Abstract
The speed and pressure of the water flow are determined by the height and volume of the water. The speed of the water flow in the actuator is determined by the use of this flow sensor system. A good tank-based water flow control model should be developed. At a certain point, the actuator stabilizes the rate of water production per minute. Therefore, it is necessary to develop an automatic and precise control technique. Many Artificial Intelligence (AI) methods are used in system optimization. Among them are Particle Swarm Optimization (PSO), Neural Network (NN), Fuzzy Inference System (FIS), and ANFIS. Adaptive Neuro Fuzzy Inference System (ANFIS) is a combination of NN and FIS. In this study, the PSO method was combined with ANFIS. This hybrid method produces better optimization compared to the previous method. The best water level control simulation results are PSO-ANFIS with an overshot of 0.572 pu, undershot of 0.563 pu, and flow output overshot of 0.008 pu, undershot of 0.009 pu.
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