A Comparative Study of Dynamic Adaptation of Parameters in the GWO Algorithm Using Type-1 and Interval Type-2 Fuzzy Logic

2018 ◽  
pp. 3-16 ◽  
Author(s):  
Luis Rodríguez ◽  
Oscar Castillo ◽  
Mario García ◽  
José Soria
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Dynamic Adaptation ◽  
Interval Type

scholarly journals Application of Type-1 and Type-2 Fuzzy Logic Controller for The Real Swarm Robot

2019 ◽  
Vol 15 (06) ◽  
pp. 83 ◽  
Author(s):  
Ade Silvia Handayani ◽  
Nyayu Latifah Husni ◽  
Siti Nurmaini ◽  
Irsyadi Yani
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Complex Problem ◽  
The Real ◽  
Advantages And Disadvantages ◽  
Path Navigation ◽  
Swarm Robot ◽  
Interval Type

Navigation is one of the typical problem domains occurred in studying swarm robot. This task needs a special ability in avoiding obstacles.  This research presents the navigation techniques using type 1 fuzzy logic and interval type 2 fuzzy logic. A comparison of those two fuzzy logic performances in controlling swarm robot as tools for complex problem modeling, especially for path navigation is presented in this paper.  Each hierarchical of fuzzy logic shows its advantages and disadvantages.  For testing the robustness of type-1 fuzzy logic and interval type-2 fuzzy logic algorithms, 3 robots for the real swarm robot experiment are used.  Each is equipped with one compass sensor, three distance sensors, and one X-Bee communication module.  The experimental results show that type-2 fuzzy logic has better performance than type-1 fuzzy logic.

Interval Type-2 Fuzzy Logic Control of NM70 Shape Memory Actuator

2014 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Shape Memory ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Logic Control ◽  
Interval Type ◽  
Nonlinear Plant

The main aim of this article is to present the usage of type-2 fuzzy logic controller to control a shape memory actuator. To enhance real-time performance simplified interval fuzzy sets were used. The algorithm was implemented in the ATmega32 microcontroller. The dedicated PC application was also built. The fuzzy logic controller type-2 was tested experimentally by controlling position of the shape memory alloy actuator NM70 which despite its small size distinguishes itself by its strength. The obtained results confirmed that type-2 fuzzy controller performed efficiently with a difficult to control nonlinear plant. The research also proved that interval type-2 controllers, which are a simplified version of the general type-2 controllers, are very efficient. They can handle uncertainties without increasing drastically the computational complexity. Experimental data comparison of the fuzzy logic controller type-2 with type-1 clearly indicates the superiority of the former, especially in reducing overshooting.

On the robustness of Type-1 and Interval Type-2 fuzzy logic systems in modeling

2011 ◽  
Vol 181 (7) ◽  
pp. 1325-1347 ◽  
Author(s):  
Mohammad Biglarbegian ◽  
William Melek ◽  
Jerry Mendel
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Systems ◽  
Logic Systems ◽  
Interval Type

scholarly journals Enhancement of Non-Holonomic Leader-Follower Formation Using Interval Type-2 Fuzzy Logic Controller

2018 ◽  
Vol 14 (09) ◽  
pp. 124 ◽  
Author(s):  
Bambang Tutuko ◽  
Siti Nurmaini ◽  
Saparudin Saparudin ◽  
Gita Fadila Fitriana
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Formation Control ◽  
Fuzzy Logic Controller ◽  
Small Data ◽  
Hardware Failure ◽  
Fuzzy Process ◽  
Interval Type

Robotics control system with leader-follower approach has a weakness in the case of formation failure if the leader robot fails. To overcome such problem, this paper proposes the formation control using Interval Type-2-Fuzzy Logic controller (IT2FLC). To validate the performance of the controller, simulations were performed with various environmental systems such as open spaces, complexes, circles and ovals with several parameters. The performance of IT2FLC will be compared with Type-1 Fuzzy Logic (T1FL) and Proportional Integral and Derivative (PID) controller. As the results found using IT2FLC has advantages in environmental uncertainty, sensor imprecision and inaccurate actuator. Moreover, IT2FLC produce good performance compared to T1FLC and PID controller in the above environments, in terms of small data generated in the fuzzy process, the rapid response of the leader robot to avoid collisions and stable movements of the follower robot to follow the leader's posture to reach the target without a crash. Especially in some situations when a leader robot crashes or stops due to hardware failure, the follower robot still continue move to the target without a collision.

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.

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