Desain Optimasi PID Controller Pada Temperatur Heating Furnace Berbasis Ant Colony Algorithm (ACO) - Kusuma Apsari, Venda; Ali, Machrus; Nurohmah, Hidayatul; Rukslin, Rukslin (FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia), 2021)
A furnace is a tool for heating materials, oil, and so on, which usually uses gas, coal, and oil as fuel. Temperature is the main parameter that needs to be controlled in order to remain stable, precise, and of course improve fuel efficiency. As technology develops, there are several methods that can be used to control temperatures that are more reliable than conventional controls. The technology is Proportional Integral Derivative (PID) controller. PID controllers have been proven to be the best controllers and are widely used in industry. But to determine the gain from the PID value is still not accurate and can affect temperature stability, the response is also still slow to reach the desired set point. Therefore, this paper is to simulate a better PID gain value by using the artificial intelligence tuning method. The artificial intelligence method is Ant Colony Optimization (ACO). The simulation results and discussion show that the best design is PID-ACO with 0.0081 overshot, no undershot, and the fastest settling time is 35 seconds