scholarly journals An Accurate Battery Charger SEPIC-Coupled Inductor Using Fuzzy Type 2

2021 ◽  
Vol 8 (1) ◽  
pp. 79
Author(s):  
Berliana Rahma Putri ◽  
Indhana Sudiharto ◽  
Farid Dwi Murdianto
Keyword(s):  
Fuzzy Logic ◽  
Solar Energy ◽  
Fuzzy Logic Controller ◽  
Lithium Ion ◽  
Electrical Energy ◽  
Solar Panel ◽  
Constant Current ◽  
Charging Current

Recently, the needs of electrical energy have increased in line with the increasing population in Indonesia. Electrical in order to save the use of fossil energy, renewable is used, namely solar energy. Solar energy depends on the conditions of sunlight and the temperature of the solar panel. So, if the solar panel is directly connected to the battery, it will cause the battery be damaged. To overcome this, a controlled DC-DC converter is needed to stabilize the solar panel output before connecting to the battery. The DC-DC converter that used is a SEPIC coupled inductor converter, this converter has the ability to increase efficiency, the output polarity is not reversed, and avoid input current ripple. The control used to adjust the output of the SEPIC converter is a type 2 fuzzy logic controller because it has ability to find a set point value faster than other control logics and can handle uncertainty better than a type 1 fuzzy logic controller. The output of the SEPIC converter is used for charging lithium ion battery with a capacity 12V 21Ah. The output value of the SEPIC converter is 12.6V for charging voltage and 7A for charging current. The method used for battery charging is the constant current constant voltage method (cc-cv).

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.

Implementation of the Type-2 Fuzzy Controller in PLC

2010 ◽  
Vol 164 ◽  
pp. 95-98 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Research Work ◽  
Problem Type ◽  
Object A ◽  
Develop Type ◽  
Linear Object

The main aim of the presented research work was to develop type-2 fuzzy logic controller, which by its own design should be “more intelligent” than type-1. Along with the intelligence it should provide better results in solving a particular problem. Type-2 fuzzy logic controller is not well-known and it is rarely used at present. The idea of type-2 fuzzy logic set was presented by Zadeh in 1975, shortly after the presentation of type-1 fuzzy set. At the beginning scientists and researchers worked on type-1. Only after developing type-1 the attention was directed towards the type-2. The first applications of type-2 fuzzy logic in control appeared in 2003. The fuzzy logic controller type-2 was tested experimentally by controlling a non-linear object: a shape memory alloy (SMA) actuator DM-01PL, made by Miga Motor company, which despite small size distinguishes itself by its 9 N strength. Comparison of experimental data of the fuzzy logic controller type-2 and type-1 clearly indicates the superiority of the former, particularly in reducing signal overshoots.

scholarly journals Type-1 and Type-2 Fuzzy Logic Controller Based Multilevel DSTATCOM Using SVM*

2016 ◽  
Vol 25 (1) ◽  
Author(s):  
Foudil BENZERAFA ◽  
Abelhalim TLEMÇANI ◽  
Karim SEBAA
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller

scholarly journals CC-CV Controlled Fast Charging Using Fuzzy Type-2 for Battery Lithium-Ion

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Ahmad Zidan Falih ◽  
Mohammad Zaenal Efendi ◽  
Farid Dwi Murdianto
Keyword(s):  
Energy Storage ◽  
Solar Energy ◽  
Alternative Energy ◽  
Lithium Ion ◽  
Buck Converter ◽  
Constant Current ◽  
Constant Voltage ◽  
Battery Lifetime ◽  
Fast Charging

Energy dependency is increasing along with the increase in population growth rate, while the fossil energy is decreasing. Alternative energy such as solar energy is one solution to provide renewable energy, but solar energy cannot provide an intense supply of energy. Therefore, the equipment needs an energy storage. The battery has important role in energy storage with the performance of the battery that need an attention. The method and type of battery used  must be considered to maintain battery lifetime and  reduce overcharging. The purpose of this research is to understand the process of fast charging the CC-CV (Constant Current Constant Voltage) method on Lithium-Ion battery which is expected to reduce battery overcharging. In this method, the current is maintained constant until certain conditions then followed by constant voltage to prevent overcharging. The voltage from the solar panel is very high, voltage reduction is needed as the charging voltage for the battery. The DC-DC Converter used is Buck Converter which is given Fuzzy Type-2 algorithm to maintain a current of 10 Ampere during CC conditions and  a voltage of 14.4 Volt during CV conditions with switch of CC conditions to CV conditions on SoC 99.25%.Keywords: battery charging, buck converter, CC-CV, lithium-ion, type-2 fuzzy.

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.

A survey of Type-2 fuzzy logic controller design using nature inspired optimization

2020 ◽  
Vol 39 (5) ◽  
pp. 6169-6179
Author(s):  
Fevrier Valdez ◽  
Oscar Castillo ◽  
Prometeo Cortes-Antonio ◽  
Patricia Melin
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Optimization Methods ◽  
Fuzzy Logic Controllers ◽  
Logic Control ◽  
Optimal Type ◽  
Logic Controllers

In this paper, we are presenting a survey of research works dealing with Type-2 fuzzy logic controllers designed using optimization algorithms inspired on natural phenomena. Also, in this review, we analyze the most popular optimization methods used to find the important parameters on Type-1 and Type-2 fuzzy logic controllers to improve on previously obtained results. To this end have included a summary of the results obtained from the web of science database to observe the recent trend of using optimization methods in the area of optimal type-2 fuzzy logic control design. Also, we have made a comparison among countries of the network of researchers using optimization methods to analyze the distribution and impact of the papers.

scholarly journals A Robust Interval Type-2 Fuzzy Logic Controller for Variable Speed Wind Turbines Based on a Doubly Fed Induction Generator

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 21
Author(s):  
Ahmed Vall Hemeyine ◽  
Ahmed Abbou ◽  
Anass Bakouri ◽  
Mohcine Mokhlis ◽  
Sidi Mohamed ould Mohamed El Moustapha
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Induction Generator ◽  
Great Success ◽  
Doubly Fed Induction Generator ◽  
Variable Speed ◽  
Doubly Fed ◽  
Interval Type

This paper presents an implementation of a new robust control strategy based on an interval type-2 fuzzy logic controller (IT2-FLC) applied to the wind energy conversion system (WECS). The wind generator used was a variable speed wind turbine based on a doubly fed induction generator (DFIG). Fuzzy logic concepts have been applied with great success in many applications worldwide. So far, the vast majority of systems have used type-1 fuzzy logic controllers. However, T1-FLC cannot handle the high level of uncertainty in systems (complex and non-linear systems). The amount of uncertainty in a system could be reduced by using type-2 fuzzy logic since it offers better capabilities to handle linguistic uncertainties by modeling vagueness and unreliability of information. A new concept based on an interval type-2 fuzzy logic controller (IT-2 FLC) was developed because of its uncertainty management capabilities. Both these control strategies were designed and their performances compared for the purpose of showing the control most efficient in terms of reference tracking and robustness. We made a comparison between the performance of the type-1 fuzzy logic controller (T1-FLC) and interval type-2 fuzzy logic controller (IT2-FLC). The simulation results clearly manifest the height robustness of the interval type-2 fuzzy logic controller in comparison to the T1-FLC in terms of rise time, settling time, and overshoot value. The simulations were realized by MATLAB/Simulink software.

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