scholarly journals Application of SCADA System by Using (Fuzzy Logic Controller) on the Cathodic Protection System for Oil Pipelines.

2021 ◽  
Vol 11 (1) ◽  
pp. 53-68
Author(s):  
Jasim A. Harbi
Keyword(s):  
Fuzzy Logic ◽  
Cathodic Protection ◽  
Fuzzy Logic Controller ◽  
Open Loop ◽  
Scada System ◽  
Oil Pipelines ◽  
Impressed Current ◽  
Cathodic Protection System ◽  
High Level ◽  
And Control

This study is dedicated to design and execute Supervisory Control and Data Acquisition system(SCADA) to monitor and control the corrosion of a pipeline buried under ground. Amicrocontroller equipped with many sensors and communication system used to control andmonitor the process of an impressed current cathodic protection ICCP process for pipeline. Thecombination of the hardware, was built with LabVIEW and personal computer (PC) interfacepresents a “SCADA” system for two methods: Fuzzy Logic Controller (FLC) presents closedloop, and a conventional for open loop system. Hence, under temperature of 30°C, anassessment and comparison were carried out for two methods of controls examined at lowmoisture of soil (50%) and high moisture of soil (80 %) for measuring the potential betweenpipeline and anode, current, and power. It was found a decrease of (39.7%) in consumed powerwhen the moisture of soil changing from the low to the high level. It was attained that the closeloop (FLC) was the best method of performance, and consumption of the power.

Fuzzy Logic in Hole Drilling of Composites

1994 ◽  
Author(s):  
Aditya Thadani ◽  
Athamaram H. Soni
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Thrust Force ◽  
Cutting Speed ◽  
Research Data ◽  
Theoretical Research ◽  
Hole Drilling ◽  
Tool Geometry ◽  
Drilling Process ◽  
And Control

Abstract Experimental and theoretical research data was utilized in building a Fuzzy Logic Controller model applied to simulate the drilling process of composite materials. The objective is to have a better understanding and control of delamination of composites during the drilling process and at the same time to improve the hole finish by controlling fraying and splintering. By controlling the main issues in the drilling process such as feed rate, cutting speed, thrust force, and torque generated in addition to the tool geometry, it is possible to optimize the drilling process avoiding the conventionally encountered problems.

Artificial Neural Networks Used As a Rule Selector for Fuzzy Logic Controllers

1993 ◽  
Author(s):  
Shou-Heng Huang ◽  
Ron M. Nelson
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Operating Conditions ◽  
Delta Rule ◽  
Rule Sets ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Set Up ◽  
And Control

Abstract A feedforward, three-layer, partially-connected artificial neural network (ANN) is proposed to be used as a rule selector for a rule-based fuzzy logic controller. This will allow the controller to adapt to various control modes and operating conditions for different plants. A principal advantage of an ANN over a look up table is that the ANN can make good estimates to fill in for missing data. The control modes, operating conditions, and control rule sets are encoded into binary numbers as the inputs and outputs for the ANN. The General Delta Rule is used in the backpropagation learning process to update the ANN weights. The proposed ANN has a simple topological structure and results in a simple analysis and relatively easy implementation. The average square error and the maximal absolute error are used to judge if the correct connections between neurons are set up. Computer simulations are used to demonstrate the effectiveness of this ANN as a rule selector.

Fuzzy Logic Control of a Laboratory Magnetic Levitation System

2003 ◽  
Author(s):  
V. Ram Mohan Parimi ◽  
Piyush Jain ◽  
Devendra P. Garg
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Magnetic Levitation ◽  
Rate Of Change ◽  
Control Laboratory ◽  
Logic Control ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
And Control

This paper deals with the Fuzzy Logic control of a Magnetic Levitation system [1] available in the Robotics and Control Laboratory at Duke University. The laboratory Magnetic Levitation system primarily consists of a metallic ball, an electromagnet and an infrared optical sensor. The objective of the control experiment is to balance the metallic ball in a magnetic field at a desired position against gravity. The dynamics and control complexity of the system makes it an ideal control laboratory experiment. The student can design their own control schemes and/or change the parameters on the existing control modes supplied with the Magnetic Levitation system, and evaluate and compare their performances. In the process, they overcome challenges such as designing various control techniques, choose which specific control strategy to use, and learn how to optimize it. A Fuzzy Logic control scheme was designed and implemented to control the Magnetic Levitation system. Position and rate of change of position were the inputs to Fuzzy Logic Controller. Experiments were performed on the existing Magnetic Levitation system. Results from these experiments and digital simulation are presented in the paper.

Corrosion Protection Features Of the Hyperion Ocean Outfall★

CORROSION ◽  
1959 ◽  
Vol 15 (7) ◽  
pp. 41-46 ◽  
Author(s):  
HARRY J. KEELING
Keyword(s):  
Los Angeles ◽  
Corrosion Protection ◽  
Cathodic Protection ◽  
Current System ◽  
Coal Tar ◽  
Design Life ◽  
Impressed Current ◽  
Cathodic Protection System ◽  
Negative Buoyancy ◽  
Impressed Current Cathodic Protection

Abstract Details are presented on the planning, design and installation of corrosion protection facilities to provide 100-year design life for a 7-mile, 22-inch steel pipe sewer outfall, the outer end of which is in ocean water 340 feet deep. The outfall serves the sewerage systems of Los Angeles and 16 other adjacent municipalities. An impressed current cathodic protection system is used to protect the exterior of the pipe which is wrapped with a multiple-layer coal tar coating reinforced with glass fiber with bonded impregnated asbestos felt shield. A reinforced pneumatically applied cement mortar jacket provides negative buoyancy. Interior is protected by centrifugally-spun mortar lining with epoxy sleeves at welded tie-in joints. Because of the depth of water in which the pipe was to be placed several novel features were necessary. Cathodic protection was applied continuously during installation by the use of zinc anodes. This system was monitored to detect any serious coating holiday before the pipe was laid in deep water. Permanent test leads also were attached to the pipe so performance of the impressed current system could be checked, continuously. After 1½ years' operation there has been very little change in effective coating resistance, a pipe potential of —1.05 volts versus a copper/copper sulfate electrode being maintained with consumption of about 150 ma. 5.2.3

scholarly journals Performance enhancement analysis of an isolated DC-DC converter using fuzzy logic controller

2017 ◽  
Vol 7 (1.2) ◽  
pp. 186 ◽  
Author(s):  
S. Muthu Balaji ◽  
R. Anand ◽  
P. Senthil Pandian
Keyword(s):  
Fuzzy Logic ◽  
High Voltage ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Performance Enhancement ◽  
Supply Voltage ◽  
Boost Converter ◽  
Open Loop ◽  
Voltage Gain ◽  
Power Application

High voltage gain dc-dc converters plays an major role in many modern industrialized applications like PV and fuel cells, electrical vehicles, dc backup systems (UPS, inverter), HID (high intensity discharge) lamps. As usual boost converter experiences a drawback of obtaining a high voltage at maximum duty cycle. Hence in order to increase the voltage gain of boost converter, this paper discusses about the advanced boost converter using solar power application. By using this technique, boost converter attains a high voltage which is ten times greater than the input supply voltage. The output voltage can be further increased to more than ten times the supply voltage by using a parallel capacitor and a coupled inductor. The voltage stress across the switch can be reduced due to high output voltage. The Converter is initially operated in open loop and then it is connected with closed loop. More over the fuzzy logic controller is used for the ripple reduction.

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