scholarly journals Pengujian Monitoring On-Line Rumah Kaca Cerdas Berbasis Android

CYCLOTRON ◽  
2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Diana Rahmawati
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Light Output ◽  
Design Procedure ◽  
Integrated System ◽  
Air Humidity ◽  
System Testing ◽  
Set Point ◽  
Input Parameters ◽  
On Line

Abstrak— Rumah kaca yang didesain adalah rumah kaca cerdas berbasis android. Sistem kendali pada rumah kaca ini menggunakan kontrol logika fuzzy untuk mengatur parameter-parameter input suhu tanaman, kelembapan udara, kelembapan tanah, dan cahaya. Output berupa pompa, kipas, dan lampu. Sistem bekerja secara otomatis sesuai set point kebutuhan tanaman yang diinputkan. Jika parameter inputan berubah, sensor akan melaporkan ke sistem, dan sistem akan melakukan aksi sesuai yang diprogramkan, agar semua berjalan sesuai seperti set point. Sistem ini dihubungkan dengan android, sehingga petani dapat memonitor kondisi tanaman dalam rumah kaca secara on-line. Dalam prosedur perancangan, diperlukan pengujian sistem rangkaian yang dirakit. Akan dilakukan pengujian sistem per blok, dan kemudian dilakukan pengujian sistem terintegrasi. Hasil yang diperoleh, sistem bekerja dengan baik sesuai dengan aturan fuzzy.Kata kunci: monitoring, on-line, rumah kaca, android, fuzzyAbstract— The greenhouse that is designed is an intelligent greenhouse based on Android. The control system in this greenhouse uses fuzzy logic controls to set input parameters for plant temperature, air humidity, soil moisture, and light. Output in the form of pumps, fans and lights. The system works automatically according to the set point of the plants inputted. If the input parameters change, the sensor will report to the system, and the system will act according to the programmed, so that everything goes according to the set point. This system is connected to Android, so farmers can monitor the condition of plants in the greenhouse on-line. In the design procedure, an assembled circuit system is needed. System testing will be carried out per block, and then integrated system testing is carried out. The results obtained, the system works well according to fuzzy rules.Keywords: monitoring, online, greenhouse, android, fuzzy

Fuzzy Logic Control System for Micro-Hole Electrical Discharge Machining

2007 ◽  
Author(s):  
Chen-Chun Kao ◽  
Scott F. Miller ◽  
Albert J. Shih
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Ignition Delay ◽  
Fuzzy Logic Control ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Logic Control ◽  
Input Parameters ◽  
Micro Hole ◽  
Adaptive Fuzzy Logic

An advanced micro-hole electrical discharge machining (EDM) system with the adaptive fuzzy logic control and precision piezoelectric stage is developed in this study. A high-speed EDM monitoring system is implemented to measure the gap voltage, current, and ignition delay time, which are used to derive three input parameters, the average gap voltage, deviation of spark ratio, and change of deviation of spark ratio, for the fuzzy logic control. Servo displacement and speed of the piezoelectric stage during each data acquisition cycle are real-time synthesized by the adaptive fuzzy logic controller. Effects of the single and multiple input parameters, ignition delay threshold value, and maximum servo displacement and speed on the EDM drilling process are experimentally studied. Design of experiments (DOE) is applied to investigate the correlation of fuzzy logic control parameters. The optimal EDM parameter values are searched via the genetic algorithm. The optimal search result is experimentally validated. The fuzzy logic EDM control system has demonstrated the efficiency and stability in micro-hole drilling by reducing the frequency of irregular discharges and the drilling time.

scholarly journals Adaptive set-point control system for microbial cultivation processes

2016 ◽  
Vol 21 (2) ◽  
pp. 153-165 ◽  
Author(s):  
Donatas Levišauskas ◽  
Rimvydas Simutis ◽  
Vytautas Galvanauskas
Keyword(s):  
Control System ◽  
Operating Mode ◽  
Operating Conditions ◽  
Set Point ◽  
On Line ◽  
Point Control ◽  
Microbial Cultivation ◽  
Set Point Control ◽  
Fast Adaptation ◽  
Steady State Control

A control system for set-point control of microbial cultivation process parameters is developed, in which a tendency model is applied for controller adaptation to process nonlinearity and time-varying operating conditions. The tendency model is updated on-line and introduced into control algorithm for prediction of steady-state control action and returning of feedback controller. The control system was tested for controlling dissolved oxygen concentration in batch operating mode bioreactor under extreme operating conditions. In simulation experiments, the control system demonstrates fast adaptation, robust behaviour and significant improvement in control performance compared to that of fixed gain controller.

Hybrid Automatic Control System of the Cascade of Centrifugal Extractors

2015 ◽  
Vol 1084 ◽  
pp. 661-665
Author(s):  
Ekaterina P. Zelenetskaya ◽  
Alexey G. Goryunov
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Automatic Control ◽  
Automatic Control System ◽  
Human Factor ◽  
Current System ◽  
Neuro Fuzzy ◽  
Advanced Control ◽  
On Line ◽  
Negative Impacts

The paper provides a control system of the cascade of centrifugal extractors. This system is based on a conventional PID controller with elements of neuro-fuzzy logic for on-line tuning system. Neural networks used with fuzzy logic in an automatic control system allowed minimizing the negative impacts of human factor on the purification processes of uranium concentrates. The current system ensures the advanced control of a cascade and stabilization of the uranium concentration at the permissible industrial levels.

scholarly journals Sistem Kendali Nutrisi Hidroponik berbasis Fuzzy Logic berdasarkan Objek Tanam

2021 ◽  
Vol 9 (2) ◽  
pp. 263
Author(s):  
FITRIA SURYATINI ◽  
SUHARYADI PANCONO ◽  
SUSETYO BAGAS BHASKORO ◽  
PUTRI MUTHIA SARASWATI MULJONO
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Water Level ◽  
Farming System ◽  
Water Pump ◽  
Monitoring And Control ◽  
Level Control ◽  
Set Point ◽  
And Control ◽  
Parameter Monitoring

ABSTRAKHidroponik merupakan sistem pertanian yang menggunakan air sebagai media tanam sehingga tidak memerlukan media tanah ataupun area luas. Hidroponik memerlukan perlakuan khusus seperti menjaga kadar nutrisi dalam rentangnya sehingga penggunaan sistem kendali dapat mempermudah pemantauan dan pengaturan parameter. Sistem kendali yang digunakan adalah fuzzy logic mamdani dengan input offset kadar nutrisi dan level air, serta output durasi nyala motor pompa nutrisi dan air untuk mencapai set point yang dapat ditentukan melalui antarmuka berdasarkan database objek tanam atau slider manual. Hasil penelitian menunjukkan nilai keberhasilan sebesar 95,14% untuk kendali nutrisi dan 91,64% untuk kendali level air dalam mencapai set point, serta menghasilkan pertumbuhan tanaman yang lebih baik, dimana rata-rata penambahan tinggi antara sistem dengan dan tanpa kendali nutrisi memiliki perbedaan sebesar 1,96 cm.Kata kunci: sistem kendali, fuzzy logic, IoT, hidroponik, nutrisi ABSTRACTHydroponic is a farming system which uses water as planting media, so it is unnecessary to use soil nor consume wide area. Hydroponic requires special handlings such as maintaining nutrient measurement level within range so the use of control system may ease the parameter monitoring and control. The control system that is used is mamdani fuzzy logic with the nutrient measurement level offset and water level input, as well as nutrient and water pump motors activation duration output to reach the set point determined from the interface based on the planting-object database or manual slider. The results showed a success value of 95.14% for nutritional control and 91.64% for water level control in reaching set point, and resulting in better plant growth, where the average increase in height between the system with and without nutrient control has a difference of 1.96 cm.Keywords: control system, fuzzy logic, IoT, hydroponics, nutrient

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Development of On-line Integrated Stability Control System (ISC) for Long-distance Bulk Power Transmission

2013 ◽  
Vol 133 (4) ◽  
pp. 313-323 ◽  
Author(s):  
Kuniaki Anzai ◽  
Kimihiko Shimomura ◽  
Soshi Yoshiyama ◽  
Hiroyuki Taguchi ◽  
Masaru Takeishi ◽  
...  
Keyword(s):  
Control System ◽  
Power Transmission ◽  
Stability Control ◽  
Long Distance ◽  
Stability Control System ◽  
On Line ◽  
Bulk Power

Concept and principles of building an integrated system of management of activities of regional gas supply system entities Kaliningrad region

2019 ◽  
pp. 64-72
Author(s):  
G.G. Arunyants
Keyword(s):  
Control System ◽  
Natural Gas ◽  
Supply System ◽  
Integrated System ◽  
Software Complex ◽  
Geographically Distributed ◽  
Basic Solutions ◽  
Kaliningrad Region ◽  
And Control ◽  
Gas Supply

The results of analysis of problems of regulation of gas supply complex of Kaliningrad region and main ways to increase its efficiency, as well as basic solutions for creation of a software complex Т-GAZ-2 automated calculation of natural gas tariffs for ACS of gas supply system subjects, geographically distributed and information connected to the regional automated information and control system (RAIS).

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