scholarly journals Kendali Posisi Motor DC Menggunakan Logika Fuzzy Interval Tipe 2

2021 ◽  
Vol 7 (1) ◽  
pp. 1-10
Author(s):  
Adnan Rafi Al Tahtawi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Dc Motor ◽  
Matlab Simulink ◽  
Footprint Of Uncertainty ◽  
Integral Error ◽  
Interval Type

Kendali posisi motor DC sangat diperlukan dalam berbagai sistem dinamik. Karaketristik kekokohan pengendalian menjadi salah satu hal yang harus dipertimbangkan dalam pengendalian posisi motor DC. Makalah ini bertujuan untuk mengusulkan metode pengendalian posisi motor DC menggunakan kendali Interval Type 2 Fuzzy Logic (IT2FL). Berbeda dengan pengendali logika fuzzy tipe 1, pengendali ini memiliki fungsi keanggotaan dengan Footprint of Uncertainty (FoU) di setiap variabel linguistik. Kelebihan inilah yang menyebabkan kendali logika fuzzy tipe 2 memiliki karakteristik kekokohan terhadap ketidakpastian parameter sistem. Penelitian ini menggunakan simulasi Matlab/Simulink untuk menunjukkan respon pengendalian dengan penambahan sinyal derau dan dua skenario FoU. Hasil simulasi menunjukkan bahwa pengendali IT2FL menghasilkan performa lebih baik dibandingkan pengendali logika fuzzy tipe 1 dalam mengatasi derau pengukuran. Pada pengendali IT2FL, FoU 0,2 menghasilkan integral error yang lebih kecil dibandingkan FoU 0,1 dengan selisih terkecil sebesar 0,001. Position control of DC motor is indispensable in various dynamic systems. Control robustness characteristics are one of the things that must be considered in controlling the position of a DC motor. This paper aims to propose a DC motor position control method using an Interval Type 2 Fuzzy Logic (IT2FL) controller. Unlike the type 1 fuzzy logic controller, this controller has a membership function with a Footprint of Uncertainty (FoU) in each linguistic variable. The benefits of it cause the type 2 fuzzy logic control to have robust characteristics against the uncertainty of system parameters. This study uses a Matlab / Simulink simulation to show the control response with the addition of a noise signal and two FoU scenarios. The simulation results show that the IT2FL controller produces better performance than the type 1 fuzzy logic controller in overcoming measurement noise. In the IT2FL controller, FoU 0.2 produces an integral error that is smaller than FoU 0.1 with the smallest difference of 0.001.

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.

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 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.

scholarly journals Stabilizing control of two-wheeled wheelchair with movable payload using optimized interval type-2 fuzzy logic

2020 ◽  
pp. 146134842097948
Author(s):  
Nurul Fadzlina Jamin ◽  
Nor Maniha Abdul Ghani ◽  
Zuwairie Ibrahim ◽  
Ahmad Nor Kasruddin Nasir ◽  
Mamunur Rashid ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Dynamic Algorithm ◽  
Logic Control ◽  
Stabilizing Control ◽  
Control Schemes ◽  
Interval Type

The control schemes of a wheelchair having two wheels with movable payload utilizing the concept of a double-link inverted pendulum have been investigated in this article. The proposed wheelchair has been simulated using SimWise 4D software considering the most efficient parameters. These parameters are extracted using the spiral dynamic algorithm while being controlled with interval type-2 fuzzy logic controller (IT2FLC). The robustness and stability of the implemented controller are assessed under different situations including standing upright, forward motion and application of varying directions and magnitudes of outer disturbances to movable (up and down) system payload. It is shown that the two-wheeled wheelchair adopted by the newly introduced controller has achieved a 94% drop in torque for both Link1 and Link2 and more than 98% fall in distance travelled in comparison with fuzzy logic control type-1 (FLCT1) controller employed in an earlier design. The present study has further considered the increased nonlinearity and complexity of the additional moving payload. From the outcome of this study, it is obvious that the proposed IT2FLC-spiral dynamic algorithm demonstrates better performance than FLCT1 to manage the uncertainties and nonlinearities in case of a movable payload two-wheel wheelchair system.

scholarly journals Design and Implementation of Type-2 Fuzzy Logic Controllers for the Position Control of a DC Servo Motor

2014 ◽  
Vol 7 (3) ◽  
pp. 120-130
Author(s):  
Mohammed Z. Al-Faiz ◽  
Mohammed S. Saleh
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Position Control ◽  
Time System ◽  
Real Time System ◽  
Real World Applications ◽  
Interval Type ◽  
Inherent Part

Uncertainty is an inherent part in controllers for real world applications. In this paper we compare the performance differences between type-1 and interval type-2 fuzzy logic (IT2FLC) controllers, with five and three term membership functions. The controllers are used to control a PM DC motor in a closed loop real time system. The performance of system with each controller to a step is recorded. The results showed that there is a statistical difference between the fuzzy logic type-1 and type-2 controllers. It is also found that a type-2 five term controller is as good as a type-1five term or type-2 three term controller

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