scholarly journals A Dynamic Type-1 Fuzzy Logic System for the Development of a New Warehouse Assessment Scheme (October 2020)

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Wafa' H. AlAlaween ◽  
Abdallah H. AlAlawin ◽  
Mahdi Mahfouf ◽  
Omar H. Abdallah
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Dynamic Type ◽  
Logic System

Set-Membership Type-1 Fuzzy Logic System Applied to Fault Classification in a Switch Machine

2017 ◽  
Vol 18 (10) ◽  
pp. 2703-2712 ◽  
Author(s):  
Eduardo P. de Aguiar ◽  
Fernando M. de A. Nogueira ◽  
Marley M. B. R. Vellasco ◽  
Moises V. Ribeiro
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Fault Classification ◽  
Set Membership ◽  
Logic System

scholarly journals Wall-Following Behavior for a Disinfection Robot Using Type 1 and Type 2 Fuzzy Logic Systems

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4445
Author(s):  
M. A. Viraj J. Muthugala ◽  
S. M. Bhagya P. Samarakoon ◽  
Madan Mohan Rayguru ◽  
Balakrishnan Ramalingam ◽  
Mohan Rajesh Elara
Keyword(s):  
Fuzzy Logic ◽  
Infectious Diseases ◽  
Fuzzy Logic System ◽  
Superior Performance ◽  
Fuzzy Logic Systems ◽  
Interval Type ◽  
Wall Following ◽  
Logic System

Infectious diseases are caused by pathogenic microorganisms, whose transmission can lead to global pandemics like COVID-19. Contact with contaminated surfaces or objects is one of the major channels of spreading infectious diseases among the community. Therefore, the typical contaminable surfaces, such as walls and handrails, should often be cleaned using disinfectants. Nevertheless, safety and efficiency are the major concerns of the utilization of human labor in this process. Thereby, attention has drifted toward developing robotic solutions for the disinfection of contaminable surfaces. A robot intended for disinfecting walls should be capable of following the wall concerned, while maintaining a given distance, to be effective. The ability to operate in an unknown environment while coping with uncertainties is crucial for a wall disinfection robot intended for deployment in public spaces. Therefore, this paper contributes to the state-of-the-art by proposing a novel method of establishing the wall-following behavior for a wall disinfection robot using fuzzy logic. A non-singleton Type 1 Fuzzy Logic System (T1-FLS) and a non-singleton Interval Type 2 Fuzzy Logic System (IT2-FLS) are developed in this regard. The wall-following behavior of the two fuzzy systems was evaluated through simulations by considering heterogeneous wall arrangements. The simulation results validate the real-world applicability of the proposed FLSs for establishing the wall-following behavior for a wall disinfection robot. Furthermore, the statistical outcomes show that the IT2-FLS has significantly superior performance than the T1-FLS in this application.

Design and application of Type-2 fuzzy logic system based on improved ant colony algorithm

2018 ◽  
Vol 40 (16) ◽  
pp. 4444-4454
Author(s):  
Zhifeng Zhang ◽  
Tao Wang ◽  
Yang Chen ◽  
Jie Lan
Keyword(s):  
Fuzzy Logic ◽  
Ant Colony Optimization ◽  
Ant Colony Algorithm ◽  
Fuzzy Logic System ◽  
Ant Colony ◽  
Original Algorithm ◽  
Interval Type ◽  
Logic System

In this paper, an improved ant colony optimization (IACO) with global pheromone update is proposed based on ant colony optimization (ACO), and it is used to design interval Type-2 TSK fuzzy logic system (FLS), including parameters adjustment and rules selection. The performance of the system can be improved by obtaining the optimal parameters and reducing the redundant rules. In order to verify the feasibility of the proposed method, the intelligent FLS is applied to predict the international petroleum price and the Zhongyuan environmental protection shares price. It is proved that the IACO can improve the efficiency of the original algorithm and accelerate the convergence speed. The simulations show that both IACO and ACO are feasible and have a high performance for the design of FLS. The simulation results compared with back-propagation design (BP algorithm) show that intelligent algorithms have an advantage over the classical algorithm, the simulation result compared with without rule-selection shows that reduced redundant rules can improve the performance, and the result compared with the Type-1 FLS shows that interval Type-2 TSK FLS has a better performance than the Type-1 TSK FLS.

Classification of Short Circuit GMA Welding using Type-1 and Singleton Fuzzy Logic System

2018 ◽  
Author(s):  
Rafaela Abreu Campos ◽  
Renan Piazzaroli Finotti Amaral ◽  
Ivan Fabio Mota de Menezes ◽  
Leonardo Goliatt da Fonseca ◽  
Moises Luiz Lagares ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Gma Welding ◽  
Short Circuit ◽  
Fuzzy Logic System ◽  
Logic System

scholarly journals Type-2 Fuzzy Logic in Pair Formation

2018 ◽  
Vol 10 (1) ◽  
pp. 94
Author(s):  
Lakshmi Shrinivasan ◽  
J. l R. Rao
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Ground Truth ◽  
Fuzzy Logic System ◽  
Pair Formation ◽  
Type Reduction ◽  
And Performance ◽  
Logic System

<span>This paper gives an overview of Type-2 Fuzzy sets (T2FSs) and Type-2 fuzzy Logic system (T2FLS) considering one aviation scenario. The existing type-1 Fuzzy system has limited capability to handle the uncertainty directly. In order to overcome the limitations of Type-1 fuzzy Logic system (T1FLS), a next level of fuzzy set is introduced, that is known as T2FSs. Here we will discuss about: Type-2 fuzzy sets, type-2 membership functions, inference engine, type reduction and defuzzification. Pair formation is the undertaken aviation scenario which is very critical in a fighting situation. Crisp data are taken by the sensors of aircraft and with the techniques of data fusion, a constant decision is passed whether two aircrafts can achieve pair formation or not. Experiments are evaluated and performance is compared with ground truth and existing T1FLS, which proves better in terms of decision making while a certain amount of uncertainty is present</span>.

Classification of Faults in Switch Machine using Type-1 and Non-singleton Fuzzy Logic System Trained by Hestenes and Stiefel's Conjugate Gradient Method

2017 ◽  
Author(s):  
Alexandre Queiroz Zamagna Bouhid ◽  
Renan Piazzaroli Finotti Amaral ◽  
Leonardo Goliatt da Fonseca ◽  
Eduardo Pestana de Aguiar
Keyword(s):  
Fuzzy Logic ◽  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Fuzzy Logic System ◽  
Logic System

scholarly journals AUTONOMOUS LANDING OF UAV: A COMPARISON BETWEEN TYPE-1 AND TYPE-2 FUZZY LOGIC SYSTEMS

2020 ◽  
Vol 5 (6) ◽  
Author(s):  
Eduardo Ravaglia Campos Queiroz ◽  
Rodrigo Perobeli Silva Costa ◽  
Fernando Luiz Cyrino Oliveira ◽  
André Luís Marques Marcato ◽  
Eduardo Pestana de Aguiar
Keyword(s):  
Fuzzy Logic ◽  
Unmanned Aerial Vehicles ◽  
Fuzzy Logic System ◽  
Fuzzy Logic Systems ◽  
Autonomous Landing ◽  
Precision And Accuracy ◽  
Object Of Study ◽  
Logic System

The Unmanned Aerial Vehicles (UAV) are an important technology with multiple applications. It is an object of study for researchers aiming to improve the performance of these vehicles, especially in flight stages as the landing. Therefore, this paper presents a method for the landing of a UAV based on Type-2 Fuzzy Logic System considering static targets. The advantage of this process is more precision and accuracy compared with Type-1 Fuzzy Logic System.

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