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One of the major sources of petroleum products is obtained from the sea (offshore and onshore). Here the major problem faced by the worker is, maintaining the constant pressure and flow till the extreme ends. In this paper, the parameters such as pressure and flow are maintained constantly by implementing control valves depending on the different pressure and flow rate of the transmitting pipe. PLC (Programmable Logical Controller) is used to automatically regulate the flow and pressure during petroleum product transportation by controlling the percentage of opening of the control valves and pumps respectively. The required set point for pressure and flow rate are obtained by implementing a suitable controller that regulates in a long transmitting concrete pipes. For this, a PLC based PID controller is developed and its open loop responses are identified. The simulation studies are carried out in the MATLAB/SIMULINK platform to ensure the performance of the controller. The controller tuning is done by ZN (Ziegler and Nicholas) PID and Simple-IMC (Internal Model Control) PID, Shams tuning IMC-PID controller. The simulation result provides better control action when Shams IMC-PID controller is used. Shams IMC-PID controller is experimentally verified on the lab scale-setup and the results prove that it provides most consistent performance as compared to ZN and Simple-IMC PID controllers.

Environmental impacts are increased on human/animal health day by day. This research work focussed on the implementation of advanced control theory for the reduction of SO2 coming out from thermal power plants. Flue gas desulphurization technique in which packed column is used for gas–liquid mass transfer by externally adding H2O2 with H2SO4 as the scrubbing liquid. The concept of fractional calculus has tremendous potential to improve the controller performance. Hence, the fractional calculus is incorporated with coefficient diagram method to tune the proportional–integral–derivative controller, and it is named as fractional-order-based coefficient diagram method (FOCDM-PIλDµ) controller. Flow rate of externally added H2O2 is regulated by fractional-order-based coefficient diagram method PIλDµ controller tuned by particle swarm optimization algorithm. The performance of fractional-order-based coefficient diagram method controller is analysed and compared with the classical controllers such as Ziegler–Nichols proportional–integral–derivative and coefficient diagram method–based proportional–integral–derivative controller in a lab-scale SO2 emission control experimental setup.

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Apart from being fundamental in industry 4.0, IoT also extends its capability to smart transportation in an oil pipeline system. The initiation of the Internet of Things has witnessed incredible success in the application of wireless sensor networks and ubiquitous computing for various smart-control applications. In the oil industry, for smooth, accident-less, long-range pipeline transportation, data communication through wireless sensor networks plays a predominant role in IoT. For the prominent integration with the internet, it is essential to fabricate a middleware by overcoming the shortcomings like interoperability and heterogeneity. But yet there is no compact, integrated IoT module with power and energy-efficient configuration to take the modern technology to the next level of innovation of wireless network systems with embedded sensors in the oil industry. Hence, this paper presents a novel, unique-integrated compact, smart IoT module that aims at reducing costs associated with commercial data loggers and sensing modules, requiring control and data storage that need proprietary software. Other usual drawbacks of commercial solutions are limited sensor connections with low expansion flexibility and maintenance restricted to the manufacturer and long cable communication distances. The proposed integrated smart IoT module operation relies on free software, allowing online distribution and communication with a cloud server wirelessly via Wi-Fi through message queuing telemetry transport (MQTT) and hypertext transfer protocol (HTTP) for efficient data communication. A secured highlevel engineering web page called Web Monitor was developed for online data analysis with real-time monitoring and control to afford intelligent transportation in oil pipelines. Further, in this work, the real-time validation of the proposed smart IoT module performance in the oil pipeline during abnormal circumstances is also provided. Through this integrated IoT module, the entire oil pipeline network with each substation can be interconnected and controlled beneficial with its intelligence, low cost, and portability.