MODELING OF HOT OIL LEAKAGE AT REGENERATION GAS HEATER ON DEHYDRATION PROCESS OF NATURAL GAS LIQUIFIED EXTRACTION (NGLE) GAS PLANT

The regeneration process in saturated dehydrator after working to drying the gas in the dehydration unit in the Natural Gas Liquified Extraction (NGLE) plant. This process is through the heating dehydrator process by flowing the regeneration gas into the dehydrator slowly (rump up temperature) until it reaches the heating temperature,and then holding the condition. Its condition is in accordance with the engineering design and followed by a rump down temperature which the dehydrator will be cooled down and ready for the dehydration process. This regeneration process works automatically in accordance with the engineering design which runs following the logic control that has been implemented into the Distributed Control System (DCS) in the Control Room. All order in DCS to obtain gas that has been moisture limited value which is allowed to be extracted. Regeneration gas was taken from the heat exchange between hot oil and regeneration gas in the regeneration gas heater package. This operation happend when the rump up temperature leaks the hot oil in the flange fitting of the regeneration gas heater package, its causes oil spillage (engineering design standart operation procedur). Its analysis case assumed the leakage is caused by thermal shock in the fittings of regeneration gas heater package in 2 % hot oil supply. To eliminate the thermal shock, a simulation of new models engineering design is initial by opening of the hot oil supply to the regeneration gas heater was changes with increasing its opening during stand-by conditions from 2% with a temperature at 45.72°C to 5% with a temperature at 51.61C in the Distributed Control System (DCS) logic control. The results goals with this implementation are no more hot oil leaks occur in the regeneration gas heater package. New models engineering design is stopping hot oil spillage, and maintaining operational continuity without having to spend money on repairing the regeneration gas heater package. process run in new models of engineering design, and this model becomes the new standard operating in start-up and commissioning plant process.

Diagnosis of Gasoline Injection Engine and Fault Tolerant Control

The paper presents some considerations regarding the diagnosis and control of a gasoline injection engine for motor vehicles. The growing importance of diagnosis is highlighted in the conditions in which the practice has shown that there are always some faults, the fault being defined as a deviation of a parameter or a variable from its nominal value. Here are some solutions used in the gasoline injection engine, related to fault tolerant control. It is exemplified by treating the air pressure control system admitted in the engine cylinders of the Audi A6 car, targeting the pressure sensor in the intake manifold. Keywords: motor vehicle, diagnosis, fault tolerant control (FTC), PID controller, fuzzy logic, control reconfiguration

Implementasi Fuzzy Logic Control Untuk Pemberi Pakan Ayam Otomatis Pada Ayam Broiler Dengan Menggunakan Teknologi IoT

Implementasi Metode Fuzzy Logic Control Untuk Pemberian Makan Ayam Broiler Secara Otomatis Menggunakan Teknologi Internet of Things; Husyainus Sobri, 172410102013, 2021, Program Studi Teknologi Informasi, Fakultas Ilmu Komputer, Universitas Jember. Ayam broiler atau disebut juga ayam pedaging merupakan ayam ras unggul hasil persilangan dari bangsa ayam yang memiliki produktivitas tinggi terutama dalam menghasilkan daging ayam. Ayam broiler merupakan hasil persilangan dan sistem lestari sehingga kualitas genetiknya dapat dikatakan baik. Kualitas genetik yang baik akan muncul secara optimal jika ayam diberikan faktor lingkungan yang mendukung, misalnya pemberian pakan yang baik agar ayam terhindar dari kematian dan kekurangan bobot ayam. Penggunaan teknologi dalam pemberian pakan ayam merupakan cara yang efektif untuk meningkatkan kualitas ayam yang baik dan menghindari kematian ayam. Teknologi yang digunakan dapat mengatur waktu makan secara otomatis dan memberi makan yang sesuai. Untuk membuat teknologi bekerja secara otomatis, diperlukan metode pengambilan keputusan. Salah satu metode yang cocok adalah Fuzzy Logic Control. Metode Fuzzy Logic Control dapat mengatasi keragaman parameter feeding untuk mengambil keputusan.

LQR and Fuzzy Logic Control for the Three-Area Power System

The three-area power system is widely considered a suitable example to test load frequency control of the distributed generation system. In this article, for such a system, for the power stabilization task, we introduce two controllers: Linear Quadratic Regulator (LQR), which is model-based, and Fuzzy Logic Controller (FLC), which is data-based. The purpose is to compare the two approaches from the point of view of (i) ease of implementation and tuning, and (ii) robustness to changes in the model. The model, together with controls strategies, has been implemented in the MATLAB software. Then, it has been tested for different simulation scenarios, taking into account the disturbances and faulty tie-lines between areas. Various quality measures allow to compare the performance of each control strategy. The comparison in terms of parameter change and load disturbances prompt us to propose suitable metrics and advice notes on the application of each controller.

Implementation of new hybrid evolutionary algorithm with fuzzy logic control approach for optimization problems

The main purpose of using the hybrid evolutionary algorithm is to reach optimal values and achieve goals that traditional methods cannot reach and because there are different evolutionary computations, each of them has different advantages and capabilities. Therefore, researchers integrate more than one algorithm into a hybrid form to increase the ability of these algorithms to perform evolutionary computation when working alone. In this paper, we propose a new algorithm for hybrid genetic algorithm (GA) and particle swarm optimization (PSO) with fuzzy logic control (FLC) approach for function optimization. Fuzzy logic is applied to switch dynamically between evolutionary algorithms, in an attempt to improve the algorithm performance. The HEF hybrid evolutionary algorithms are compared to GA, PSO, GAPSO, and PSOGA. The comparison uses a variety of measurement functions. In addition to strongly convex functions, these functions can be uniformly distributed or not, and are valuable for evaluating our approach. Iterations of 500, 1000, and 1500 were used for each function. The HEF algorithm’s efficiency was tested on four functions. The new algorithm is often the best solution, HEF accounted for 75 % of all the tests. This method is superior to conventional methods in terms of efficiency