This is a control system identification study using a fuzzy logic algorithm to handle the issue of the controller parameter tuning in a control system with time delay. Among the studies related to the controller parameter tuning for control system identification, Yunwana-Seborg's controller parameter tuning method showed a rapid response in plants with no time delay or with small-time delays due to the phase error caused by Pade's first-order approximation method. However, a large time delay causes a higher time delay estimate and it cannot be applied to the actual system. Zigler-Nichols' loop tuning method, which is widely applied in the industrial field, requires much time to tune controller parameters because it goes through many trials and errors. Although Cohen-Coon's controller parameter tuning method using the process response curve has an advantage of shortening the time required for controller parameter tuning than the Zigler-Nichols’s loop tuning method, it can only be applied to an open loop system. To overcome these shortcomings, Suh proposed to set a phase controller in Pade’s approximation method to reduce the phase error, between the estimated model transfer function while converting time delay into Pade’s first-order approximation and the time delay of an actual plant, as a controller parameter tuning. However, it has a disadvantage that it is not analytical because this method derives by substituting a phase regulator proportional to a constant value in time delay. This study discussed an analytical method that could solve the issue of the phase error between the actual plant and the estimated transfer function using a fuzzy logic algorithm. This study proved that the proposed method could overcome the shortcomings of causing the large time delay estimation and provide quick response and stability by suggesting a logical way to set up a phase regulator based on the comparisons of Zielger-Nichols' loop tuning method, Yunwana-Seborg's method, and the proposed controller parameter tuning method.