Iranian journal of fuzzy systems
Volume:13 Issue: 3, Jun - Jul 2016

The main asset of this paper is among the uses of fuzzy logic in the engineering sector and especially in the renewable energies as a large alternate of fossil energies, in this paper a PSO-based optimization is used to find the optimal scaling parameters, of a fuzzy logic-based MPPT controller, that maximize the efficiency of a photovoltaic pumping system. The tuning of input and output parameters are of direct effect on the power that flows from the photovoltaic source to the load. In order to see concrete results, the PV system is used for irrigation of greenhouses in Laghouat, Algeria. The performances of the proposed PSO-based fuzzy controller are compared with those obtained using fuzzy logic and P&O controllers under variations of meteorological conditions. The simulation results proved a good robustness performance of the proposed Fuzzy based PSO controller over the other regarding the gained solar energy and the daily pumped water.

The purpose of this work is to introduce and study the concept of minimal deterministic automaton with IF-outputs which realizes the given IF-language. Among two methods for construction of such automaton presented here, one is based on Myhill-Nerode's theory while the other is based on derivatives of the given IF-language. Meanwhile, the categories of deterministic automata with IF-outputs and IF-languages alongwith a functorial relationship between them are introduced

Research on wind turbine technologies have focused primarily on power cost reduction. Generally, this aim has been achieved by increasing power output while maintaining the structural load at a reasonable level. However, disturbances, such as wind speed, affect the performance of wind turbines, and as a result, the use of various types of controller becomes crucial.
This paper deals with two adaptive fuzzy controllers at full load operation. The first controller uses the generated power, and the second one uses the angular velocity as feedback signals. These feedback signals act to control the load torque on the generator and blade pitch angle. Adaptive rules, derived from the fuzzy controller, are defined based on the differences between state variables of the power and angular velocity of the generator and their nominal values.
The results, which are compared with verified results of reference controller, show that the proposed adaptive fuzzy controller in full load operation has a higher efficiency than that of reference ones, insensitive to fast wind speed variation that is considered as disturbance.

Predominantly in the faltering atmosphere, the precise value of some factors is difficult to measure. Though, it can be easily approximated by intuitionistic fuzzy linguistic term in the real-life world problem. To deal with such situations, in this paper two information measures based on trigonometric function for intuitionistic fuzzy sets, which are a generalized version of the fuzzy information measures are introduced. Based on it new trigonometric similarity measure is developed. Mathematical illustration displays reasonability and effectiveness of the information measures for IFSs by comparing it with the existing information measures. Corresponding to information and similarity measures for IFSs, two new (1) Intuitionistic Fuzzy Similarity Measure Weighted Average Operator (IFSMWAO) method for township development and (2) TOPSIS method for multiple criteria decision making (MCDM) (investment policies) problems have been developed. In the existing methods the authors have assumed the weight vectors, while in the proposed method it has been calculated using intuitionistic fuzzy information measure. This enhances the authenticity of the proposed method.

In this paper, The Picard method is proposed to solve the system of first-order fuzzy differential equations $(FDEs)$ with fuzzy initial conditions under generalized $H$-differentiability. The existence and uniqueness of the solution and convergence of the proposed method are proved in details. Finally, the method is illustrated by solving some examples.

This paper proposes a quadratic programming method (QPM) for ranking alternatives based on multiplicative preference relations (MPRs) and fuzzy preference relations (FPRs). The proposed QPM can be used for deriving a ranking from either a MPR or a FPR, or a group of MPRs, or a group of FPRs, or their mixtures. The proposed approach is tested and examined with two numerical examples, and comparative analyses with the existing methods are provided to show the effectiveness and advantages of the QPM.

We apply Preus's concept of $mbbe$-connectedness to the categories of lattice-valued uniform convergence spaces and of lattice-valued uniform spaces. A space is uniformly $mbbe$-connected if the only uniformly continuous mappings from the space to a space in the class $mbbe$ are the constant mappings. We develop the basic theory for $mbbe$-connected sets, including the product theorem. Furthermore, we define and study uniform local $mbbe$-connectedness, generalizing a classical definition from the theory of uniform convergence spaces to the lattice-valued case. In particular it is shown that if the underlying lattice is completely distributive, the quotient space of a uniformly locally $mbbe$-connected space and products of locally uniformly $mbbe$-connected spaces are locally uniformly $mbbe$-connected.

In this paper, we introduce the concept of best proximal contraction theorems in non-Archimedean fuzzy metric space for two mappings and prove some proximal theorems. As a consequence, it provides the existence of an optimal approximate solution to some equations which contains no solution. The obtained results extend further the recently development proximal contractions in non-Archimedean fuzzy metric spaces and famous Banach contraction principle.

Our aim of this paper is to introduce the concept of L-double fuzzy rough sets in which both constructive and axiomatic approaches are used. In constructive approach, a pair of L-double fuzzy lower (resp. upper) approximation operators is defined and the basic properties of them are studied. From the viewpoint of the axiomatic approach, a set of axioms is constructed to characterize the L double fuzzy upper (resp. lower) approximation of L-double fuzzy rough sets. Finally, from L- double fuzzy approximation operators, we generated Alexandrov L-double fuzzy topology.

Based on previous results that study the completion of fuzzy metric spaces, we show that every intuitionistic fuzzy quasi-metric space, using the notion of fuzzy metric space in the sense of Kramosil and Michalek to obtain a generalization to the quasi-metric setting, has a bicompletion which is unique up to isometry.