Remote monitoring and control of LQR-PI controller parameters for an oil pipeline transport system

摘要

Today's main energy sources such as natural gas, petrol, and petroleum products are transported via pipelines that are safe at long distances. Most of these pipelines are buried and their integrity is highly important. Deformations such as corrosions, dents, and cracks destruct the integrity of the pipeline and they can cause highly dangerous results. In oil transport system, at every specific interval of distance when petroleum products enter circular pipelines at uniform velocity due to no-slip condition, transported fluid particles come in contact with the surface of the pipe results in a complete stop. This complete stop causes higher pressure drops which lower the flow rates of the fluids. Due to higher pressure drops, cracks/bursts occur on the pipelines and also affect the production performance by lowering flow rate at destination during transportation. Hence, prevention of such adversities can be done by remotely monitoring pressure and flow by controlling the operation of control valves through modern optimal controllers as local intelligent decision controllers which unveils fast settling time on the setpoint at a desired interval of time along with supervisory control and data acquisition. The proposed work uses Linear Quadratic Regulator-Proportional Integral (LQR-PI) controller in LabVIEW platform to regulate the desired flow rate by monitoring the various pressure signals during the oil transportation through pipelines remotely. The performance analyses are verified experimentally with the real-time data of pressure and flow which are monitored through supervisory control and data acquisition to provide instantaneous information for the operator. The experimental results spectacle the enhanced performance of flow rate control by LQR-PI controller in comparison with Gain and Phase Margin-Proportional Integral (GPM-PI) and Zigler Nicholas-Proportional Integral (ZN-PI) controllers by its faster settling time and effective robustness.