http://www.hindawi.comThe latest articles from Hindawi Publishing Corporation© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/172917.htmlIn 1992, Ramadan introduced the concept of a smooth topological space and relativeness between smooth topological space and fuzzy topological space in Chang's (1968) view points. In this paper we give a new definition of smooth topological space. This definition can be considered as a generalization of the smooth topological space which was given by Ramadan. Some general properties such as relative smooth continuity and relative smooth compactness are studied.B. Ghazanfari© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/450259.htmlThis paper proposes a fuzzy modelling approach oriented to the design of a fuzzy controller for regulating the fresh airflow of a real diesel engine. This strategy has been suggested for enhancing the regulator design that could represent an alternative to the standard embedded BOSCH controller, already implemented in the Engine Control Unit (ECU), without any change to the engine instrumentation. The air system controller project requires the knowledge of a dynamic model of the diesel engine, which is achieved by means of the suggested fuzzy modelling and identification scheme. On the other hand, the proposed fuzzy PI controller structure is straightforward and easy to implement with respect to different strategies proposed in literature. The results obtained with the designed fuzzy controller are compared to those of the traditional embedded BOSCH controller.S. Simani and M. Bonfè© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/407890.htmlWe define the concept of a mapping on classes of fuzzy soft sets and study the properties of fuzzy soft images and fuzzy soft inverse images of fuzzy soft sets, and support them with examples and counterexamples.Athar Kharal and B. Ahmad© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/586507.htmlWe further contribute to the properties of fuzzy soft sets as defined and studied in the work of Maji et al. ( 2001), Roy and Maji (2007), and Yang et al. (2007) and support them with examples and counterexamples. We improve Proposition 3.3 by Maji et al., (2001). Finally we define arbitrary fuzzy soft union and fuzzy soft intersection and prove DeMorgan Inclusions and DeMorgan Laws in Fuzzy Soft Set Theory.B. Ahmad and Athar Kharal© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/148193.htmlThis paper investigates the dynamical systems in the context of topological semigroup actions on intuitionistic fuzzy metric spaces. We give some concepts such as topological transitivity, point transitivity, and densely point transitivity for such dynamical systems. Particularly, we consider the implications of nonsensitivity and its relation to dynamical properties such as transitivity and equicontinuity.Yaoyao Lan and Qingguo Li© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/303042.htmlSeveral properties of fuzzy semiclosure and fuzzy semi-interior of fuzzy sets defined by Yalvac (1988), have been established and supported by counterexamples. We also study the characterizations and properties of fuzzy semi-open and fuzzy semi-closed sets. Moreover, we define fuzzy s-open and fuzzy s-closed mappings and give some interesting characterizations.B. Ahmad and Athar Kharal© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2009/241809.htmlThis paper presents a new method of online estimation of the stator and rotor resistance of the induction motor in the indirect vector-controlled drive, with artificial neural networks. The back propagation algorithm is used for training of the neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, is investigated with the help of simulations for variations in the stator and rotor resistance from their nominal values. Both types of resistance are estimated experimentally, using the proposed neural network in a vector-controlled induction motor drive. Data on tracking performances of these estimators are presented. With this approach, the rotor resistance estimation was found to be insensitive to the stator resistance variations both in simulation and experiment.Baburaj Karanayil, Muhammed Fazlur Rahman, and Colin Grantham© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/963710.htmlExtraction of maximum wind power of variable speed wind turbines in hybrid wind-diesel-storage system (HWDSS) is considered due to economical purposes. The proposed control algorithm utilizes extended fuzzy-linear matrix equalities (FLMEs) systems design of stabilizing fuzzy controllers for nonlinear systems described by Takagi-Sugeno (TS) fuzzy models. The algorithm maximizes the power coefficient for a fixed pitch. Moreover, it reduces the voltage ripple and stabilizes the system over a wide range of wind speed variations. The control scheme is tested for different profiles of wind speed pattern and provides satisfactory results.Elkhatib Kamal, Magdy Koutb, Abdul Azim Sobaih, and Sahar Kaddah© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/295649.htmlThe aim of this paper is the generalization of the notion of fuzzy vector spaces to fuzzy hypervector spaces. In this regard, by considering the notion of fuzzy hypervector spaces, we characterized a fuzzy hypervector space based on its level sub-hyperspace. The algebraic nature of fuzzy hypervector space under transformations is studied. Certain conditions are obtained under which a given fuzzy hypervector space can or cannot be realized as a union of two fuzzy hypervector spaces such that none is contained in the other. The construction of a fuzzy hypervector space generated by a given fuzzy subset of a hypervector space is given. The set of all fuzzy cosets of a fuzzy hypervector space is shown to be a hypervector space. Finally, a fuzzy quotient hypervector space is defined and an analogue of a consequence of the “fundamental theorem of homomorphisms” is obtained.R. Ameri and O. R. Dehghan© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/920615.htmlA novel digital image stabilization technique is proposed in this paper. It is based on a fuzzy Kalman compensation of the global motion vector (GMV), which is estimated in the log-polar plane. The GMV is extracted using four local motion vectors (LMVs) computed on respective subimages in the logpolar plane. The fuzzy Kalman system consists of a fuzzy system with the Kalman filter's discrete time-invariant definition. Due to this inherited recursiveness, the output results into smoothed image sequences. The proposed stabilization system aims to compensate any oscillations of the frame absolute positions, based on the motion estimation in the log-polar domain, filtered by the fuzzy Kalman system, and thus the advantages of both the fuzzy Kalman system and the log-polar transformation are exploited. The described technique produces optimal results in terms of the output quality and the level of compensation.Nikolaos Kyriakoulis and Antonios Gasteratos© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/586893.htmlWe present several properties of fuzzy boundary and fuzzy semiboundary which have been supported by examples. Properties of fuzzy semi-interior, fuzzy semiclosure, fuzzy boundary, and fuzzy semiboundary have been obtained in product-related spaces. We give necessary conditions for fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions. Moreover, fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions have been characterized via fuzzy-derived (resp., fuzzy-semiderived) sets.M. Athar and B. Ahmad© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/691808.htmlThis paper presents the real-time implementation of a fuzzy coordinated classical PI control scheme for controlling the pressure in a pilot pressure tank system. The fuzzy system has been designed to track the variation parameters in a feedback loop and tune the classical controller to achieve a better control action for load disturbances and set point changes. The error and process inputs are chosen as the inputs of fuzzy system to tune the conventional PI controller according to the process condition. This online conventional controller tuning technique will reduce the human involvement in controller tuning and increase the operating range of the conventional controller. The proposed control algorithm is experimentally implemented for the real-time pressure control of a pilot air tank system and validated using a high-speed 32-bit ARM7 embedded microcontroller board (ATMEL AT91M55800A). To demonstrate the performance of the fuzzy coordinated PI control scheme, results are compared with a classical PI and PI-type fuzzy control method. It is observed that the proposed controller structure is able to quickly track the parameter variation and perform better in load disturbances and also for set point changes.N. Kanagaraj, P. Sivashanmugam, and S. Paramasivam© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/421525.htmlWe provide a way to combine matrix Lyapunov systems with fuzzy rules to form a new fuzzy system called fuzzy dynamical matrix Lyapunov system, which can be regarded as a new approach to intelligent control. First, we study the controllability property of the fuzzy dynamical matrix Lyapunov system and provide a sufficient condition for its controllability with the use of fuzzy rule base. The significance of our result is that given a deterministic system and a fuzzy state with rule base, we can determine the rule base for the control. Further, we discuss the concept of observability and give a sufficient condition for the system to be observable. The advantage of our result is that we can determine the rule base for the initial value without solving the system.M. S. N. Murty and G. Suresh Kumar© 2010, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/journals/afs/2008/528461.htmlThe main goal of this study is to investigate the relationship between psychosocial variables and diabetic children patients and to obtain a classifier function with which it was possible to classify the patients on the basis of assessed adherence level. The rough set theory is used to identify the most important attributes and to induce decision rules from 302 samples of Kuwaiti diabetic children patients aged 7–13 years old. To increase the efficiency of the classification process, rough sets with Boolean reasoning discretization algorithm is introduced to discretize the data, then the rough set reduction technique is applied to find all reducts of the data which contains the minimal subset of attributes that are associated with a class label for classification. Finally, the rough sets dependency rules are generated directly from all generated reducts. Rough confusion matrix is used to evaluate the performance of the predicted reducts and classes. A comparison between the obtained results using rough sets with decision tree, neural networks, and statistical discriminate analysis classifier algorithms has been made. Rough sets show a higher overall accuracy rates and generate more compact rules.Aboul ella Hassanien, Mohamed E. Abdelhafez, and Hala S. Own© 2010, Hindawi Publishing Corporation. All rights reserved.