Researches Related to Control Engineering

Title: Smart Two-Tank Water Quality and Level Detection System via IoT

(by): Engr. Olisa Samuel Chukwuemeka, Engr. Bonaventure Onyeka Ekengwu, Engr. Nnaemeka Asiegbu, Dr. Abdulhakim Shittu (Ph.D), Juliet Olisa

Abstract: The two-tank water system is common practice for the storage and distribution of water in many homes. Water is transported via a pipeline network from the storage tank (lower tank) to the distribution tank (overhead tank) using an electric pumping machine. Due to limited control in the existing pumping system, water wastage becomes inevitable. Determining the quality of water in the overhead tank before supply in the home is still un-addressed. In this work, an integrated Android mobile App and a control system were developed to assess the water quality, perform level check in the overhead tank, and activate intelligent pumping control. An ultrasonic pulse-echo technique was used for water level checks, while the water turbidity and pH signals were used for water quality checks. Three-level control conditions (LC_1, LC_2, LC_3) and two water quality check conditions (QC_1 and QC_2) were devised and used in the intelligent control algorithm of the system. Control valve1 regulates the flushable poor water quality while valve2 regulates the house’s supply of good water quality. The absolute relative error between the expected time and the system time of filling the tank level was observed to be less than 10% when the water volume is less than 81%. Hence, distortion in the sensory signals increases and worsen as the water level approaches the ultrasonic sensor position. The poor internet signal network was observed to affect the real-time monitoring and automation of the system control through delay in system responses to commands. However, the average recorded response time of the system is 3 s, and it could be less in the situation of good internet network services.

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conceptual architecture of the system

Title: Performance Evaluation of An Optimized PID Controller for Networked Control System Using Ant Colony Optimization

(by): Engr. Eke-Nnodu Chukwuebuka Obinana, Dr. Udeze Chidiebele Chinwendu, Engr. Chukwudi Chukwudozie, Engr. Ndefo Mmasom Iruoma, Engr. Ugwu Henry

Abstract: The potentials of controlling systems remotely led researchers to develop systems comprising of networks and control systems. Such systems have been known by various names, but it is lately referred to as Networked Control System (NCS). The inherent challenges with communication networks such as latency, packet drop/loss, congestion etc. creates major challenges for such system especially in the transmission of control signal from one component to another in real time applications. Proportional Integral Derivative (PID) controller is used to estimate factors which can cause delay during data transfer among system components. This work compensates this delay with the use of Ant Colony Optimization (ACO) technique to improve the parameters of the PID controller such that performance of the NCS will be improved. The work will evaluate the performance of the NCS after ACO technique has been used to tune the parameters of PID and compare it with the performance of NCS when fuzzy tuned PID controller and PID controller are used. The performance obtained by simulation shows that the performance of the ACO technique performed better than the fuzzy tuned PID controller and PID controller. The simulation of the performance was done using Matlab/Simulink 2016b and TrueTime toolbox. Indexed Terms- Ant Colony Optimization (ACO), Networked Control System (NCS), Optimization, Proportional Integral Derivative (PID).

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Title: Improving the Reliability and Security of Active Distribution Networks Using SCADA Systems

(by): Dr. Eneh Nnenna Joy, Harris Onyekachi Orah, Aka Benneth Emeka

Abstract: The traditional electricity distribution system is rapidly shifting from the passive infrastructure to a more active infrastructure, giving rise to a smart grid. In this project an active electricity distribution network and its components have been studied. A 14-node SCADA-based active distribution network model has been proposed for managing this emerging network infrastructure to ensure reliability and protection of the network The proposed model was developed using matlab /simulink software and the fuzzy logic toolbox. Surge arresters and circuit breakers were modelled and deployed in the network at different locations for protection and isolation of fault conditions. From the reliability analysis of the proposed model, the failure rate and outage hours were reduced due to better response of the system to power fluctuations and fault conditions.

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