Water Level Tank Using Fuzzy Logic Controller

Mohd Salmi, Munirah (2016) Water Level Tank Using Fuzzy Logic Controller. Project Report. UTeM, Melaka, Malaysia . (Submitted)

Text (24 Pages) Water Level Tank Using Fuzzy Logic Controller.pdf - Submitted Version Download (1MB)

Abstract

Water Level Control is the most important element in the process control. Application of a controller is widely used in industries especially for mould and die casting process and also for the level monitoring of water in reservoirs. The most controller used in industries is PID Controller, but the system is poor effected when the parameter in not chosen nicely. On the other hand, by using Fuzzy Logic Controller, the control performances are increase in time response and overshoot percentage. Jn order to get the accuracy on Level changes, a simple work project water level sensor and water level controller based on Fuzzy Logic is proposed. The hardware of the project is based on the suitable and simplicity of the tank shape. The tanks used in the project were seal with water proof liquid to avoid the water from flowing out. The experiment is conduct to find the resistance value in order to complete the transfer function of the selection model of the tank. The Fuzzy Logic Controller is select as the controller to control the system for accuracy of level in the tank. 'fbe technique use in this project is based on Takagi-Sugeno Method which are the typically in the case of constant output. This method is selected due to the types of motor pump that acting as actuator in the tank. All the range values at the membership function and the rules table are decided based on the different of error and rate of change in the tanks. The testing on the parameter level is consists of the microcontroller with and without the fuzzy controller. At the end of the experiment, the differences between the two experiments are shown. After implemented the controller into the system, the time response had shown an improvement compared with non-controller adaption into the system. The time response had shown the improvement from 8.74 second to 0.2667 sec for rise time. Meanwhile for settling time improved from 24.2 second to 6.980 second. The overshoot percentages from 4.32% to 0% with time peak 18 second to 7 second. The result is shown illustrated in sequences.

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