Liquid Level Controlling Using the Intelligent Techniques

The control of liquid levels is one of the most important topics in many industrial applications. In this work, a liquid level control system model was built in a water system consisting of 2-tanks. The control system was designed using intelligent techniques, which were represented by adopting Fuzzy Logic to adjust the important factors in the PID controller. Also, the design factors for the system were chosen, such as the resistance of the valves to flow and the capacity of the tanks, using a genetic algorithm with multiple-objectives optimization. The objectives were to derive mathematical equations for the damping factor, settling time, and steady-state error. The results of optimization have resulted in obtaining a set of design factors for the system that enables an acceptable response based on the application used. Additionally, the design of the main controller is in two types based on the membership function, the number of rules, and the other factors. The results showed that the controller used can reach an acceptable rise time and a significantly lower maximum overshoot compared to the comparable controller.