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Journal of Fuzzy Systems and Control (JFSC)
Published by Peneliti Teknologi Teknik Indonesia
ISSN : 29866537     EISSN : -     DOI : https://doi.org/10.59247/jfsc.v1i1.24
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Journal of Fuzzy Systems and Control is an international peer review journal that published papers about Fuzzy Logic and Control Systems. The Journal of Fuzzy Systems and Control should encompass original research articles, review articles, and case studies that contribute to the advancement of the theory and application of fuzzy systems and control, and their integration with other technologies, such as artificial intelligence, machine learning, and optimization.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 6 Documents
 1 
Search results for , issue "Vol. 1 No. 1 (2023)" : 6 Documents clear
Adaptive Fuzzy-PI for Induction Motor Speed Control Hari Maghfiroh; Joko Slamet Saputro; Fahmizal Fahmizal; Muhammad Ahmad Baballe
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.24

Abstract

An induction motor (IM) is one type of AC motor which widely used. IM is chosen due to its simplicity, reliability, efficiency, and low cost. There are many methods proposed to control the speed of IM which is known as variable speed drive (VFD). In this study, the DTC method is used since it is more robust to the parameter’s changes. The combination of the Fuzzy and PI method is used in speed control. PID performances decrease when the system condition changes. Therefore, fuzzy is used as an adaptive algorithm to vary the PID gain. It was superior in terms of settling time, overshoot/ undershoot, and IAE compared to the PI method. It has lower IAE in both speed tracking and loaded conditions by 44.98% and 4.47%, respectively.
Implementation of Fuzzy Logic Control on a Tower Copter Fahmizal; Daffa Yanu Kharisma; Subuh Pramono
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.25

Abstract

Air transport has become a major attraction for scientists in the last decade, to carry out developments in the fields of firefighting, military, and commercial purposes. A quadcopter is a helicopter with four rotors. There are four arms connected to the main control and each arm has a motor with a rotor. In this study, the position control of a tower control is presented. A Fuzzy Logic Controller (FLC) is proposed, and it performance is compared with PID control. The hardware implementation test shows that FLC is superior to PID. The hardware testing shows that the settling time of the FLC control response is 0.5s while the PID control response is 1.2s. That means FLC settling time is faster by 58.33% compared to PID.
DC Motor Speed Control with Proportional Integral Derivative (PID) Control on the Prototype of a Mini-Submarine Qolil Ariyansyah; Alfian Ma'arif
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.26

Abstract

DC (Direct Current) motors are widely used as controllers in the industrial and robotics fields. In the rotation of the DC motor, there is still an unstable rotational speed so that a controller is needed to be able to stabilize the speed at the rotation of the DC motor. The control used in this study used the PID (Proportional Integral Derivative) control method. The PID control system works by processing calculations based on control variables Kp, Ki, and Kd to achieve conditions according to the expected setpoints. To achieve the expected conditions, the trial and error method is used. PID control in this study was implemented on a DC motor with a brushed type using an Arduino Mega microcontroller. The speed of the DC motor is read by the encoder sensor and entered in the PID equation. The output of the PID value will produce data in the form of PWM (Pulse Width Modulation) which will be the input of the L298N driver via Arduino Mega. The DC motor will produce a rotational speed in the form of RPM (Revolution Per Minute) data up to the specified set point. The implementation of PID was produced by giving parameter values to Kp, Ki, and Kd. The best PID parameter usage in this study was in the form of Kp = 0.6; Ki=0.3; and Kd=0.01. The application of the PID parameter obtains a stable system response curve at a predetermined set point. The resulting Kp, Ki, and Kd parameter data is used as graph data in MATLAB software.
Mecanum 4 Omni Wheel Directional Robot Design System Using PID Method Muhammad Alfiyan; Riky Dwi Puriyanto
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.27

Abstract

Robot or Artificial Intelligence (AI) can be interpreted as a machine with some computer intelligence and controlled by a computer, and has physical abilities like humans. One of the drives of robots that is often used is a DC motor, a DC motor is a motor with an electronic device that converts electrical energy into kinetic energy or motion. However, DC motors often experience a decrease due to the existing load, so that the speed becomes not constant, so it is necessary to design a controller. The controller used is Proportional Integral Derivative (PID). In the PID there are several parameters such as , , and which are selected or determined so that the plant characteristics match the desired criteria. The general parameters are rise-time, settling-time, maximum, overshoot, and steady-state error for a given input. From the results of the DC motor speed control test using the PID method which was carried out by trial and error testing of the four DC motors, the best PID value was obtained with ; ; ; and with the Rise Time system message: 14.7452; Overshoots: 0.6667; Settling Time: 52.0100; Undershot: 0; Settling Min: 136; Peaks: 151; Settling Max : 151; and Peak Time: 65.
PID Control of Magnetic Levitation (Maglev) System Muhammad Arif Seto; Alfian Ma'arif
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.28

Abstract

Magnetic levitation is a process of drifting or shifting an object with a certain reference, by creating a repulsive force from the gravity of an object caused by an electromagnetic field without noise. In modern times like today, with the density of community activities, especially those living in urban areas, it is necessary to be able to carry out activities efficiently as well as quickly.  Therefore, the reason for many people to be able to find an innovative solution to make it easier for humans to carry out their activities. One of the innovations that can be a solution to the limited space and time is in the development of magnetic levitation technology. The system that will be used in controlling this maglev is to use a PID controller. Using this PID control will be tested with several , , and  values with a setpoint of 950. At the initial tunning with the values  =2,  =0.01, and  =2. Then in the second test using the values  =3,  =0.1, and  =0.3. Software testing is also carried out using matlab. The exact PID value for controlling an elevated object can be found by changing the value of the , , and  values that can be searched through a matlab software in the PID tunner feature, which can then be seen the PID tunning results by analyzing the graph that will be displayed by the PID tunner.
Hydraulic Power System Control using State Feedback Controller (SFC) Fahmizal; Jimmy Trio Putra; Sekar Fatimawardhani; Hari Maghfiroh
Journal of Fuzzy Systems and Control Vol. 1 No. 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i1.30

Abstract

In an electrical network, generators work and provide power to the loads. When the load on the generator increases, the speed of the generator decreases then resulting in a reduction in the frequency of the network. This paper was designed within the state feedback controller (SFC) to improve the hydraulic power system performance. The performance of the proposed controller is compared with simple feedback controller (FC) in the simulation environment. The load variation was tested which is 5%, 10%, and 20% variation. The testing results show that in terms of steady state error (SSE) and overshoot, the SFC is superior. In terms of settling time, the FC method is faster. Since it quickly reaches steady event not getting into set-point. The overall, it can be concluded that SFC can give better performance than FC in the frequency control of a hydraulic power system.

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