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Generator merupakan salah satu jenis mesin listrik yang banyak digunakan pada sistem pembangkit tenaga listrik. Namun, seringkali generator memiliki efisiensi daya yang rendah akibat kondisi pembebanan maupun gangguan. Untuk mengoptimalkan daya generator, terdapat berbagai cara salah satunya dengan maximum power point tracking (MPPT). Pada penelitian ini, MPPT digunakan untuk memaksimalkan daya keluaran pada generator magnet permanen (PMSG). Penelitian ini bertujuan merancang dan membuat alat optimalisasi daya keluaran pada penyearah generator magnet permanen dengan kendali fuzzy logic control (FLC). Kendali FLC dirancang dengan masukan berupa error dan perubahannya. Setelah itu keluaran dari FLC akan berupa duty cycle yang akan menjadi masukan konverter DC-DC. Keluaran dari sistem ini berupa penambahan dan pengurangan duty cycle agar daya keluaran sama dengan daya masukan yang dapat dikendalikan oleh mikrokontroler Arduino Mega2560. Dari hasil pengujian, didapat bahwa MPPT telah berhasil menjejaki titik kerja keluaran dari penyearah sehingga mendapatkan daya keluaran hampir sama dengan daya masukan. Efisiensi yang didapat dari sistem dengan MPPT ini sebesar 94% jauh lebih baik daripada sistem tanpa MPPT sebesar 84%.

The configuration of the battery-supercapacitor as a hybrid power source (HPS) is one solution to overcome the limitations of battery life, such as in an electric vehicle. To achieve battery energy savings when a supercapacitor is added, a control scheme is needed. This paper proposes a battery-supercapacitor current sharing control scheme using Fuzzy Supervisory Control (FSC). The FSC is designed to determine how much current of the battery and supercapacitor need to discharge based on the current requirement of the load. The output of the FSC will produce a reference current which is then controlled in the main closed-loop control using a Proportional-Integral (PI) controller. The control signal in the form of a duty cycle is then used to regulate the battery-supercapacitor current through a DC/DC converter. This control scheme is tested using a resistive load change scenario both simulation and experimental. The results show that the battery-supercapacitor current can be controlled according to the loading conditions.

The presence of robots that can assist humans with heavy or dangerous work makes the need for robots more pressing at the moment. One type of robot needed is a robot arm, which is widely used in the manufacturing industry, such as in the assembly process and pick and place. The types of robotic arms used vary both in terms of configuration and the number of degrees of freedom. However, with different types of robotic arms, different models of movement are used. Therefore, research related to the modeling of the robotic arm continues to be carried out to obtain the appropriate movement of the robotic arm. One of the methods used as a first step in designing a robotic arm movement model is kinematics analysis. Kinematics analysis aims to analyze the movement of the robot arm without knowing what force causes the movement. This paper aims to produce an ideal movement model for the AX-12A 3-DoF robotic arm using forward kinematic and inverse kinematic analysis using two methods, the Denavit-Haterberg method and the geometric approach method. The difference from other papers is that this paper makes the kinematics model using Robotic, Vision, and Control (RVC) tools based on the Peter I. Corke model on MATLAB software first before implementing it on hardware. The results show that the error percentage for the forward kinematic model is 1.04% and the inverse kinematic is 0.76%, which means the two models achieved the target that the model’s error maximum must be less than 2%.

Pada sistem hidroponik deep flow technique (DFT), setiap umur dan jenis tanaman yang ditanam memerlukan total dissolved solids (TDS) dengan satuan ppm yang berbeda serta kegagalan tanaman dalam bertumbuh dapat terjadi jika nilai TDS tidak terpantau dengan baik. Tujuan dalam penelitian ini untuk membuat sistem kendali nilai TDS dengan metode fuzzy logic agar nilai TDS sesuai dengan kondisi tanaman yang ditanam serta membuat sistem pemantau nilai TDS dengan memanfaatkan Internet of Things (IoT) agar nilai TDS dapat terpantau dengan baik. Sistem ini menggunakan nilai error dan delta error yang didapat dari selisih nilai setpoint dengan sensor TDS SKU:SEN0244 sebagai masukan fuzzy logic. Keluaran sistem berupa durasi ON dan OFF relay yang terhubung dengan pompa air 12 VDC. Nilai setpoint dan bacaan sensor akan ditampilkan pada LCD serta ditampilkan juga pada aplikasi Android Blynk dengan menggunakan module WiFi NodeMCU ESP8266 sebagai wireless. Hasil pengujian dari sistem yang dirancang yaitu sensor TDS yang digunakan memiliki rata-rata error sebesar 0,165%. Pengendalian yang dirancang mampu menghasilkan nilai integral absolute error (IAE) terkecil sebesar 1119 pada setpoint 800 ppm dan integral time absolute error (ITAE) terkecil sebesar 4200 pada setpoint 1000 ppm.

Pengendalian Kecepatan Motor DC Menggunakan Metode Fuzzy Integral Controller

Process control is needed in various types of industries for production. The controlled process variables can be temperature, flow, pressure, and level. For this reason, an automatic control system with the right method is needed to produce quality products. This study aims to design and implement a steam pressure control system on a prototype heating tank using PID controller based on PLC. The pressure in the heating tank will be controlled to a set point of 10 kPa with a maximum steady-state error of 3%. PID control is designed using the Ziegler Nichols method which is then implemented on the PLC Omron CP1H with an MPX5500DP sensor to detect pressure. The results of the research obtained are that the PI controller can produce a better response when compared to the P and PID controllers. PI controller with parameters Kp = 1.23, Ti = 860, and Td = 0 can produce a response with a rise time of about 300 seconds and a steady-state error of 3.3%.

This study proposes a control method for servo motor position using a proportional-integral-derivative (PID) controller with particle swarm optimization (PSO). We use an AX-12 servo motor that is commonly used for robotic manipulator applications. The angular position of the servo motor will be controlled using the PID control method with PSO as a controller gain optimizer. Firstly, the transfer function model of the servo motor is generated using open-loop model identification. Then, the integral error of the closed-loop system is used as PSO input in producing PID controller gain. As an objective function of the PSO algorithm, the integral time absolute error (ITAE) index performance is used. The proposed controller was tested and compared with PID with the Ziegler-Nichols (ZN) method. We also conduct the hardware experiment using Arduino Uno as a microcontroller using one AX-12 servo motor on the base joint of the manipulator robot. Based on the simulation result, the PID-PSO controller can achieve the best control response performance if compared to PID-ZN with a rise time is less than 0.5 s, a settling time of fewer than 8 s, and an overshoot under 1.2%. The effectiveness of the proposed PID-PSO controller is also validated by hardware experimental results.

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.

In proton exchange membrane fuel cell (PEMFC) systems operating at low temperature, water management is important as it helps to improve cell performance. In this research paper, a three-dimensional, steady-state and non-isothermal model was established. The paper is aimed at investigating the effect of water flooding on the PEMFC performance. The Taguchi approach was proposed to obtain optimal levels and analyze the influence of different parameters, such as relative humidity (RH) on the anode and cathode sides, gas diffusion layer (GDL) porosity on the anode and cathode sides, temperature and pressure, respectively. To illustrate the effect of wet inlet gases, the relative humidity and the GDL porosity for the model were varied on both sides of the anode and cathode as follows: 10%, 30%, 50%, 70% and 90%. Therefore, our findings show that at the anode RH = 0% and 100%, the optimum levels were (L4, L5, L3 and L1) and (L1, L1, L5 and L4) for the relative humidity of the cathode, GDL porosity of the cathode, temperature and pressure, respectively, while at the cathode RH = 0% and 100%, the optimum levels were (L5, L5, L5 and L4) and (L1, L5, L1 and L4) for the relative humidity of the anode, GDL porosity of the anode, temperature and pressure, respectively. Consequently, the maximum power densities for the optimal combinations were found to be 0.727, 0.725, 0.135 and 0.111 for the anode RH = 0%, anode RH = 100%, cathode RH = 0% and cathode RH = 100%, respectively.

This paper presents a pair of portable wireless nodes for a smart agricultural system to control and monitor the agricultural parameters based on Internet of Things (IoT). This system utilizes low-cost wireless communication through an nRF24L01 module between the sensor node and the controller node. The sensor node is placed on the agricultural area with a Li-Ion battery as a power supply, while the controller node is placed at the control and monitoring station. On the sensor node, there is a YL-69 soil moisture sensor and DS18B20 temperature sensor, while in the controller node there is a relay that can set watering on/off condition. In the controller node, there is also an ESP8266 WiFi module that serves to send data to the internet cloud for user monitoring. Both hardware nodes are built in small and portable size. The experimental result shows that the sensor node can transmit soil moisture and temperature data via RF wireless communication to the controller node. Watering is done automatically based on the condition of sensor values. In addition, this system can also be monitored through a website interface, so the users can easily find out the condition of their plant as long as there is internet access.

Robot arm is often used in industry with various tasks, one of which is a pick and place. Rapid prototyping of robot arms is needed to facilitate the development of many industrial tasks, especially on a laboratory scale. This study aims to design a small-scale three degree of freedom (3-DoF) robot arm for pick and place mission using the inverse kinematics method. The mechanical robotic arm system is designed using Solidworks with four servo motors as the actuator. Arduino Mega 2560 is used as a microcontroller in which the inverse kinematic method is embedded. This method is used to move the robot based on the coordinates of the destination pick and place. The test results show that the robot arm can carry out the pick and place mission according to the target coordinates given with the largest average error of about 5 cm. While the error generated between the calculation and computation results is around 3%.