Fuzzy Point Research Articles

Filter Theory in Pre-Ordered Residuated Systems Using Intuitionistic Fuzzy Points

Using the notion of intuitionistic fuzzy points, the concept of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters in pre-ordered residuated systems are introduced, and several related properties are investigated. Characterizations of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters are studied. By forming sub-structures called intuitionistic level set, intuitionistic [Formula: see text]-set, intuitionistic [Formula: see text]-set, and [Formula: see text]-set, the conditions under which they can be filters will be tracked.

Predictive direct power control of a grid connected photovoltaic system, associated with an active power filter

This paper deals with power quality improvement using a three-phase active power filter (APF) connected to a PV power system. This paper deals with power quality improvement using a three-phase active power filter (APF) connected to a PV power system. The DC-DC boost converter acting as an interface within the PV system and the three-phase voltage source inverter. A fuzzy logic maximum power point tracking (MPPT) controller is used to obtain the maximum power from the PV system. Furthermore, the optimal selection of the inverter switching states is realized by combination of direct power control (DPC) and a predictive method. Modelling and simulation of the system were performed by using Matlab/Simulink software.

On a family of billiards-inspired operators over intuitionistic fuzzy sets

In the present work we introduce a family of geometrically inspired operators over intuitionistic fuzzy sets. In essence, if we consider the interpretational triangle as a billiards table with certain properties and each point of an intuitionistic fuzzy set as a ball propelled with a predetermined initial force, then its image after bouncing off from the boundaries of the triangle will, in general, be a new and different intuitionistic fuzzy point. The value of this image depends on the magnitude and direction of the force, which we will describe by using a parameter λ > 0 and another intuitionistic fuzzy set over the same universe.

Fuzzy Logic Control of Two-Stage Grid- Connected Photovoltaic System

In this paper, a two-stage grid-connected photovoltaic system is presented. The optimal performance of solar panels at varying temperatures and irradiance levels is achieved by the application of a fuzzy logic-based maximum power point tracking method. Space vector modulation is used to control the inverter; to achieve capacitor voltage balance, redundant switching states of a three level inverter are used. The grid side control regulates the power and the current injected to the grid, the conventional PI controllers are replaced by fuzzy PI. Simulations have been made using Simulink environment on MATLAB to validatethe control of the proposed system.

Reinforcement learning based fractional fuzzy controller for photovoltaic systems

This article presents an innovative artificial nonlinear control technique for photovoltaic (PV) systems. A boost converter extracts maximum power from the PV system under different weather conditions. A fuzzy logic maximum power point (MPP) finding algorithm is used to determine the reference voltage of the PV system under various atmospheric conditions. It is assumed that the nonlinear dynamic model, parameters, and uncertainties of the converter are unknown. To estimate a precise model that contains nonlinearities, model uncertainties, and disturbances of the converter, proximal policy optimization (PPO) with a special reward function is applied. PPO is optimal in policy learning and sampling, fast to implement, and is a simple reinforcement learning (RL) algorithm. Then, estimations of dynamics and uncertainties are used to enhance the robustness of the suggested fractional order sliding mode controller. Furthermore, the controller coefficients are optimally adjusted by the PPO algorithm. The Lyapunov theorem is used for proving the control system's closed-loop stability. Also, the proposed methods can be generalized and used for other control systems. The simulation is conducted by MATLAB to evaluate the suggested controller's performance effectiveness. Robustness against the presence of parameter uncertainty is investigated. Moreover, the suggested technique is also compared with sliding mode controller.

Enhancing of single-stage grid-connected photovoltaic system using fuzzy logic controller

The power generated by photovoltaic (PV) systems is influenced by environmental factors. This variability hampers the control and utilization of solar cells' peak output. In this study, a single-stage grid-connected PV system is designed to enhance power quality. Our approach employs fuzzy logic in the direct power control (DPC) of a three-phase voltage source inverter (VSI), enabling seamless integration of the PV connected to the grid. Additionally, a fuzzy logic-based maximum power point tracking (MPPT) controller is adopted, which outperforms traditional methods like incremental conductance (INC) in enhancing solar cell efficiency and minimizing the response time. Moreover, the inverter's real-time active and reactive power is directly managed to achieve a unity power factor (UPF). The system's performance is assessed through MATLAB/Simulink implementation, showing marked improvement over conventional methods, particularly in steady-state and varying weather conditions. For solar irradiances of 500 and 1,000 W/m<sup>2</sup>, the results show that the proposed method reduces the total harmonic distortion (THD) of the injected current to the grid by approximately 46% and 38% compared to conventional methods, respectively. Furthermore, we compare the simulation results with IEEE standards to evaluate the system's grid compatibility.

FUZZY MAXIMUM POWER POINT TRACKING CONTROLLERS FOR PHOTOVOLTAIC SYSTEMS: A COMPARATIVE ANALYSIS

The design of an effective fuzzy maximum power point tracking controller plays a crucial aspect in enhancing the photovoltaic system’s efficiency. This article aims to design and compare the performance of symmetric and asymmetric types of fuzzy controllers’ maximum power point tracking algorithms. Depending on the BP SX150S module’ power-voltage attributes at standard technical conditions, the input membership function parameters are derived. Moreover, the effect of fuzzy memberships’ quantity is also examined in this article. Where Five and seven triangular memberships are used. For the simulation, MATLAB is used to assess the effectiveness of the fuzzy controllers. Simulation results show that the asymmetric controller outperforms the symmetric type in terms of transient and steady-state tracking for different numbers of membership functions. Specifically, when employed with 5-triangle memberships, the asymmetric controller outperforms the symmetrical controller in terms of rise time, tracking precision, and energy output, respectively, by 83%, 0.06%, and 14.14%. While, the rise time, tracking precision, and energy yield of 7-triangle memberships are all improved by 86.7%, 0.04%, and 14.78%, respectively. Using asymmetric type, 7-triangle memberships enhance the rise time and harvested energy by around 18.2% and 0.082%, respectively. Overall, the most effective tracking technique for enhancing the photovoltaic system’s efficiency is the asymmetric type, independent of the quantity of memberships.

A study on fuzzy sphere and fuzzy cone

In this paper, we investigate three different methods to construct a fuzzy sphere. These methods depend on the entities available to form a fuzzy sphere. In the first method, we formulate a fuzzy sphere when the position of the center and the value of the radius are given imprecisely. In the second method, a fuzzy sphere is constructed when the diameter of a fuzzy sphere is known. In the last method, we construct a fuzzy sphere that passes through four given S-type space fuzzy points whose core points are not co-planar. Also, a rotation invariance property of a fuzzy sphere is investigated. In addition, we show that the intersection of a fuzzy sphere with a crisp plane is a fuzzy circle. In a sequel, the idea of a fuzzy cone is developed. The properties concerned with the intersection of a fuzzy cone with a crisp plane are studied sequentially. All the studies are supported with geometrical interpretations and numerical examples.Moreover, we also develop the algorithms to get the membership grade of a number(i)in the diameter form of the fuzzy sphere and(ii)in the four-point form of the fuzzy sphere.

Lyapunov stability of fuzzy dynamical systems based on fuzzy-number-valued function granular differentiability

Lyapunov stability theory provides a powerful technique for stability analysis of dynamical systems, particularly for the stability of nonlinear dynamical system. This paper deals with the stability of fuzzy dynamical systems using a novel notion called granular fuzzy Lyapunov function. In order to analyze the stability, some new notions are introduced such as fuzzy equilibrium point, the ball of fuzzy state space, granular fuzzy 2-norm and etc. Based on the concept of fuzzy-number-valued function granular differentiability, two theorems are proved for calculation. Moreover, using granular fuzzy Lyapunov function, the granular fuzzy local stability theorem is proposed, and two definitions of exponential stability and like-Lyapunov stability are generalized. Finally, several examples are given to illustrate the proposed theorems.

Spherical fuzzy symmetric point criterion-based approach using Aczel–Alsina prioritization: application to sustainable supplier selection

Spherical fuzzy symmetric point criterion-based approach using Aczel–Alsina prioritization: application to sustainable supplier selection

Implementation of fuzzy logic MPPT based on Arduino in small scale PV pumping system

The performance of photovoltaic (PV) affected directly by climatic changes, The controller maintain maximum potential energy conversation to operate the pimping system at nominal conditions, fuzzy logic intelligent controllers are successfully suitable and applicable in engineering and applied science. The aim of this paper is present an experimental approach in Implementation of fuzzy logic maximum power point tracking (MPPT) with boost converter based on Arduino Mega micro-controller to maximize energy production in different weather condition applied to small scale pumping system for water and chemical fluid analyses in isolated area. The system is supplied by 20 (W) solar photovoltaic (PV) panel. This paper present a real-time MATLAB/Simulink fuzzy logic method controlling and monitoring MPPT application using an low cost Arduino Mega micro-controller combined with (LV25, LP55) sensors controlling boost converter interconnected with solar panel and plastic pump.

Bipolar Fuzzy Supra Topology via (Q-) Neighborhood and Its Application in Data Mining Process

The aim of this study is to provide neighborhood structures in bipolar fuzzy supra topological space and to show the applicability of bipolar fuzzy supra topology to the medical diagnosis problem. Firstly, we give some properties related to bipolar fuzzy points and their neighborhood structure in bipolar fuzzy supra topological spaces. Then, we consider another important structure, “quasi-coincident”, in the case of bipolar fuzzy points and bipolar fuzzy sets. Then, we introduce the corresponding neighborhood structure called “Q-neighborhood system” by using the quasi-coincident relations. Furthermore, we also investigate the characterization of bipolar fuzzy supra topological space in terms of quasi-neighborhoods. Finally, we present a new method to solve medical diagnosis problems by using the bipolar fuzzy score function.

Comparison of Solar P&O and FLC-based MPPT Controllers & Analysis under Dynamic Conditions

Increase in electricity generation is caused due to population increase, which leads to the depletion of fossil fuels, and increased pollution. This leads to focusing on alternate renewable energy, mainly solar photovoltaic generation, due to the abundant availability. The maximum power generated by a PV module depends on the temperature and irradiance because the P-V and V-I natures are non-linear. Various DC-DC boost converters are used along with the MPPT techniques because the conversion efficiency of the PV system is low [1][2]. In this paper, comparative analysis between Perturb and Observe (P&O) and Fuzzy Logic-based Maximum Power Point Tracking (MPPT) systems along with modified SEPIC are done using MATLAB/ SIMULINK software. Simulations are done at different irradiations to observe its tracking speed towards MPP. From the obtained output (simulation), it is observed that the Fuzzy Logic Converter (FLC)-based MPPT controllers have good dynamic performance, reduced oscillation, high tracking speed, maximum power, etc...[3].

Quantum Euler angles and agency-dependent space-time

Abstract Quantum gravity is expected to introduce quantum aspects into the description of reference frames. Here we begin exploring how quantum gravity induced deformations of classical symmetries could modify the transformation laws among reference frames in an effective regime. We invoke the quantum group SUq(2) as a description of deformed spatial rotations and interpret states of a representation of its algebra as describing the relative orientation between two reference frames. This leads to a quantization of one of the Euler angles and to an aspect of agency dependence: space is reconstructed as a collection of fuzzy points, exclusive to each agent, which depends on their choice of reference frame. Each agent can choose only one direction in which points can be sharp, while points in all other directions become fuzzy in a way that depends on this choice. Two agents making different choices will thus observe the same points with different degrees of fuzziness.

An adaptive fuzzy maximum power point tracking for PV systems by a mutant gray wolf optimization algorithm

Abstract An innovative and adaptive maximum power point tracking (MPPT) based on a fuzzy controller is proposed in this article. The proposed controller is optimized by the mutant gray wolf optimization (MGWO) algorithm, and the objective function uses an integral squared time squared error (ISTSE) index. To indicate the efficiency of the proposed MPPT algorithm (MGWO-AF-MPPT), the simulations for several irradiation conditions are modeled in MATLAB. In addition, two fair comparisons are performed between the simulation results of the proposed MPPT method with an adaptive fuzzy controller that optimized with particle swarm optimization (PSO-AF-MPPT), as well as a Perturbation and Observation method (P&O-MPPT). The comparison results illustrate that the amount of generated electrical power from the PV system for all adaptive MPPT systems is almost close to each other, indicating the high accuracy of both fuzzy-based controllers. However, the PV power generation of the proposed MGWO-AF-MPPT is higher, and also its ripple is lower than PSO-AF-MPPT. Note that, the calculated total harmonic distortion (THD) for the P&O-MPPT, PSO-AF-MPPT, and the proposed MGWO-AF-MPPT methods are calculated at 3.4%, 2.3%, and 2.1%, respectively. A lower THD indicates better power quality generated by the PV system employing the MGWO-AF-MPPT method.

A New Notion of Fuzzy Function Ideal Convergence

P.M. Pu and Y.M. Liu extended Moore-Smith’s convergence of nets to fuzzy topology and Y.M. Liu provided analogous results to J. Kelley’s classical characterization theorem of net convergence by introducing the notion of fuzzy convergence classes. In a previous paper, the authors of this study provided modified versions of this characterization by using an alternative notion of convergence of fuzzy nets, introduced by B.M.U. Afsan, named fuzzy net ideal convergence. Our main scope here is to generalize and simplify the preceding results. Specifically, we insert the concept of a fuzzy function ideal convergence class, L, on a non-empty set, X, consisting of triads (f,e,I), where f is a function from a non-empty set, D, to the set FP(X) of fuzzy points in X, which we call fuzzy function, e∈FP(X), and I is a proper ideal on D, and we provide necessary and sufficient conditions to establish the existence of a unique fuzzy topology, δ, on X, such that (f,e,I)∈L iff fI-converges to e, relative to the fuzzy topology δ.

Quasi-subalgebras of Sheffer stroke BL-algebras associated with fuzzy points and a new type of fuzzy set

The Jun’s YεJ -fuzzy set is applied to the Sheffer stroke BL-algebra, and the notions of an (∈, ∈)- YεJ -fuzzy quasisubalgebra and an (∈, ∈ ∨q)-YεJ -fuzzy quasi-subalgebra in Sheffer stroke BL-algebras are introduced, and several properties are explored. Characterizations of (∈, ∈)- YεJ - fuzzy quasi-subalgebras and (∈, ∈ ∨q)- YεJ -fuzzy quasisubalgebras are investigated, and the relationships between the fuzzy quasi-subalgebra, the (∈, ∈)- YεJ -fuzzy quasi- subalgebra and the (∈, ∈ ∨q)- YεJ -fuzzy quasisubalgebra are considered. Conditions for a fuzzy set to be an (∈, ∈∨q)- YεJ -fuzzy quasi-subalgebra are displayed.

δ-separation Axioms on Fuzzy Hypersoft Topological Spaces

In this article, the concept of fuzzy hypersoft δ (resp. semi, pre, δ semi δ pre)-separation axioms in fuzzy hypersoft topological spaces are introduced by developing fuzzy hypersoft δ (resp. semi, pre, δ semi δ pre)-neighbourhood with respect to fuzzy hypersoft points. Also, the properties and relations between fuzzy hypersoft δ (resp. semi, pre, δ semi δ pre)- Ti- spaces (i = 0, 1, 2, 3, 4) are discussed.

Feature detection of mineral zoning in spiral slope flow under complex conditions based on improved YOLOv5 algorithm

In actual processing plants, the quality and efficiency of the traditional spiral slope flow concentrator still rely on workers to observe the changes in the mineral belt. However, in realistic complex working conditions, the formation of mineral separation zones is subject to large uncertainties, and coupled with the limited efforts, experience, and responsibility of workers, it becomes important to free up labour and improve the efficiency and profitability of the beneficiation plant. Therefore, to solve the problem of difficult detection of fuzzy small target mineral separation point features in real scenes, an improved YOLOv5-based algorithm is proposed. Firstly, the dataset quality is well improved by image enhancement and pre-processing techniques, after that an innovative CASM attention mechanism is added to the backbone of the YOLOv5 model, followed by a multi-scale feature output and prediction enhancement in the neck part of the model, and an optimized loss function is designed to optimize the whole feature learning process. The improved effect of the model and the specific detection performance were tested using real mine belt image datasets, the ablation experiment verified the comprehensive effectiveness of the proposed improved method and finally compared it with the existing high-level attention mechanism and target detection algorithms. The experimental results show that the improved YOLOv5 algorithm proposed in this study has the best overall detection performance carrying a MAP of 0.954, which is over 20% better than YOLOv5. It is worth mentioning that the improvement to achieve this performance only increases the parameter values by 0.8M and GFLOPs by 1.8, moreover, in terms of the inference speed, it also achieves a respectable 63 FPS, implying that the proposed improved method achieves a better balance between the performance enhancement and the computational complexity of the model, the overall detection results fully satisfy the industrial requirements.

Computational study of a co-infection model of HIV/AIDS and hepatitis C virus models

Hepatitis C infection and HIV/AIDS contaminations are normal in certain areas of the world, and because of their geographic overlap, co-infection can’t be precluded as the two illnesses have a similar transmission course. This current work presents a co-infection model of HIV/AIDS and Hepatitis C virus with fuzzy parameters. The application of fuzzy theory aids in tackling the issues associated with measuring uncertainty in the mathematical depiction of diseases. The fuzzy reproduction number and fuzzy equilibrium points have been determined in this context, focusing on a model applicable to a specific group defined by a triangular membership function. Furthermore, for the model, a fuzzy non-standard finite difference (NSFD) technique has been developed, and its convergence is examined within a fuzzy framework. The suggested model is numerically validated, confirming the dependability of the devised NSFD technique, which successfully retains all of the key properties of a continuous dynamical system.