamically. For the given test system data, different de-fuzzifier methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.

Keywords: Fuzzy controller, Grid voltage

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Authors: S. Massoum, A. Bentaallah, A. Massoum, F. Benaimeche, P. Wira, A. Meroufel

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This paper presents a speed fuzzy sliding mode controller for a vector controlled induction machine (IM) fed by a voltage source inverter (PWM). The sliding mode based fuzzy control method is developed to achieve fast response, a best disturbance rejection and to maintain a good decoupling. The problem with sliding mode control is that there is high frequency switching around the sliding mode surface. The FSMC is the combination of the robustness of Sliding Mode Control (SMC) and the smoothness of Fuzzy Logic (FL). To reduce the torque fluctuations (chattering), the sign function used in the conventional SMC is substituted with a fuzzy logic algorithm. The proposed algorithm was simulated by Matlab/Simulink software and simulation results show that the performance of the control scheme is robust and the chattering problem is solved.

Keywords: IM, FOC, FLC, SMC, and FSMC.

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Authors: Azah Kamilah Muda, Siti Mariyam Shamsuddin, Maslina Darus

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Writer identification is one of the areas in pattern recognition that attract many researchers to work in, particularly in forensic and biometric application, where the writing style can be used as biometric features for authenticating an identity. The challenging task in writer identification is the extraction of unique features, in which the individualistic of such handwriting styles can be adopted into bio-inspired generalized global shape for writer identification. In this paper, the feasibility of generalized global shape concept of complimentary binding in Artificial Immune System (AIS) for writer identification is explored. An experiment based on the proposed framework has been conducted to proof the validity and feasibility of the proposed approach for off-line writer identification.

Keywords: Writer identification, generalized global shape, individualistic, pattern recognition.

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Authors: Yung-Yuan Chen, Kuen-Long Leu

Abstract:

FlexRay, as a communication protocol for automotive control systems, is developed to fulfill the increasing demand on the electronic control units for implementing systems with higher safety and more comfort. In this work, we study the impact of radiation-induced soft errors on FlexRay-based steer-by-wire system. We injected the soft errors into general purpose register set of FlexRay nodes to identify the most critical registers, the failure modes of the steer-by-wire system, and measure the probability distribution of failure modes when an error occurs in the register file.

Keywords: Soft errors, FlexRay, fault injection, steer-by-wirer

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Authors: Mustafa Resa Becan

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Sliding mode control with a fuzzy boundary layer is presented to hydraulic position control problem in this paper. A nonlinear hydraulic servomechanism which has an asymmetric cylinder is modeled and simulated first, then the proposed control scheme is applied to this model versus the conventional sliding mode control. Simulation results proved that the chattering free position control is achieved by tuning the fuzzy scaling factors properly.

Keywords: Hydraulic servomechanism, position control, sliding mode control, chattering, fuzzy boundary layer.

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Authors: Mehrdad N. Khajavi, Vahid Abdollahi

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The purpose of suspension system in automobiles is to improve the ride comfort and road handling. In this research the ride and handling performance of a specific automobile with passive suspension system is compared to a proposed fuzzy logic semi active suspension system designed for that automobile. The bodysuspension- wheel system is modeled as a two degree of freedom quarter car model. MATLAB/SIMULINK [1] was used for simulation and controller design. The fuzzy logic controller is based on two inputs namely suspension velocity and body velocity. The output of the fuzzy controller is the damping coefficient of the variable damper. The result shows improvement over passive suspension method.

Keywords: Suspension System, Ride Comfort, Fuzzy Logic Controller, Passive and Semi Active System.

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