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Axioms
Special Issues
Recent Developments in Fuzzy Control Systems and Their Applications
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Recent Developments in Fuzzy Control Systems and Their Applications

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Logic".

Deadline for manuscript submissions: 28 April 2025 | Viewed by 5611

Special Issue Editors

Dr. Ramasamy Kavikumar

E-Mail Website
Guest Editor
School of Electrical Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea
Interests: systems and control theory; fuzzy systems
Special Issues, Collections and Topics in MDPI journals
Dr. Kaviarasan Boomipalagan

E-Mail Website
Guest Editor
School of Electrical Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea
Interests: fuzzy systems; time-delay systems
Dr. S. A. Karthick

E-Mail Website
Guest Editor
Department of Electrical Engineering, National Tsing Hua University, Hsinchu 300044, Taiwan
Interests: robust control; neural networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Generally, nonlinear systems pose an extremely challenging research problem because of their inherent complexity. As a solution for the design of suitable modeling and control approach for nonlinear systems, the Takagi–Sugeno (T-S) fuzzy-model-based control method was chosen as a suitable candidate due to its remarkable nonlinear processing ability and rigorous mathematical structure. It has been widely used in various fields, such as electrical engineering, aerospace engineering, nuclear spin generators, population management, and secure communication. Over the last few decades, many researchers have found that T-S fuzzy control systems provide a natural framework for the mathematical modeling of a variety of practical systems in many real-world systems and natural processes. Moreover, the mathematical theory of T-S fuzzy control systems, including the existence and continuity theorems and Lyapunov stability theory, promotes the process from theoretical modeling to practical applications.

The purpose of this Special Issue is to present a collection of articles showing novel developments and results in the theory and practice of fuzzy control algorithms for nonlinear systems. The proposed Special Issue will focus on advanced and non-standard methods, offering remarkable innovations in both theoretical background and applications.

Dr. Ramasamy Kavikumar
Dr. Kaviarasan Boomipalagan
Dr. S. A. Karthick
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Axioms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fuzzy modeling and its applications
  • takagi–Sugeno structures
  • interval type-2 fuzzy control systems
  • membership-function-dependent analysis
  • optimization-based fuzzy algorithm
  • stability/performance/robustness analysis of fuzzy control systems
  • industrial applications of fuzzy control systems

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Published Papers (4 papers)

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Research

36 pages, 455 KiB  
Article
A Hybrid Fuzzy Mathematical Programming Approach for Manufacturing Inventory Models with Partial Trade Credit Policy and Reliability
by Prasantha Bharathi Dhandapani, Kalaiarasi Kalaichelvan, Víctor Leiva, Cecilia Castro and Soundaria Ramalingam
Axioms 2024, 13(11), 743; https://doi.org/10.3390/axioms13110743 - 29 Oct 2024
Viewed by 588
Abstract
This study introduces an inventory model for manufacturing that prioritizes product quality and cost efficiency. Utilizing fuzzy logic and mathematical programming, the model integrates fuzzy numbers to describe uncertainties associated with manufacturing costs and quality control parameters. The model extends beyond conventional inventory [...] Read more.
This study introduces an inventory model for manufacturing that prioritizes product quality and cost efficiency. Utilizing fuzzy logic and mathematical programming, the model integrates fuzzy numbers to describe uncertainties associated with manufacturing costs and quality control parameters. The model extends beyond conventional inventory systems by incorporating a dynamic mechanism to halt production, employing fuzzy decision variables to optimize the economic order quantity and minimize total costs. Key innovations include the application of approaches related to graded mean integration for defuzzification and the use of Kuhn–Tucker conditions to ensure optimal solutions under complex constraints. These approaches facilitate the precise management of production rates, inventory levels, and cost factors, which are essential in achieving a balance between supply and demand. A computational analysis validates the model’s effectiveness, demonstrating cost reductions while maintaining optimal inventory levels. This underscores the potential of integrating fuzzy arithmetic with traditional optimization techniques to enhance decision making in inventory management. The model’s adaptability and accuracy indicate its broad applicability across various sectors facing similar challenges, offering a valuable tool for operational managers and decision makers to improve efficiency and reduce waste in production cycles. Full article
(This article belongs to the Special Issue Recent Developments in Fuzzy Control Systems and Their Applications)
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22 pages, 1201 KiB  
Article
Generalization of Fermatean Fuzzy Set and Implementation of Fermatean Fuzzy PROMETHEE II Method for Decision Making via PROMETHEE GAIA
by Revathy Aruchsamy, Inthumathi Velusamy, Krishnaprakash Sanmugavel, Prasantha Bharathi Dhandapani and Kavikumar Ramasamy
Axioms 2024, 13(6), 408; https://doi.org/10.3390/axioms13060408 - 17 Jun 2024
Cited by 1 | Viewed by 1016
Abstract
The Fermatean fuzzy set, in contrast to other generalizations of fuzzy sets like PFS and IFS, has a wide range of acceptance for both MF and NMF. In light of this, the Fermatean fuzzy set performs as an efficient, flexible, and comprehensive representation [...] Read more.
The Fermatean fuzzy set, in contrast to other generalizations of fuzzy sets like PFS and IFS, has a wide range of acceptance for both MF and NMF. In light of this, the Fermatean fuzzy set performs as an efficient, flexible, and comprehensive representation in situations that lack certainty. Here, the weaker forms of Fermatean fuzzy sets are introduced, and their traits are analyzed. Decomposition and continuity of the Fermatean fuzzy α-open set are also accustomed. With the goal of safeguarding our green environment, hiring the best supplier is of the utmost significance in the construction industry. Using outranking techniques, Visual PROMETHEE Academic Edition 1.4 is a live multi-criteria decision aid software program. It runs virtual analysis through GAIA and applies selected criteria to contrast parameters. It also saves them for possible export and editing. In this article, the PROMETHEE II method is applied for Fermatean fuzzy numbers with FF(α,β)-level for selecting the optimal green supplier for a construction company. Because of its ability to handle vagueness, the FF PROMETHEE II method emerges as a valuable tool in Multi-criteria decision making. Furthermore, this study assesses the efficacy of the proposed technique by comparing its results with those obtained through other established methods. Full article
(This article belongs to the Special Issue Recent Developments in Fuzzy Control Systems and Their Applications)
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15 pages, 1387 KiB  
Article
Solving a Multimodal Routing Problem with Pickup and Delivery Time Windows under LR Triangular Fuzzy Capacity Constraints
by Jie Ge and Yan Sun
Axioms 2024, 13(4), 220; https://doi.org/10.3390/axioms13040220 - 26 Mar 2024
Cited by 3 | Viewed by 1725
Abstract
This study models a container routing problem using multimodal transportation to improve its economy, timeliness, and reliability. Pickup and delivery time windows are simultaneously formulated in optimization to provide the shipper and the receiver with time-efficient services, in which early pickup and delayed [...] Read more.
This study models a container routing problem using multimodal transportation to improve its economy, timeliness, and reliability. Pickup and delivery time windows are simultaneously formulated in optimization to provide the shipper and the receiver with time-efficient services, in which early pickup and delayed delivery can be avoided, and nonlinear storage periods at the origin and the destination can be minimized. Furthermore, the capacity uncertainty of the multimodal network is incorporated into the advanced routing to enhance its reliability in practical transportation. The LR triangular fuzzy number is adopted to model the capacity uncertainty, in which its spread ratio is defined to measure the uncertainty level of the fuzzy capacity. Due to the nonlinearity introduced by the time windows and the fuzziness from the network capacity, this study establishes a fuzzy nonlinear optimization model for optimization problem. A chance-constrained linear reformulation equivalent to the proposed model is then generated based on the credibility measure, which makes the global optimum solution attainable by using Lingo software. A numerical case verification demonstrates that the proposed model can effectively solve the problem. The case analysis points out that the formulation of pickup and delivery time windows can improve the timeliness of the entire transportation process and help to achieve on-time transportation. Furthermore, improving the confidence level and the uncertainty level increases the total costs of the optimal route. Therefore, the shipper and the receiver must prepare more transportation budget to improve reliability and address the increasing uncertainty level. Further analysis draws some insights to help the shipper, receiver, and multimodal transport operator to organize a reliable and cost-efficient multimodal transportation under capacity uncertainty through confidence level balance and transportation service and transfer service selection. Full article
(This article belongs to the Special Issue Recent Developments in Fuzzy Control Systems and Their Applications)
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12 pages, 270 KiB  
Article
Multi-Objective Non-Linear Programming Problems in Linear Diophantine Fuzzy Environment
by Salma Iqbal, Naveed Yaqoob and Muhammad Gulistan
Axioms 2023, 12(11), 1048; https://doi.org/10.3390/axioms12111048 - 13 Nov 2023
Viewed by 1358
Abstract
Due to various unpredictable factors, a decision maker frequently experiences uncertainty and hesitation when dealing with real-world practical optimization problems. At times, it’s necessary to simultaneously optimize a number of non-linear and competing objectives. Linear Diophantine fuzzy numbers are used to address the [...] Read more.
Due to various unpredictable factors, a decision maker frequently experiences uncertainty and hesitation when dealing with real-world practical optimization problems. At times, it’s necessary to simultaneously optimize a number of non-linear and competing objectives. Linear Diophantine fuzzy numbers are used to address the uncertain parameters that arise in these circumstances. The objective of this manuscript is to present a method for solving a linear Diophantine fuzzy multi-objective nonlinear programming problem (LDFMONLPP). All the coefficients of the nonlinear multi-objective functions and the constraints are linear Diophantine fuzzy numbers (LDFNs). Here we find the solution of the nonlinear programming problem by using Karush-Kuhn-Tucker condition. A numerical example is presented. Full article
(This article belongs to the Special Issue Recent Developments in Fuzzy Control Systems and Their Applications)
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