scholarly journals Kontrol Keseimbangan Robot Hexapod EILERO menggunakan Fuzzy Logic

2021 ◽  
Vol 9 (3) ◽  
pp. 533
Author(s):  
IWAN KURNIANTO WIBOWO ◽  
DANY PREISTIAN ◽  
FERNANDO ARDILLA
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Balance Control ◽  
Inverse Kinematic ◽  
Hexapod Robot ◽  
Kinematic Modeling ◽  
Inclined Plane ◽  
Balance System ◽  
Data Feedback ◽  
Pitch Tilt

ABSTRAKPenelitian dengan topik robot hexapod telah banyak dikembangkan, namun sampai saat ini masih sedikit yang mengulas tentang kontrol keseimbangannya. Permasalahan yang kerap muncul adalah ketika robot berada dalam bidang miring, robot dapat terjatuh jika robot tidak dapat menyeimbangkan badan. Begitu pula dengan robot hexapod EILERO yang telah kami bangun. Untuk mengatasi permasalahan itu, selain pemodelan kinematik dan kinematika terbalik yang tepat, juga diperlukan suatu sistem keseimbangan yang baik. Dalam penelitian ini, kami menggunakan fuzzy logic untuk mengontrol keseimbangan robot EILERO dengan umpan balik data kemiringan dari sebuah sensor IMU. Setelah melalui beberapa pengujian yang komprehensif, didapatkan hasil bahwa robot dapat menyeimbangkan diri pada kondisi kemiringan papan pijakan antara -15° dan 15° pada orientasi kemiringan roll dan pitch. Robot mampu merespon dengan capaian steady state di bawah 3000 ms. Dengan demikian, robot EILERO semakin stabil dalam melintasi bidang yang tidak datar.Kata kunci: hexapod, EILERO, kinematika terbalik, fuzzy logic ABSTRACTResearch on the topic of the hexapod robot has been developed a lot, but until now there is little that has been discussed about balance control. The problem that often arises is that when the robot is on an inclined plane, the robot can fall if the robot cannot balance its body. Likewise with the EILERO hexapod robot that we have built. To solve this problem, besides proper kinematic modeling and inverse kinematic modeling, a good balance system is also needed. In this study, we used fuzzy logic to control the balance of the EILERO robot, with tilt data feedback from an IMU sensor. After going through several comprehensive tests, the results show that the robot can balance itself on the slope of the stepboards between -15 ° and 15 ° in the orientation of roll and pitch tilt. The robot is able to respond with steady state achievements below 3000 ms. Thus, the EILERO robot is increasingly stable in traversing uneven planes.Keywords: hexapod, EILERO, inverse kinematic, fuzzy logic

scholarly journals Rancang Bangun Farming Box Dengan Pengaturan Suhu Menggunakan Fuzzy Logic Controller

ELKHA ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 92
Author(s):  
Riza Agung Firmansyah ◽  
Dani Junianto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Air Temperature ◽  
Temperature Control ◽  
Fuzzy Logic Controller ◽  
Pulse Width Modulation ◽  
Data Feedback ◽  
Shipping Containers ◽  
Fan Speed ◽  
State Error

Implementation of control systems has been carried out in many fields of science. One of it applications is in the agriculture fields. In this research we implemented a control system on farming in a box. Farming in a box is a system that uses old shipping containers for the purpose of growing plants in any environment. Inside shipping containers is fully assembled hydroponic pipe with air temperature control. In this research was built a little farming box from acryclic to imitate a shipping container. Main focus of this research is design an air temperature control using fuzzy logic controller. Fuzzy logic controller was choosen because many existing farming box use on off controller. In some application, fuzzy logic controller has better performance than on off controller. Farming box temperature is controlled by blowing cool air using an electric fan. In this case, cool air is produced by cold side of peltier. Electric fan speed is controlled by pulse width modulation signal (PWM) that generated from microcontroller. Air temperature data feedback is obtained from DHT 11 sensor that installed in a acrylic box. Sensor is physically connected with microcontroller and Fuzzy logic controller is embedded in microcontroller as an algorithm. Fuzzy logic controller was design with error temperature and error difference as an input, and duty cycle of PWM signal as output. Fuzzy logic controller system performs to reduce the temperature from 31,6 ° C to set poin 28° C in 71 seconds. Steady state error obtained by 1.28% and better than uncontrolled system that obtain steady state error 7,14%.

Continuous Estimation of CO2 Production during Exercise

1997 ◽  
Vol 36 (04/05) ◽  
pp. 368-371
Author(s):  
R. Soma ◽  
Y. Yamamoto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Infusion Rate ◽  
Feedback System ◽  
Whole Body ◽  
Co2 Production ◽  
Cycle Exercise ◽  
Continuous Estimation ◽  
Breath Measurement ◽  
13Co2 Enrichment

Abstract.A new method was developed for continuous isotopic estimation of human whole body CO2 rate of appearance (Ra) during non-steady state exercise. The technique consisted of a breath-by-breath measurement of 13CO2 enrichment (E) and a real-time fuzzy logic feedback system which controlled NaH13CO3 infusion rate to achieve an isotopic steady state. Ra was estimated from the isotope infusion rate and body 13CO2 enrichment which was equal to E at the isotopic steady state. During a non-steady state incremental cycle exercise (5 w/min or 10 w/min), NaH13CO3 infusion rate was successfully increased by the action of feedback controller so as to keep E constant.

STABILISASI TEGANGAN KELUARAN BUCK CONVERTER DENGAN METODE FUZZY LOGIC CONTROLLER

JURNAL ELTEK ◽  
2018 ◽  
Vol 16 (2) ◽  
pp. 125
Author(s):  
Oktriza Melfazen
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Buck Converter ◽  
Settling Time

Buck converter idealnya mempunyai keluaran yang stabil, pemanfaatandaya rendah, mudah untuk diatur, antarmuka yang mudah dengan pirantiyang lain, ketahanan yang lebih tinggi terhadap perubahan kondisi alam.Beberapa teknik dikembangkan untuk memenuhi parameter buckconverter. Solusi paling logis untuk digunakan pada sistem ini adalahmetode kontrol digital.Penelitian ini menelaah uji performansi terhadap stabilitas tegangankeluaran buck converter yang dikontrol dengan Logika Fuzzy metodeMamdani. Rangkaian sistem terdiri dari sumber tegangan DC variable,sensor tegangan dan Buck Converter dengan beban resistif sebagaimasukan, mikrokontroler ATMega 8535 sebagai subsistem kontroldengan metode logika fuzzy dan LCD sebagai penampil keluaran.Dengan fungsi keanggotaan error, delta error dan keanggotaan keluaranmasing-masing sebanyak 5 bagian serta metode defuzzifikasi center ofgrafity (COG), didapat hasil rerata error 0,29% pada variable masukan18V–20V dan setpoint keluaran 15V, rise time (tr) = 0,14s ; settling time(ts) = 3,4s ; maximum over shoot (%OS) = 2,6 dan error steady state(ess) = 0,3.

Research on Dynamic Balance Method of Precision Centrifuge

2014 ◽  
Vol 945-949 ◽  
pp. 777-780
Author(s):  
Tao Liu ◽  
Yong Xu ◽  
Bo Yuan Mao
Keyword(s):  
Mathematical Model ◽  
Balance Control ◽  
Dynamic Balance ◽  
Dynamic Balancing ◽  
Structure Characteristics ◽  
Balance System ◽  
Simulation Results ◽  
Set Up ◽  
System Controller ◽  
The Mathematical Model

Firstly, according to the structure characteristics of precision centrifuge, the mathematical model of its dynamic balancing system was set up, and the dynamic balancing scheme of double test surfaces, double emendation surfaces were established. Then the dynamic balance system controller of precision centrifuge was designed. Simulation results show that the controller designed can completely meet the requirements of precision centrifuge dynamic balance control system.

The flow of a micropolar liquid layer down an inclined plane

1968 ◽  
Vol 64 (2) ◽  
pp. 513-526 ◽  
Author(s):  
A. J. Willson
Keyword(s):  
Thin Films ◽  
Steady State ◽  
Liquid Layer ◽  
Stability Criterion ◽  
Long Waves ◽  
Inclined Plane ◽  
The Stability ◽  
Micropolar Liquid

AbstractConsideration is given to the flow of a micropolar liquid down an inclined plane. The steady state is analysed and Yih's technique is employed in an investigation of the stability of this flow with respect to long waves. Detailed calculations are given for thin films and it is shown that the micropolar properties of the liquid play an important role in the stability criterion.

Application of a Fuzzy Logic Controller for Speed Control on a Small-Scale Turbojet Engine

2014 ◽  
Author(s):  
Serdar Üşenmez ◽  
Sinan Ekinci ◽  
Oğuz Uzol ◽  
İlkay Yavrucuk
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Transient Response ◽  
Fuzzy Logic Controller ◽  
Electronic Control Unit ◽  
Small Scale ◽  
Gas Temperature ◽  
Fuel Pump ◽  
Fuel Flow ◽  
Turbojet Engine

Having a small-scale turbojet engine operate at a desired speed with minimum steady state error, while maintaining good transient response is crucial in many applications, such as UAVs, and requires precise control of the fuel flow. In this paper, first the mathematical model of a Small-Scale Turbojet Engine (SSTE) is obtained using system identification tests, and then based on this model, a classical PI controller is designed. Afterwards, to improve on the transient response and steady state performance of this classical controller, a Fuzzy Logic Controller (FLC) is designed. The design process for the FLC employs logical deduction based on knowledge of the engine behavior and iterative tuning in the light of software- and hardware-in-the-loop simulations. The classical and fuzzy logic controllers are both implemented on an in-house, embedded Electronic Control Unit (ECU) running in real time. This ECU is an integrated device carrying a microcontroller based board, a fuel pump, fuel line valves, speed sensor and exhaust gas temperature sensor inputs, and starter motor and glow plug driver outputs. It mainly functions by receiving a speed reference value via its serial communication interface. Based on this reference, a voltage is calculated and applied to the fuel pump in order to regulate the fuel flow into the engine, thereby bringing the engine speed to the desired value. Pre-defined procedures for starting and stopping the engine are also automatically performed by the ECU. Further, it connects to a computer running an in-house comprehensive Graphical User Interface (GUI) software for operating, monitoring, configuration and diagnostics purposes. The designed controllers are used to drive a generic SSTE. Reference inputs consisting of step, ramp and chirp profiles are applied to the controllers. The engine response using both controllers are recorded and inspected. The results show that the FLC exhibits a comparable performance to the classical controller, with possible opportunities to improve this performance.

scholarly journals Evaluasi Performa Fuzzy Logic Controller untuk mengatur kecepatan Motor DC Penguatan Terpisah

2020 ◽  
Vol 12 (2) ◽  
pp. 100-110
Author(s):  
Muhammad Aditya Ardiansyah ◽  
Renny Rakhmawati ◽  
Hendik Eko Hadi Suharyanto ◽  
Era Purwanto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Duty Cycle ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Boost Converter ◽  
Voltage Source ◽  
Single Output ◽  
Multiple Input ◽  
State Error

Beragamnya metode yang ditawarkan oleh fuzzy logic kontroller membuat sebagaian orang meneliti mengenai perbedaan metode inferensi yang digunakan oleh fuzzy logic controller. Sejauh ini terdapat tiga metode fuzzy logic kontroller yang telah dikembangkan yaitu Mamdani, Sugono dan Sukamoto. Pada jurnal ini penggunaan fuzzy logic kontroller akan dievaluasi dengan menggunakan motor dc penguat terpisah sebagai beban untuk melakukan pengaturan kecepatan motor dc. Pada paper ini tujuan utamanya adalah dapat mengendalikan kecepatan dari motor DC Penguatan Terpisah dengan mengatur tegangan jangkar dari motor tersebut. DC motor merupakan salah satu jenis motor memiliki banyak aplikasi dan memiliki kemudahan untuk mengatur kecepatan pada motor tersebut. Logika fuzzy yang digunakan pada studi ini adalah inferensi sugeno dimana dengan konfigurasi Multiple Input Single Output (MiSo). Dimana input berupa error dan perubahan error dan output berupa duty cycle dikarenakan yang dikendalikan oleh logika fuzzy adalah Boost Converter selaku controlled voltage source. Target pada jurnal ini adalah dari kecilnya nilai steady – state error dan minimnya osilasi sehingga mampu membuat sistem lebih stabil. Pada studi ini, Hasil pengujian dilakukan dengan menggunakan Simulink by Matlab dengan Hasil pengujian berupa error rata rata sebesar 5.36%.

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