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ENHANCING THE PERFORMANCE OF THE WALL-FOLLOWING ROBOT BASED ON FLC-GA Suwoyo, Heru; Tian, Yingzhong; Ibnu Hajar, Muhammad Hafizd
SINERGI Vol 24, No 2 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.2.008

Abstract

Determination of the improper speed of the wall-following robot will produce a wavy motion. This common problem can be solved by adding a Fuzzy Logic Controller (FLC) to the system. The usage of FLC is very influential on the performance of the wall-following robot. Accuracy in the determination of speed is largely based on the setting of the membership function that becomes the value of its input. So manual setting on membership function can still be enhanced by approaching the certain optimization method. This paper describes an optimization method based on Genetic Algorithm (GA). It is used to improving the ability of FLC to control the wall-following robot controlled by FLC. To provide clarity, the wall-following robot that controlled using an FLC with manual settings will be simulated and compared with the performance of wall-following robots controlled by a fuzzy logic controller optimized by a Genetic Algorithm (FLC-GA). According to comparative results, the proposed method has been showing effectiveness in terms of stability indicated by a small error.
SISTEM KONTROL PADA HYDROPONICS GROW ROOM DENGAN MENGGUNAKAN MODULE ESP8266-01 Saputra, Andrial; Ibnu Hajar, Muhammad Hafizd; Bahrain, Ahmad Rasikh
Jurnal Teknologi Elektro Vol 10, No 1 (2019)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (602.993 KB) | DOI: 10.22441/jte.v10i1.003

Abstract

Media tanaman yang digunakan pada penelitian ini adalah teknik hidroponik dengan memakai tanaman kangkung untuk media pengamatan yang akan dilakukan pada Hydroponics grow room menggunakan lampu LED Grow Light sebagai pengganti cahaya matahari. Dalam sistem kontrol ada 3 input yang akan di proses menjadi output adalah sensor DHT11 sebagai input untuk pembacaan hasil pada program arduino yang akan mengontrol relay terhadap kipas, sensor LDR sebagai input untuk pembacaan hasil pada program arduino yang akan mengontrol relay terhadap lampu, kemudian water level sensor sebagai input untuk pembacaan hasil pada program arduino yang akan mengontrol relay terhadap pompa. Pada sistem monitoring yang akan dihasilkan pada internet web Thinkspeak mempunyai 4 output dari sensor suhu DHT11, sensor kelembaban DHT11, sensor Ultrasonik HC-SR04 untuk mengukur ketinggian tanaman, dan water level sensor untuk mengukur ketinggian air pada baki. Hasil pada pengaturan kontrol otomatis sesuai dengan pembacaan data oleh arduino, yaitu kipas akan hidup (on) ketika suhu >300 dan kelembaban sebesar >60% pada Hydroponics Grow Room. Kemudian pada pompa air akan hidup (on) ketika ketinggian air pada baki hidroponik kurang dari 50 % sesuai dengan setpoint yang dibutuhkan. Selanjutnya adalah kontrol pada lampu LED grow light dan LED bulb ketika sensor LDR mencapai setpoint >500 dalam keadaan terang, dan <500 dalam keadaan gelap. Pada sistem monitoring melalui wifi module esp8266-01 yang terhubung hotspot internet mempunyai waktu update / menerima data di web Thingspeak rata-rata selama 2,4 detik dari waktu pengiriman data melalui arduino dan wifi module esp8266-01. Untuk hasil pengamatan pertumbuhan tanaman kangkung menggunakan pencahayaan LED bulbs memiliki pertumbuhan lebih pesat dibandingkan pertumbuhan tanaman kangkung menggunakan pencahayaan LED grow light. Faktor yang menyebabkan pertumbuhan menggunakan pencahayaan LED bulbs lebih cepat dibandingkan dengan pertumbuhan menggunakan LED grow light adalah adanya pengaruh dari hormon auksin. Jika terkena cahaya LED grow light, auksin menjadi tidak aktif, tetapi apabila terkena cahaya LED bulbs pengaruh auksin menjadi lebih aktif dan menghasilkan kondisi batang dan daun menjadi kuning pucat serta layu.
MONITORING OF ELECTRICAL SYSTEM USING INTERNET OF THINGS WITH SMART CURRENT ELECTRIC SENSORS Ibnu Hajar, Muhammad Hafizd; Dani, Akhmad Wahyu; Miharno, Satriyo
SINERGI Vol 22, No 3 (2018)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (198.163 KB) | DOI: 10.22441/sinergi.2018.3.010

Abstract

Electricity is one of the most important human needs. In the presence of electricity it can facilitate human work. But it should be noted that too large and uncontrolled electricity use will be wasteful and get high costs. The problem is that electricity is not monitored accurately, easily and efficiently. This study aims to design an electric current monitoring device with an IoT system. IoT is a concept with the ability to transfer data by network, no need humans to humans or humans to PCs. In this concept, the SCT 013-000 electric current sensor is connected to the load, it will be show electric current value in the LCD, if the electric current which is determined exceeds the capacity, Wemos D1 including Wifi ESP 8266 will be sending a notification to the telegram. The system has been implemented with ironing load for 3.29%, the dispenser load is 0.20% and Magicom's get load for 1.07%. The delay time also has been implemented in the relay for 1.50 second when relay is on and 0.78 second when relay is off. When the notification send to the telegram also have a delay for 6.2 second. So, monitoring of electrical system using internet of things with smart current electric sensors has been done.
ENHANCING THE PERFORMANCE OF THE WALL-FOLLOWING ROBOT BASED ON FLC-GA Suwoyo, Heru; Tian, Yingzhong; Ibnu Hajar, Muhammad Hafizd
SINERGI Vol 24, No 2 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (677.577 KB) | DOI: 10.22441/sinergi.2020.2.008

Abstract

Determination of the improper speed of the wall-following robot will produce a wavy motion. This common problem can be solved by adding a Fuzzy Logic Controller (FLC) to the system. The usage of FLC is very influential on the performance of the wall-following robot. Accuracy in the determination of speed is largely based on the setting of the membership function that becomes the value of its input. So manual setting on membership function can still be enhanced by approaching the certain optimization method. This paper describes an optimization method based on Genetic Algorithm (GA). It is used to improving the ability of FLC to control the wall-following robot controlled by FLC. To provide clarity, the wall-following robot that controlled using an FLC with manual settings will be simulated and compared with the performance of wall-following robots controlled by a fuzzy logic controller optimized by a Genetic Algorithm (FLC-GA). According to comparative results, the proposed method has been showing effectiveness in terms of stability indicated by a small error.
A CRANE ROBOT OF THREE AXES DIMENSIONAL USING TRAJECTORY PLANNING METHOD Pangaribowo, Triyanto; Ibnu Hajar, Muhammad Hafizd; Andika, Julpri; Juliyanto, Adi
International Journal of Advanced Technology in Mechanical, Mechatronics and Materials Vol 1, No 2 (2020)
Publisher : Institute for Research on Innovation and Industrial System (IRIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (692.135 KB) | DOI: 10.37869/ijatec.v1i2.20

Abstract

This study aims to design a crane robot that has good performance with good stability, good accuracy in the gripper clamping the object at the point of balance and reach the target location well. The crane controller is installed with US-100 ping sensor and proximity infrared sensor to detect position of object. The robot crane moves on the x , y and z axes or in three  dimensions using motors as actuator and  it can be adjusted with motor drive. The crane moves on the x and y axes using  DC motor and z axis using servo motor. The crane automatically moves when it detects an object. The crane's movement uses the trajectory determination method by maintaining speed. Finally, the average accuracy of the gripper clamping exactly at the midpoint of the object is 93%. The length of the object when it is clamped has an accuracy of 95%. The performance of the crane robot is evaluated to transfer an object to the destination location takes 11 seconds with a track length of 86.055 cm 
ROBOT PEMADAM KEBAKARAN BERBASIS WEMOS Wisnuputra, Yulianto; Ihsanto, Eko; Ibnu Hajar, Muhammad Hafizd
Jurnal Teknologi Elektro Vol 10, No 2 (2019)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (633.717 KB) | DOI: 10.22441/jte.v10i2.007

Abstract

IOT adalah sebuah paradigma baru yang bertujuan menjembatani kesenjangan antara dunia fisik dan perwakilannya dalam dunia digital. Terbatasnya tata ruang mengharuskan untuk memunculkan alat yang bisa menjangkau sudut-sudut ruangan yang tidak dapat dijangkau oleh manusia. Dari kebutuhan tersebut, maka dibuatlah robot pemadam kebakaran berbasis internet of things. Dengan penggunaan module microcontroller wemos, diharapkan dapat menggantikan sistem kabel LAN sebagai sarana untuk berkomunikasi data dari robot dengan aplikasi Blynk sehingga robot ini dapat menjangkau sudut-sudut ruangan dimana apabila menggunakan kabel sangat sulit untuk dijangkau. Robot pemadam kebakaran ini dirancang menggunakan microcontroller wemos. Microcontroller tersebut akan menjadi penghubung antara smartphone dengan rangkaian robot. Sistem penggerak robot menggunakan 2unit motor DC dengan transistor sebagai motor driver. Penyemprotan air menggunakan 1unit mini pump motor DC. Pengukuran suhu dan kelembapan dideteksi oleh sensor DHT11. Daya untuk menggerakan robot ini menggunakan 2 unit baterai 4.2 volt. Aplikasi yang digunakan adalah Blynk yang merupakan open source IoT server. Durasi pembacaan suhu dan kelembapan dilakukan selama 20 detik, dimana suhu dalam ruang adalah 29oC dengan kelembapan 70%.
AN FLC-PSO ALGORITHM-CONTROLLED MOBILE ROBOT Suwoyo, Heru; Tian, Yingzhong; Ibnu Hajar, Muhammad Hafizd
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.002

Abstract

The ineffectiveness of the wall-following robot (WFR) performance indicated by its surging movement has been a concerning issue. The use of a Fuzzy Logic Controller (FLC) has been considered to be an option to mitigate this problem. However, the determination of the membership function of the input value precisely adds to this problem. For this reason, a particular manner is recommended to improve the performance of FLC. This paper describes an optimization method, Particle Swarm Optimization (PSO), used to automatically determinate and arrange the FLC’s input membership function. The proposed method is simulated and validated by using MATLAB. The results are compared in terms of accumulative error. According to all the comparative results, the stability and effectiveness of the proposed method have been significantly satisfied.
AN FLC-PSO ALGORITHM-CONTROLLED MOBILE ROBOT Suwoyo, Heru; Tian, Yingzhong; Ibnu Hajar, Muhammad Hafizd
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.002

Abstract

The ineffectiveness of the wall-following robot (WFR) performance indicated by its surging movement has been a concerning issue. The use of a Fuzzy Logic Controller (FLC) has been considered to be an option to mitigate this problem. However, the determination of the membership function of the input value precisely adds to this problem. For this reason, a particular manner is recommended to improve the performance of FLC. This paper describes an optimization method, Particle Swarm Optimization (PSO), used to automatically determinate and arrange the FLC’s input membership function. The proposed method is simulated and validated by using MATLAB. The results are compared in terms of accumulative error. According to all the comparative results, the stability and effectiveness of the proposed method have been significantly satisfied.
AN FLC-PSO ALGORITHM-CONTROLLED MOBILE ROBOT Suwoyo, Heru; Tian, Yingzhong; Ibnu Hajar, Muhammad Hafizd
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.002

Abstract

The ineffectiveness of the wall-following robot (WFR) performance indicated by its surging movement has been a concerning issue. The use of a Fuzzy Logic Controller (FLC) has been considered to be an option to mitigate this problem. However, the determination of the membership function of the input value precisely adds to this problem. For this reason, a particular manner is recommended to improve the performance of FLC. This paper describes an optimization method, Particle Swarm Optimization (PSO), used to automatically determinate and arrange the FLC’s input membership function. The proposed method is simulated and validated by using MATLAB. The results are compared in terms of accumulative error. According to all the comparative results, the stability and effectiveness of the proposed method have been significantly satisfied.