Hasin Turnitin "Fuel Saving Strategy in Spark Ignition Engine Using Fuzzy Logic Engine Torque Control"

In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to control the throttle position entered by the driver to achieve optimal engine torque. An engine torque vs. throttle position and engine speed mapping for vehicles with economical function is used to build this control process regulation. From the simulation result, it can be concluded that this control strategy is very effective to reduce fuel consumption and simultaneously to optimize the engine performance

Fuel Saving Strategy in Spark Ignition Engine Using Fuzzy Logic Engine Torque Control

In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to control the throttle position entered by the driver to achieve optimal engine torque. An engine torque vs. throttle position and engine speed mapping for vehicles with economical function is used to build this control process regulation. From the simulation result, it can be concluded that this control strategy is very effective to reduce fuel consumption and simultaneously to optimize the engine performance

Fuel Saving Strategy in Spark Ignition Engine Using Fuzzy Logic Engine Torque Control

In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to control the throttle position entered by the driver to achieve optimal engine torque. An engine torque vs. throttle position and engine speed mapping for vehicles with economical function is used to build this control process regulation. From the simulation result, it can be concluded that this control strategy is very effective to reduce fuel consumption and simultaneously to optimize the engine performance

Optimization of Wind Farm Yaw Offset Angle using Online Genetic Algorithm with a Modified Elitism Strategy to Maximize Power Production

The wake interaction in a wind farm occurs when the front turbines block the flow of wind to the turbines behind them, causing a total power loss of approximately 10–25%. Wake interactions can be redirected to reduce bad impacts by optimizing the yaw offset angles. Optimization of the yaw offset angle can increase the total power of the wind farm by approximately 6–9%. However, the fluctuating wind flow angle in the environment causes the behavior of the wake interaction to change, making it difficult to optimize the yaw offset angles. Therefore, this study proposes an online genetic algorithm with a modified elitism strategy to overcome this problem. The contribution of this study is to improve the performance of the genetic algorithm by modifying the elitism strategy in order to optimize the yaw offset angle for each turbine adaptively to a wind farm operating in a dynamic environment. The optimal yaw offset angles are stored in the elite population for various wind flow angles and then reinserted into the search population in each generation according to the actual wind flow angles. A Gaussian-based analytical wake interaction model under a yawed condition developed by Shapiro is employed in this study to evaluate the total power of a wind farm. This study resulted in a convergence speed that was 3.8 times faster than the classical elitism strategy. At several wind flow angles of 270°, 315°, and 360°, an average power increase of 10.52% was obtained. This study shows that the modification of the elitism strategy can increase the convergence speed to adaptively track the optimal yaw offset angle at various wind flow angles, so that the average increase in wind farm power is 1.94% higher than in previous studies

FUEL SAVING STRATEGY IN SPARK IGNITION ENGINE USING FUZZY LOGIC ENGINE TORQUE CONTROL

In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to control the throttle position entered by the driver to achieve optimal engine torque. An engine torque vs. throttle position and engine speed mapping for vehicles with economical function is used to build this control process regulation. From the simulation result, it can be concluded that this control strategy is very effective to reduce fuel consumption and simultaneously to optimize the engine performance.Keywords: engine torque control, fuzzy logic, spark ignition engin

Hasil Turnitin "PERANCANGAN KONTROL OPTIMAL LINEAR QUADRATIC REGULATOR (LQR) DENGAN GLOWWORM SWARM OPTIMIZATION (GSO) UNTUK SISTEM SUSPENSI AKTIF MODEL KENDARAAN SEPEREMPAT"

Sistem suspensi pada kendaraan merupakan salah satu komponen penting. Sistem suspensi yang ideal dapat meminimalkan defleksi dan percepatan vertikal badan kendaraan yang menjamin kenyamanan dan ketahanan dalam berkendara untuk variasi kondisi permukaan jalan. Pada penelitian ini menggunakan kendali untuk menganalisis sistem suspensi aktif pada model kendaraan seperempat. Metode merupakan sebuah mekanisme untuk menentukan nilai gain LQR optimal dimana nilai variabel diagonal matriks bobot Q dan R pada LQR dihitung menggunakan GSO. Sistem suspensi aktif diuji dengan beberapa model gangguan yang diwakilkan oleh sinyal gundukan, random, dan sinusoidal. Hasil simulasi yang diperoleh yaitu perbandingan antara respon suspensi aktif yang menggunakan kontrol , LQR, dan suspensi pasif. Berdasarkan pengujian yang dilakukan, suspensi aktif dengan memiliki faktor kenyamanan dan ketahanan yang relatif lebih baik pada frekuensi 2-25 Hz[14]. Pada gangguan gundukan memberikan defleksi badan kendaraan sebesar 10,27 cm untuk , 12,22 cm untuk LQR, dan 13,68 cm untuk suspensi pasif. Saat gangguan random, suspensi aktif dengan memiliki performansi yang lebih baik dengan rata-rata percepatan sebesar 7,976 m/s2, dibandingkan dengan LQR sebesar 8,413 m/s2, dan suspensi pasif sebesar 8,803 m/s2

Hasil Turnitin "Design of color based object sorting through arm manipulator with inverse kinematics method"

Arm manipulator is one type of robot that is widely applied in the industrial world. Robots of this type are commonly used to help people in the hard work, dangerous or repetitive work. Arm manipulator application that has been widely used are for welding, painting, drilling, and displacement. There are two methods of motion in the arm manipulator development, they are forward kinematics and inverse kinematics. In this research, a 3 DOF arm manipulator prototype designed as sorting object by color. The arm manipulator's prototype using inverse kinematics motion in determining the position of the sorted object transfer. In sorting this object is used as a sensor photodiode detector and distinguishing colors object are sorted. The output of this research is to produce a 3 DOF arm manipulator prototype that can move and sort object by it's color. In this research, the average yield on a standard deviation is 0.866 cm for X axis and the Y axis is 1.197 cm. The standard deviation is obtained from 4 kinds of the test site sorting of object variations